diff --git a/dpmhm/datasets/transformer.py b/dpmhm/datasets/transformer.py
index edcf4ca..02ed1fb 100644
--- a/dpmhm/datasets/transformer.py
+++ b/dpmhm/datasets/transformer.py
@@ -432,8 +432,11 @@ def _drop_meta(X):
             return {'feature': X['feature'], 'label': X['label']}
 
         ds = self.to_windows(self._dataset_origin, self._window_size, self._hop_size)
+        # ds = utils.restore_shape(ds, 'feature', self.data_dim)
 
-        return ds.map(_drop_meta, num_parallel_calls=tf.data.AUTOTUNE) if self._no_meta else ds
+        if self._no_meta:
+            ds = ds.map(_drop_meta, num_parallel_calls=tf.data.AUTOTUNE)
+        return ds
 
     # @property
     # def full_label_dict(self) -> dict:
diff --git a/dpmhm/datasets/utils.py b/dpmhm/datasets/utils.py
index b5dcd0d..d730eb1 100644
--- a/dpmhm/datasets/utils.py
+++ b/dpmhm/datasets/utils.py
@@ -174,6 +174,8 @@ def random_split_dataset(ds:Dataset, splits:dict, *, shuffle_size:int=None, ds_s
 		dictionary specifying the name and ratio of the splits.
 	shuffle_size
 		size of shuffle, 1 for no shuffle (deterministic), None for full shuffle.
+	ds_size
+		real size of `ds`.
 	kwargs
 		other keywords arguments to the method `shuffle()`, e.g. `reshuffle_each_iteration=False`, `seed=1234`.
 
@@ -222,7 +224,7 @@ def split_dataset(ds:Dataset, splits:dict={'train':0.7, 'val':0.2, 'test':0.1},
 	splits
 		dictionary specifying the name and ratio of the splits.
 	labels
-		list of categories. If given apply the few-shot style split (i.e. split per category) otherwise apply the normal split.
+		list of categories. If given apply the few-shot style split (i.e. split per category) otherwise apply the normal split. This is incompatible with the keyword argument `ds_size`.
 	kwargs
 		arguments for `random_split_dataset()`
 
@@ -241,7 +243,12 @@ def split_dataset(ds:Dataset, splits:dict={'train':0.7, 'val':0.2, 'test':0.1},
 		ds = extract_by_category(ds, labels)
 		dp = {}
 		for n, (k,v) in enumerate(ds.items()):
-			dq = random_split_dataset(v, splits, **kwargs)
+			try:
+				dq = random_split_dataset(
+					v, splits, ds_size=None, **kwargs
+				)
+			except:
+				raise Exception("`ds_size` not supported in per category split")
 			if n == 0:
 				dp.update(dq)
 			else:
@@ -251,7 +258,7 @@ def split_dataset(ds:Dataset, splits:dict={'train':0.7, 'val':0.2, 'test':0.1},
 	return dp
 
 
-def restore_shape(ds:Dataset, key:int|str=None, shape:tuple[int]=None) -> Dataset:
+def restore_shape(ds:Dataset, key:str|int=None, shape:tuple[int]=None) -> Dataset:
 	"""Restore the shape of a dataset.
 
 	Parameters
@@ -274,35 +281,31 @@ def restore_shape(ds:Dataset, key:int|str=None, shape:tuple[int]=None) -> Datase
 			shape = list(ds.take(1).as_numpy_iterator())[0].shape
 		except:
 			shape = list(ds.take(1).as_numpy_iterator())[0][key].shape
+	# print(shape, key)
 
 	@tf.function
 	def _mapper(X):
 		try:
+			# flat dataset
 			Y = tf.ensure_shape(X, shape)
 		except:
+			# nested dataset
 			Y = X.copy()
-			Y[key] = tf.ensure_shape(Y[key], shape)  # will create an extra dimension if `key=None`
+			Y[key] = tf.ensure_shape(X[key], shape)
 		return Y
-	# if key is None:
-	# 	if shape is None:
-	# 		shape = list(ds.take(1).as_numpy_iterator())[0].shape
-
-	# 	@tf.function
-	# 	def _mapper(X):
-	# 		Y = tf.ensure_shape(X, shape)
-	# 		return Y
-	# else:
-	# 	if shape is None:
-	# 		shape = list(ds.take(1).as_numpy_iterator())[0][key].shape
-
-	# 	@tf.function
-	# 	def _mapper(X):
-	# 		Y = X.copy()
-	# 		Y[key] = tf.ensure_shape(Y[key], shape)
-	# 		return Y
-
-	return ds.map(_mapper, num_parallel_calls=tf.data.AUTOTUNE)
-	# return ds.map(lambda x,y: (tf.ensure_shape(x, shape), y), num_parallel_calls=tf.data.AUTOTUNE)
+
+	@tf.function
+	def _mapper_tuple(*X):
+		# tuple dataset
+		# This code looks suspicious but actually works...
+		Y = list(X)
+		Y[key] = tf.ensure_shape(X[key], shape)
+		return Y  # automatically converted back to tuple
+
+	if type(ds.element_spec) is tuple:
+		return ds.map(_mapper_tuple, num_parallel_calls=tf.data.AUTOTUNE)
+	else:
+		return ds.map(_mapper, num_parallel_calls=tf.data.AUTOTUNE)
 
 
 def restore_cardinality(ds:Dataset, card:int=None) -> Dataset:
diff --git a/notebooks/models/SimCLR.ipynb b/notebooks/models/SimCLR.ipynb
index cf3af3c..0c7a386 100644
--- a/notebooks/models/SimCLR.ipynb
+++ b/notebooks/models/SimCLR.ipynb
@@ -22,7 +22,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2024-06-18 12:51:51.637414: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n"
+      "2024-06-18 18:09:36.487979: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n"
      ]
     }
    ],
@@ -241,10 +241,9 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2024-06-18 12:51:52.548080: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
-      "2024-06-18 12:51:53.733647: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
-      "2024-06-18 12:51:53.970254: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
-      "2024-06-18 12:51:54.199143: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+      "2024-06-18 18:09:38.324186: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:09:38.600347: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:09:38.870577: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
      ]
     }
    ],
@@ -261,7 +260,7 @@
     ")\n",
     "\n",
     "# ds0 = ds_all['train']\n",
-    "ds_size = utils.get_dataset_size(ds0)\n",
+    "# ds_size = utils.get_dataset_size(ds0)\n",
     "\n",
     "channels = ['DE', 'FE', 'BA']  # will rule out the normal data\n",
     "\n",
@@ -308,7 +307,7 @@
     "\n",
     "For any spectral sample `x`, we apply the spectrogram augmentation provided in `transformer` and build a paired dataset of form `(x1, x2)` for SSL.\n",
     "\n",
-    "Notably, the paired dataset preserve the randomness: a paired sample `(x1, x2)` is two randomly transformed version of a common `x`. Let's check this:\n",
+    "Notably, the paired dataset preserves randomness: a paired sample `(x1, x2)` is two randomly transformed version of a common `x`. Let's check this.\n",
     "\n",
     "Alternatively, the spectrogram augmentation can be implemented also via keras preprocessing layers as follows \n",
     "\n",
@@ -331,12 +330,12 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2024-06-18 12:51:55.896356: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+      "2024-06-18 18:09:40.891371: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
      ]
     },
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -346,7 +345,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -356,7 +355,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -405,7 +404,7 @@
     "\n",
     "Then one can call `model.fit()` on the dataset `((x1, x2), fake_label)` for training, independant of the backend.\n",
     "\n",
-    "The logic behind this solution is that the `Model` class in Keras is actually designed for supervised learning, of type `y=f(x)`. A customized Keras model implements `f` in the method `.call(x)`, which should not be confused with `.fit(x,y)`. The argument `inputs` to `.call(inputs)` can be a tuple, but the output has to be a single tensor (if the output has several terms then only the first is passed to the loss function). The type of dataset passed to `model.fit()` has always to be `(x,y)`: no matter how many actual terms in `x` (and `y`), they need to be packed into a single tensor properly. The loss function takes `(y_true, y_pred)` with `y_true` from the dataset and `y_pred` from the output of `.call()`. Any deviation from this setting should be adapted, like the solution outlined above."
+    "The logic behind this solution is that the `Model` class in Keras is actually designed for supervised learning, of type `y=f(x)`. A customized Keras model implements `f` in the method `.call(x)`, which should not be confused with `.fit(x,y)`. The argument `inputs` to `.call(inputs)` can be a tuple, but the output has to be a single tensor (if the output has several terms then only the first is passed to the loss function). The type of dataset passed to `model.fit()` has always to be `(x,y)`: no matter how many actual terms in `x` (and `y`), they need to be packed in a single tensor properly. The loss function takes `(y_true, y_pred)` with `y_true` from the dataset and `y_pred` from the output of `.call()`. Any deviation from this setting should be adapted, like the solution outlined above."
    ]
   },
   {
@@ -426,7 +425,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2024-06-18 12:51:56.804030: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+      "2024-06-18 18:09:41.830671: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
      ]
     },
     {
@@ -501,7 +500,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2024-06-18 12:51:57.366973: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+      "2024-06-18 18:09:42.421424: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
      ]
     },
     {
@@ -535,7 +534,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2024-06-18 12:52:01.305788: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+      "2024-06-18 18:09:46.742143: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
      ]
     },
     {
@@ -624,7 +623,7 @@
        "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
        "│ resnet50 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Functional</span>)           │ ?                      │    <span style=\"color: #00af00; text-decoration-color: #00af00\">23,587,712</span> │\n",
        "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
-       "│ projector (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Sequential</span>)          │ ?                      │   <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (unbuilt) │\n",
+       "│ Projection_head (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Sequential</span>)    │ ?                      │   <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (unbuilt) │\n",
        "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
        "</pre>\n"
       ],
@@ -634,7 +633,7 @@
        "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
        "│ resnet50 (\u001b[38;5;33mFunctional\u001b[0m)           │ ?                      │    \u001b[38;5;34m23,587,712\u001b[0m │\n",
        "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
-       "│ projector (\u001b[38;5;33mSequential\u001b[0m)          │ ?                      │   \u001b[38;5;34m0\u001b[0m (unbuilt) │\n",
+       "│ Projection_head (\u001b[38;5;33mSequential\u001b[0m)    │ ?                      │   \u001b[38;5;34m0\u001b[0m (unbuilt) │\n",
        "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
       ]
      },
@@ -703,425 +702,3654 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "id": "86f1003b",
+   "id": "b4365761-f936-4760-a152-96476a4c3a5c",
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 764ms/step - loss: 11.3896"
+      "Epoch 1/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 892ms/step - loss: 6.9124"
      ]
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2024-06-18 12:52:20.727342: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
-      "2024-06-18 12:52:24.450913: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+      "2024-06-18 18:10:09.208755: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:10:13.820833: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m18s\u001b[0m 2s/step - loss: 11.0070 - val_loss: 5.4263\n"
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m21s\u001b[0m 2s/step - loss: 6.9296 - val_loss: 8.4720\n",
+      "Epoch 2/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 167ms/step - loss: 12.8761"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:10:25.864272: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:10:30.300608: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m14s\u001b[0m 1s/step - loss: 12.5508 - val_loss: 7.6275\n",
+      "Epoch 3/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 179ms/step - loss: 11.5524"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:10:35.801590: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:10:40.545181: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: 11.0819 - val_loss: 8.7005\n",
+      "Epoch 4/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 178ms/step - loss: 5.6673"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:10:46.104997: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:10:50.567205: W tensorflow/core/kernels/data/prefetch_autotuner.cc:52] Prefetch autotuner tried to allocate 983080 bytes after encountering the first element of size 983080 bytes.This already causes the autotune ram budget to be exceeded. To stay within the ram budget, either increase the ram budget or reduce element size\n",
+      "2024-06-18 18:10:50.568485: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: 5.4876 - val_loss: 2.0394\n",
+      "Epoch 5/100\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:10:55.142388: W tensorflow/core/kernels/data/prefetch_autotuner.cc:52] Prefetch autotuner tried to allocate 983080 bytes after encountering the first element of size 983080 bytes.This already causes the autotune ram budget to be exceeded. To stay within the ram budget, either increase the ram budget or reduce element size\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 167ms/step - loss: 10.1115"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:10:56.054813: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:11:00.547146: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: 9.6603 - val_loss: 5.7913\n",
+      "Epoch 6/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 166ms/step - loss: 4.5024"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:11:05.886791: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:11:10.474296: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: 4.6484 - val_loss: 4.0656\n",
+      "Epoch 7/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 161ms/step - loss: 5.4390"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:11:15.769208: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:11:20.326042: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: 5.5558 - val_loss: -0.6790\n",
+      "Epoch 8/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 171ms/step - loss: 4.2635"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:11:25.390925: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:11:29.634606: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 1s/step - loss: 4.4252 - val_loss: 3.1120\n",
+      "Epoch 9/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 170ms/step - loss: 4.6496"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:11:34.774161: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:11:38.903735: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 1s/step - loss: 4.2750 - val_loss: -3.4895\n",
+      "Epoch 10/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 184ms/step - loss: 2.6769"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:11:44.437200: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:11:48.955114: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: 2.8174 - val_loss: 2.0947\n",
+      "Epoch 11/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 192ms/step - loss: -0.5508"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:11:54.586981: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:11:58.724273: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -0.4814 - val_loss: 0.4344\n",
+      "Epoch 12/100\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:12:03.403751: W tensorflow/core/kernels/data/prefetch_autotuner.cc:52] Prefetch autotuner tried to allocate 983080 bytes after encountering the first element of size 983080 bytes.This already causes the autotune ram budget to be exceeded. To stay within the ram budget, either increase the ram budget or reduce element size\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 178ms/step - loss: 8.7092"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:12:04.365458: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:12:08.822988: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 1s/step - loss: 8.1540 - val_loss: 6.2128\n",
+      "Epoch 13/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 158ms/step - loss: 0.6313"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:12:15.183445: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:12:19.675334: W tensorflow/core/kernels/data/prefetch_autotuner.cc:52] Prefetch autotuner tried to allocate 983080 bytes after encountering the first element of size 983080 bytes.This already causes the autotune ram budget to be exceeded. To stay within the ram budget, either increase the ram budget or reduce element size\n",
+      "2024-06-18 18:12:19.677475: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: 0.7511 - val_loss: -1.8104\n",
+      "Epoch 14/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 169ms/step - loss: -2.0619"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:12:25.013301: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:12:29.252134: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -2.2002 - val_loss: 4.6767\n",
+      "Epoch 15/100\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:12:33.648918: W tensorflow/core/kernels/data/prefetch_autotuner.cc:52] Prefetch autotuner tried to allocate 983080 bytes after encountering the first element of size 983080 bytes.This already causes the autotune ram budget to be exceeded. To stay within the ram budget, either increase the ram budget or reduce element size\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 179ms/step - loss: -0.8343"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:12:34.615961: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:12:39.440353: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -0.9387 - val_loss: -14.5494\n",
+      "Epoch 16/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 185ms/step - loss: -3.6555"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:12:44.952748: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:12:49.357946: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 1s/step - loss: -3.5393 - val_loss: -2.4177\n",
+      "Epoch 17/100\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:12:54.782265: W tensorflow/core/kernels/data/prefetch_autotuner.cc:52] Prefetch autotuner tried to allocate 983080 bytes after encountering the first element of size 983080 bytes.This already causes the autotune ram budget to be exceeded. To stay within the ram budget, either increase the ram budget or reduce element size\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 172ms/step - loss: -1.5360"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:12:55.710395: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:13:00.054829: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -1.7341 - val_loss: -9.3314\n",
+      "Epoch 18/100\n",
+      "\u001b[1m5/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 189ms/step - loss: 1.8624"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:13:05.666234: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 191ms/step - loss: 1.6219"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:13:10.098532: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: 1.4500 - val_loss: 16.3947\n",
+      "Epoch 19/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 166ms/step - loss: -2.4136"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:13:15.758350: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:13:20.251225: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -2.5383 - val_loss: -0.1033\n",
+      "Epoch 20/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 186ms/step - loss: -6.6573"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:13:25.556171: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:13:29.606840: W tensorflow/core/kernels/data/prefetch_autotuner.cc:52] Prefetch autotuner tried to allocate 983080 bytes after encountering the first element of size 983080 bytes.This already causes the autotune ram budget to be exceeded. To stay within the ram budget, either increase the ram budget or reduce element size\n",
+      "2024-06-18 18:13:29.608247: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 1s/step - loss: -6.4250 - val_loss: 4.5819\n",
+      "Epoch 21/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 167ms/step - loss: -1.6437"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:13:35.337827: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:13:39.544389: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -0.9032 - val_loss: 2.8966\n",
+      "Epoch 22/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 177ms/step - loss: -5.5454"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:13:45.004360: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:13:48.838561: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 957ms/step - loss: -5.3519 - val_loss: 2.6861\n",
+      "Epoch 23/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 187ms/step - loss: 0.3586"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:13:54.224715: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:13:58.203296: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 992ms/step - loss: 0.4053 - val_loss: -2.2514\n",
+      "Epoch 24/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 166ms/step - loss: -6.7801"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:14:03.717092: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:14:07.764044: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 996ms/step - loss: -6.7306 - val_loss: -1.5553\n",
+      "Epoch 25/100\n",
+      "\u001b[1m5/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 187ms/step - loss: -6.8830"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:14:13.274771: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 192ms/step - loss: -6.6996"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:14:17.779945: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -6.5686 - val_loss: -5.4542\n",
+      "Epoch 26/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 175ms/step - loss: -3.1053"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:14:23.330822: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:14:27.827431: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -3.6466 - val_loss: -0.1497\n",
+      "Epoch 27/100\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:14:32.143922: W tensorflow/core/kernels/data/prefetch_autotuner.cc:52] Prefetch autotuner tried to allocate 983080 bytes after encountering the first element of size 983080 bytes.This already causes the autotune ram budget to be exceeded. To stay within the ram budget, either increase the ram budget or reduce element size\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m5/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 188ms/step - loss: -6.3168"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:14:33.138493: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 190ms/step - loss: -5.8908"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:14:37.491990: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -5.5865 - val_loss: 15.1315\n",
+      "Epoch 28/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 180ms/step - loss: -8.2304"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:14:42.951480: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:14:47.442141: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -7.7805 - val_loss: 4.4031\n",
+      "Epoch 29/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 165ms/step - loss: -0.6011"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:14:52.832610: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:14:57.269518: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -0.9942 - val_loss: 6.1328\n",
+      "Epoch 30/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 163ms/step - loss: -4.0056"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:15:02.658658: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:15:07.189625: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -3.9247 - val_loss: -13.0043\n",
+      "Epoch 31/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 183ms/step - loss: -2.2257"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:15:12.418038: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:15:16.833029: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -2.7076 - val_loss: 2.5819\n",
+      "Epoch 32/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 178ms/step - loss: -3.9103"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:15:22.124448: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:15:26.489272: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -3.8572 - val_loss: 3.1211\n",
+      "Epoch 33/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 167ms/step - loss: -5.6054"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:15:31.818778: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:15:36.383552: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -5.4585 - val_loss: -1.9249\n",
+      "Epoch 34/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 169ms/step - loss: -4.8188"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:15:41.314850: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:15:45.420941: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 1s/step - loss: -4.9595 - val_loss: 0.2965\n",
+      "Epoch 35/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 183ms/step - loss: -0.8020"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:15:51.038878: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:15:55.491702: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 1s/step - loss: -0.8595 - val_loss: -2.6825\n",
+      "Epoch 36/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 191ms/step - loss: -2.3562"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:16:01.927192: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:16:06.430230: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -2.7804 - val_loss: -8.9331\n",
+      "Epoch 37/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 167ms/step - loss: 0.4411"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:16:11.673126: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:16:16.004676: W tensorflow/core/kernels/data/prefetch_autotuner.cc:52] Prefetch autotuner tried to allocate 983080 bytes after encountering the first element of size 983080 bytes.This already causes the autotune ram budget to be exceeded. To stay within the ram budget, either increase the ram budget or reduce element size\n",
+      "2024-06-18 18:16:16.007818: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -0.1042 - val_loss: -16.1886\n",
+      "Epoch 38/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 185ms/step - loss: -3.5952"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:16:21.540905: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:16:25.870780: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -3.7506 - val_loss: -10.4527\n",
+      "Epoch 39/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 158ms/step - loss: -5.3716"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:16:31.110006: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:16:35.595600: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -5.5834 - val_loss: 3.4566\n",
+      "Epoch 40/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 171ms/step - loss: -3.5178"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:16:41.234972: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:16:45.612351: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -3.7368 - val_loss: -12.6320\n",
+      "Epoch 41/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 164ms/step - loss: -6.8261"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:16:51.112069: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:16:55.666424: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -7.1106 - val_loss: 7.6272\n",
+      "Epoch 42/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 183ms/step - loss: -8.7126"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:17:00.880629: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:17:05.390775: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -8.2087 - val_loss: -10.5751\n",
+      "Epoch 43/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 190ms/step - loss: -5.0250"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:17:11.048362: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:17:15.381954: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -4.6601 - val_loss: -4.9451\n",
+      "Epoch 44/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 178ms/step - loss: -8.1202"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:17:20.946581: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:17:25.417323: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -8.2154 - val_loss: -7.8549\n",
+      "Epoch 45/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 165ms/step - loss: -6.7602"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:17:30.514702: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:17:34.705780: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 1s/step - loss: -6.4242 - val_loss: 0.7701\n",
+      "Epoch 46/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 178ms/step - loss: -6.3810"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:17:39.839261: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:17:44.534435: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -6.7210 - val_loss: -8.1021\n",
+      "Epoch 47/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 169ms/step - loss: -8.8549"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:17:50.028695: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:17:54.412878: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -8.8903 - val_loss: 3.1441\n",
+      "Epoch 48/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 168ms/step - loss: 2.6957"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:17:59.385766: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:18:04.027094: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: 2.5333 - val_loss: -8.4327\n",
+      "Epoch 49/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 165ms/step - loss: -1.3508"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:18:09.538067: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:18:13.981548: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -1.3025 - val_loss: -15.0472\n",
+      "Epoch 50/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 174ms/step - loss: 1.3635"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:18:19.357101: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:18:23.965781: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: 1.0969 - val_loss: -3.7479\n",
+      "Epoch 51/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 183ms/step - loss: -0.7390"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:18:29.115943: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:18:33.445726: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 1s/step - loss: -1.0481 - val_loss: -10.5202\n",
+      "Epoch 52/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 176ms/step - loss: -11.6030"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:18:38.889366: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:18:43.178304: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -11.3790 - val_loss: -13.1513\n",
+      "Epoch 53/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 183ms/step - loss: -10.5764"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:18:48.657926: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:18:53.211969: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -10.1003 - val_loss: 4.2854\n",
+      "Epoch 54/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 169ms/step - loss: -7.4156"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:18:58.548349: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:19:02.966849: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -7.8462 - val_loss: -7.0540\n",
+      "Epoch 55/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 175ms/step - loss: -3.1756"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:19:08.422394: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:19:12.869915: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -3.2910 - val_loss: 6.9765\n",
+      "Epoch 56/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 163ms/step - loss: -11.6347"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:19:18.079420: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:19:22.579817: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -11.3826 - val_loss: 4.3485\n",
+      "Epoch 57/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 175ms/step - loss: -3.6050"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:19:27.908777: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:19:32.062075: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 1s/step - loss: -3.3435 - val_loss: -3.5171\n",
+      "Epoch 58/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 177ms/step - loss: -5.5408"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:19:37.522556: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:19:41.710251: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -5.4626 - val_loss: -6.0188\n",
+      "Epoch 59/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 171ms/step - loss: -10.9216"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:19:47.062815: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:19:51.739654: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -10.2020 - val_loss: 1.2489\n",
+      "Epoch 60/100\n",
+      "\u001b[1m5/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 203ms/step - loss: -6.6877"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:19:57.290239: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 204ms/step - loss: -6.0780"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:20:01.884258: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -5.6425 - val_loss: -7.5831\n",
+      "Epoch 61/100\n",
+      "\u001b[1m5/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 198ms/step - loss: -5.9261"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:20:07.410244: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 203ms/step - loss: -6.1239"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:20:11.715078: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -6.2652 - val_loss: -20.7139\n",
+      "Epoch 62/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 165ms/step - loss: -8.2633"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:20:17.259414: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:20:21.525578: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -7.7614 - val_loss: 10.4310\n",
+      "Epoch 63/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 185ms/step - loss: -11.2380"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:20:27.154908: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:20:31.546869: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -10.9594 - val_loss: -5.2369\n",
+      "Epoch 64/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 169ms/step - loss: -3.5057"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:20:36.591651: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:20:41.050668: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 1s/step - loss: -3.7862 - val_loss: -14.4639\n",
+      "Epoch 65/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 165ms/step - loss: -12.7207"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:20:46.076917: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:20:50.584033: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -12.2636 - val_loss: 4.0351\n",
+      "Epoch 66/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 191ms/step - loss: -7.0537"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:20:55.961130: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:21:00.569365: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -7.0030 - val_loss: 8.0344\n",
+      "Epoch 67/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 181ms/step - loss: -5.1857"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:21:05.971347: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:21:10.215353: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -5.1361 - val_loss: -8.5080\n",
+      "Epoch 68/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 177ms/step - loss: -12.0106"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:21:15.602083: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:21:20.166441: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -11.9782 - val_loss: -11.0411\n",
+      "Epoch 69/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 176ms/step - loss: -7.8373"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:21:25.564035: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:21:30.059666: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -8.0586 - val_loss: -9.2091\n",
+      "Epoch 70/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 184ms/step - loss: -11.6791"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:21:35.280580: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:21:39.752524: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -11.2324 - val_loss: -2.8709\n",
+      "Epoch 71/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 162ms/step - loss: -4.0821"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:21:45.192102: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:21:49.447517: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -3.9385 - val_loss: -13.9857\n",
+      "Epoch 72/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 160ms/step - loss: -2.8128"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:21:54.898102: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:21:59.246066: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -3.0204 - val_loss: -3.8005\n",
+      "Epoch 73/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 169ms/step - loss: -9.5274 "
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:22:04.780364: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:22:09.340923: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -9.0394 - val_loss: -7.1085\n",
+      "Epoch 74/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 173ms/step - loss: -6.9821"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:22:14.821417: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:22:19.212981: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -7.0190 - val_loss: -1.6739\n",
+      "Epoch 75/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 182ms/step - loss: -9.0720"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:22:24.822734: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:22:29.114348: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -8.9116 - val_loss: -2.5727\n",
+      "Epoch 76/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 178ms/step - loss: -10.2082"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:22:34.418572: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:22:38.819151: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -10.1673 - val_loss: 4.7921\n",
+      "Epoch 77/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 165ms/step - loss: -5.6090"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:22:44.469715: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:22:48.978073: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -5.7357 - val_loss: -18.5402\n",
+      "Epoch 78/100\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:22:49.640405: W tensorflow/core/kernels/data/prefetch_autotuner.cc:52] Prefetch autotuner tried to allocate 1451951 bytes after encountering the first element of size 1451951 bytes.This already causes the autotune ram budget to be exceeded. To stay within the ram budget, either increase the ram budget or reduce element size\n",
+      "2024-06-18 18:22:53.507894: W tensorflow/core/kernels/data/prefetch_autotuner.cc:52] Prefetch autotuner tried to allocate 983080 bytes after encountering the first element of size 983080 bytes.This already causes the autotune ram budget to be exceeded. To stay within the ram budget, either increase the ram budget or reduce element size\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 164ms/step - loss: -8.1490"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:22:54.394828: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:22:58.845164: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 1s/step - loss: -8.1786 - val_loss: -11.7750\n",
+      "Epoch 79/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 174ms/step - loss: -7.7636"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:23:05.465038: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:23:09.975123: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -7.3488 - val_loss: -9.3819\n",
+      "Epoch 80/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 179ms/step - loss: -10.5916"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:23:15.333863: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:23:19.782994: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -10.5031 - val_loss: -5.2485\n",
+      "Epoch 81/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 181ms/step - loss: -11.0255"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:23:25.179001: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:23:29.814211: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -10.8803 - val_loss: 3.1710\n",
+      "Epoch 82/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 181ms/step - loss: -8.5471"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:23:35.169310: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:23:39.666190: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 1s/step - loss: -8.3667 - val_loss: -6.5445\n",
+      "Epoch 83/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 186ms/step - loss: -10.8005"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:23:46.127786: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:23:50.619747: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -10.7375 - val_loss: -11.2866\n",
+      "Epoch 84/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 175ms/step - loss: -9.7341"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:23:56.021192: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:24:00.460076: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -9.6780 - val_loss: -5.7891\n",
+      "Epoch 85/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 169ms/step - loss: -11.5649"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:24:05.715343: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:24:09.982304: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -11.6615 - val_loss: -4.4442\n",
+      "Epoch 86/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 184ms/step - loss: -10.4848"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:24:15.563913: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:24:19.625686: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -10.6551 - val_loss: -13.1193\n",
+      "Epoch 87/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 176ms/step - loss: -7.7198"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:24:25.087241: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:24:29.518882: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -7.5616 - val_loss: -10.3428\n",
+      "Epoch 88/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 173ms/step - loss: -3.0326"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:24:34.653273: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:24:39.205736: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -3.2173 - val_loss: -13.3038\n",
+      "Epoch 89/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 169ms/step - loss: -6.3086"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:24:44.576247: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:24:49.111768: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -6.2965 - val_loss: -17.9752\n",
+      "Epoch 90/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 173ms/step - loss: -0.0039"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:24:54.384939: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:24:58.414585: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 995ms/step - loss: -0.4178 - val_loss: -2.1213\n",
+      "Epoch 91/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 191ms/step - loss: -10.4912"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:25:04.050425: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:25:08.480569: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -10.3589 - val_loss: -1.7054\n",
+      "Epoch 92/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 177ms/step - loss: -3.4555"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:25:13.884675: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:25:17.990408: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 1s/step - loss: -3.4892 - val_loss: -9.0304\n",
+      "Epoch 93/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 181ms/step - loss: -4.1257"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:25:24.751798: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:25:28.727905: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 992ms/step - loss: -4.1617 - val_loss: -7.7968\n",
+      "Epoch 94/100\n",
+      "\u001b[1m5/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━━━━\u001b[0m \u001b[1m0s\u001b[0m 187ms/step - loss: -11.3511"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:25:34.227648: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 191ms/step - loss: -10.8253"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:25:38.959239: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -10.4498 - val_loss: -1.1790\n",
+      "Epoch 95/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 166ms/step - loss: -7.8682"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:25:44.237631: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:25:48.569342: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -8.0303 - val_loss: 4.1570\n",
+      "Epoch 96/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 177ms/step - loss: -8.4884"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:25:54.045460: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:25:58.346658: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -8.9057 - val_loss: 8.2640\n",
+      "Epoch 97/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 188ms/step - loss: -10.6313"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:26:03.652742: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:26:08.057922: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -10.4899 - val_loss: -11.5326\n",
+      "Epoch 98/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 173ms/step - loss: -3.7386"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:26:13.437820: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:26:17.543765: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 1s/step - loss: -4.1425 - val_loss: -6.6096\n",
+      "Epoch 99/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 172ms/step - loss: -13.9096"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:26:23.060393: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:26:27.711043: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 1s/step - loss: -13.6365 - val_loss: -5.7103\n",
+      "Epoch 100/100\n",
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 172ms/step - loss: -11.7418"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 18:26:33.018851: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 18:26:37.132759: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m6/6\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 1s/step - loss: -11.8087 - val_loss: 0.4843\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7945e8dfad50>]"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "hh = model.fit(ds_train,\n",
+    "               validation_data=ds_val,\n",
+    "               epochs=100)\n",
+    "\n",
+    "plt.plot(hh.history['loss'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a7538a35",
+   "metadata": {},
+   "source": [
+    "### Supervised fine tuning\n",
+    "\n",
+    "From the trained SimCLR model, we extract the feature transformation part which includes the base encoder and the first two dense layers of the projection head. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "f31cbb32",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"SimCLR_feature\"</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1mModel: \"SimCLR_feature\"\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
+       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">       Param # </span>┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
+       "│ input_layer_2 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">InputLayer</span>)      │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">3</span>)      │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ resnet50 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Functional</span>)           │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">2048</span>)           │    <span style=\"color: #00af00; text-decoration-color: #00af00\">23,587,712</span> │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ functional_2 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Functional</span>)       │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)            │       <span style=\"color: #00af00; text-decoration-color: #00af00\">558,464</span> │\n",
+       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
+       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
+       "│ input_layer_2 (\u001b[38;5;33mInputLayer\u001b[0m)      │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m3\u001b[0m)      │             \u001b[38;5;34m0\u001b[0m │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ resnet50 (\u001b[38;5;33mFunctional\u001b[0m)           │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m2048\u001b[0m)           │    \u001b[38;5;34m23,587,712\u001b[0m │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ functional_2 (\u001b[38;5;33mFunctional\u001b[0m)       │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m)            │       \u001b[38;5;34m558,464\u001b[0m │\n",
+       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">24,146,176</span> (92.11 MB)\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m24,146,176\u001b[0m (92.11 MB)\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">557,952</span> (2.13 MB)\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m557,952\u001b[0m (2.13 MB)\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">23,588,224</span> (89.98 MB)\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m23,588,224\u001b[0m (89.98 MB)\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "x = layers.Input(input_shape)\n",
+    "\n",
+    "# same same\n",
+    "# _proj = models.Model(inputs=model._projector.inputs, outputs=model._projector.layers[3].output)\n",
+    "_proj = models.Model(inputs=model._projector.layers[0].input, outputs=model._projector.layers[3].output)\n",
+    "\n",
+    "# _proj.summary()  # shows a concrete value for batch\n",
+    "\n",
+    "f = _proj(model._encoder(x))\n",
+    "\n",
+    "model_feature = models.Model(inputs=x, outputs=f, name='SimCLR_feature')\n",
+    "\n",
+    "model_feature.summary()  # shows `None` for batch"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "761c1a04-c645-4a0b-bedd-9c688ad93858",
+   "metadata": {},
+   "source": [
+    "#### Classfication head and fine tuning\n",
+    "\n",
+    "We add a classification head to the feature transformation network and fine tune the model on some new data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "id": "97e371aa-757d-4869-b594-3086072423aa",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "window = transformer.WindowSlider(extractor.dataset, window_size=(64,64), hop_size=(64,64))\n",
+    "# fp = tempfile.mkdtemp()\n",
+    "# window.serialize(str(workdir), compression='GZIP')\n",
+    "# window.dataset = tf.data.Dataset.load(str(workdir), compression='GZIP')\n",
+    "\n",
+    "preproc = preprocessing.get_mapping_supervised(labels)\n",
+    "\n",
+    "splits = {'train':0.7, 'val':0.2, 'test':0.1}\n",
+    "batch_size = 64\n",
+    "\n",
+    "n_classes = len(labels) + 1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "id": "2a51544e-5985-43e5-b7ec-6889a36a4d72",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:47:36.336503: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 22:47:36.628718: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 22:47:36.877716: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 22:47:39.408311: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 22:47:39.412625: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    }
+   ],
+   "source": [
+    "dw = utils.restore_shape(\n",
+    "    window.dataset.map(preproc, num_parallel_calls=tf.data.AUTOTUNE),\n",
+    "    key=0\n",
+    ")\n",
+    "\n",
+    "dw_split = utils.split_dataset(\n",
+    "    dw, splits, \n",
+    "    # ds_size=dw_size, \n",
+    "    # labels=np.arange(n_classes)\n",
+    ")\n",
+    "\n",
+    "dw_train = dw_split['train']\\\n",
+    "    .shuffle(dw_size, reshuffle_each_iteration=True)\\\n",
+    "    .repeat()\\\n",
+    "    .batch(batch_size, drop_remainder=True)\\\n",
+    "    .prefetch(tf.data.AUTOTUNE)\n",
+    "dw_val = dw_split['val'].repeat().batch(batch_size, drop_remainder=True)\n",
+    "dw_test = dw_split['test'].batch(batch_size, drop_remainder=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6a28bca4-051a-48ab-8781-884798e9ea8b",
+   "metadata": {},
+   "source": [
+    "The classification head here is a simple MLP. The weights of the feature transformation network are frozen for the training."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "99f13cd1-5223-4bc8-bdbd-51bc28227657",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model_feature.trainable = False\n",
+    "\n",
+    "class_head = models.Sequential([\n",
+    "    layers.Dense(128, activation='relu'),\n",
+    "    layers.BatchNormalization(),\n",
+    "    layers.Dense(n_classes) # nb labels\n",
+    "], name='Classification_head')\n",
+    "\n",
+    "x = layers.Input(input_shape)\n",
+    "\n",
+    "model_fine = models.Model(inputs=x, outputs=class_head(model_feature(x)))\n",
+    "\n",
+    "model_fine.compile(\n",
+    "    optimizer=keras.optimizers.Adam(),\n",
+    "    loss=losses.SparseCategoricalCrossentropy(from_logits=True),\n",
+    "    metrics=[metrics.SparseCategoricalAccuracy()]\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "03fca33b",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Epoch 1/10\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:00:06.579722: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 22:00:11.752229: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m177/178\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 289ms/step - loss: 0.7895 - sparse_categorical_accuracy: 0.7663"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:01:04.898604: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m178/178\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 289ms/step - loss: 0.7893 - sparse_categorical_accuracy: 0.7664"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:01:10.211262: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 22:01:26.443051: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m178/178\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m80s\u001b[0m 411ms/step - loss: 0.7891 - sparse_categorical_accuracy: 0.7665 - val_loss: 0.6880 - val_sparse_categorical_accuracy: 0.8022\n",
+      "Epoch 2/10\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:01:31.782949: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m177/178\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 283ms/step - loss: 0.6119 - sparse_categorical_accuracy: 0.8167"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:02:23.311512: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m178/178\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 283ms/step - loss: 0.6118 - sparse_categorical_accuracy: 0.8167"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:02:28.831251: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 22:02:42.860830: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m178/178\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m76s\u001b[0m 393ms/step - loss: 0.6117 - sparse_categorical_accuracy: 0.8167 - val_loss: 0.5011 - val_sparse_categorical_accuracy: 0.8472\n",
+      "Epoch 3/10\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:02:48.256063: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m177/178\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 286ms/step - loss: 0.5107 - sparse_categorical_accuracy: 0.8469"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:03:38.858683: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m178/178\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 286ms/step - loss: 0.5106 - sparse_categorical_accuracy: 0.8469"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:03:44.278436: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 22:03:58.220246: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m178/178\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m75s\u001b[0m 395ms/step - loss: 0.5105 - sparse_categorical_accuracy: 0.8469 - val_loss: 0.4407 - val_sparse_categorical_accuracy: 0.8697\n",
+      "Epoch 4/10\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:04:03.645383: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m177/178\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 290ms/step - loss: 0.4333 - sparse_categorical_accuracy: 0.8713"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:04:54.939011: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m178/178\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 290ms/step - loss: 0.4332 - sparse_categorical_accuracy: 0.8713"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:05:00.209964: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 22:05:14.250770: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m178/178\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m76s\u001b[0m 399ms/step - loss: 0.4332 - sparse_categorical_accuracy: 0.8713 - val_loss: 0.3545 - val_sparse_categorical_accuracy: 0.8975\n",
+      "Epoch 5/10\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:05:19.887105: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m177/178\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 288ms/step - loss: 0.3763 - sparse_categorical_accuracy: 0.8860"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:06:10.820527: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m178/178\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 288ms/step - loss: 0.3763 - sparse_categorical_accuracy: 0.8860"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:06:16.215612: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 22:06:30.071623: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m178/178\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m76s\u001b[0m 396ms/step - loss: 0.3763 - sparse_categorical_accuracy: 0.8860 - val_loss: 0.3364 - val_sparse_categorical_accuracy: 0.8981\n",
+      "Epoch 6/10\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:06:35.394778: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m177/178\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 280ms/step - loss: 0.3353 - sparse_categorical_accuracy: 0.8956"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:07:24.933594: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m178/178\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 280ms/step - loss: 0.3353 - sparse_categorical_accuracy: 0.8956"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:07:30.216677: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 22:07:44.233583: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m178/178\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m74s\u001b[0m 389ms/step - loss: 0.3353 - sparse_categorical_accuracy: 0.8956 - val_loss: 0.2944 - val_sparse_categorical_accuracy: 0.9084\n",
+      "Epoch 7/10\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:07:49.831970: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m177/178\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 280ms/step - loss: 0.3064 - sparse_categorical_accuracy: 0.9076"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:08:39.477198: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m178/178\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 280ms/step - loss: 0.3064 - sparse_categorical_accuracy: 0.9076"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:08:44.893281: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 22:08:58.465833: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m178/178\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m74s\u001b[0m 388ms/step - loss: 0.3064 - sparse_categorical_accuracy: 0.9075 - val_loss: 0.2573 - val_sparse_categorical_accuracy: 0.9259\n",
+      "Epoch 8/10\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:09:03.781418: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m177/178\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 287ms/step - loss: 0.2883 - sparse_categorical_accuracy: 0.9109"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:09:54.531223: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m178/178\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 287ms/step - loss: 0.2883 - sparse_categorical_accuracy: 0.9109"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:09:59.893396: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 22:10:13.792376: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m178/178\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m75s\u001b[0m 396ms/step - loss: 0.2882 - sparse_categorical_accuracy: 0.9109 - val_loss: 0.2298 - val_sparse_categorical_accuracy: 0.9325\n",
+      "Epoch 9/10\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:10:19.185287: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m177/178\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 289ms/step - loss: 0.2675 - sparse_categorical_accuracy: 0.9155"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:11:10.295008: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m178/178\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 289ms/step - loss: 0.2675 - sparse_categorical_accuracy: 0.9155"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:11:15.686673: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 22:11:29.460408: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m178/178\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m76s\u001b[0m 397ms/step - loss: 0.2675 - sparse_categorical_accuracy: 0.9155 - val_loss: 0.2244 - val_sparse_categorical_accuracy: 0.9328\n",
+      "Epoch 10/10\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:11:34.743218: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m177/178\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 296ms/step - loss: 0.2310 - sparse_categorical_accuracy: 0.9280"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:12:27.161809: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m178/178\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 297ms/step - loss: 0.2310 - sparse_categorical_accuracy: 0.9280"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:12:33.604451: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 22:12:48.229442: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m178/178\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m79s\u001b[0m 416ms/step - loss: 0.2310 - sparse_categorical_accuracy: 0.9280 - val_loss: 0.2063 - val_sparse_categorical_accuracy: 0.9413\n"
      ]
     }
    ],
    "source": [
-    "hh = model.fit(ds_train,\n",
-    "               validation_data=ds_val,\n",
-    "               epochs=1)"
+    "hh = model_fine.fit(\n",
+    "    dw_train,\n",
+    "    validation_data=dw_val,\n",
+    "    epochs=10\n",
+    ")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
-   "id": "11a1e743",
+   "execution_count": 28,
+   "id": "2cabf96a-e1b5-4f89-8803-f3e5828f8127",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:14:38.280661: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m24/25\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m━\u001b[0m \u001b[1m0s\u001b[0m 283ms/step - loss: 0.2115 - sparse_categorical_accuracy: 0.9405"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 22:14:45.099446: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m25/25\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 284ms/step - loss: 0.2106 - sparse_categorical_accuracy: 0.9409\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[0.19973041117191315, 0.9449999928474426]"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model_fine.evaluate(dw_test)"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "id": "43cb9215-3271-4fbc-8cb7-d811eb46fa44",
+   "metadata": {},
+   "source": [
+    "### Few-shot learning\n",
+    "\n",
+    "In few-shot learning the number of new data per category is limited. We can prepare the data for few-shot learning by splitting separately data of each category.\n",
+    "\n",
+    "However for unknown reasons, the performance of the few-shot split seems to be very low compared to the normal split."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "id": "3a9f0179-ccaf-4911-8b8b-4077386e6915",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "window = transformer.WindowSlider(\n",
+    "    extractor.dataset, \n",
+    "    window_size=(64,64), \n",
+    "    hop_size=(64, 64)\n",
+    "    # hop_size=(32, 32)\n",
+    ")\n",
+    "\n",
+    "preproc = preprocessing.get_mapping_supervised(labels)\n",
+    "\n",
+    "splits = {'train':0.2, 'val':0.7, 'test':0.1}\n",
+    "batch_size = 64\n",
+    "\n",
+    "n_classes = len(labels) + 1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e6c55de6-16ec-4731-b429-f2ec93ee7946",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "# Only for demonstration, here we apply the preprocessing after the split.\n",
+    "dw_split = utils.split_dataset(\n",
+    "    dw, splits, \n",
+    "    labels=labels\n",
+    ")\n",
+    "\n",
+    "dw_train = dw_split['train']\\\n",
+    "    .map(preproc, num_parallel_calls=tf.data.AUTOTUNE)\\\n",
+    "    .shuffle(dw_size, reshuffle_each_iteration=True)\\\n",
+    "    .repeat()\\\n",
+    "    .batch(batch_size, drop_remainder=True)\\\n",
+    "    .prefetch(tf.data.AUTOTUNE)\n",
+    "dw_val = dw_split['val']\\\n",
+    "    .map(preproc, num_parallel_calls=tf.data.AUTOTUNE)\\\n",
+    "    .repeat()\\\n",
+    "    .batch(batch_size, drop_remainder=True)\n",
+    "dw_test = dw_split['test']\\\n",
+    "    .map(preproc, num_parallel_calls=tf.data.AUTOTUNE)\\\n",
+    "    .batch(batch_size, drop_remainder=True)\n",
+    "\n",
+    "# for k, dv in dw_split.items():\n",
+    "#     dv.save(str(workdir/f'fs_split_{k}'))\n",
+    "\n",
+    "# %time eles = list(dw_train.take(10))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 85,
+   "id": "09665753-31d0-46bc-b4dd-62ea791ca6d8",
    "metadata": {},
+   "outputs": [],
+   "source": [
+    "model_feature.trainable = False\n",
+    "\n",
+    "class_head = models.Sequential([\n",
+    "    layers.Dense(128, activation='relu'),\n",
+    "    layers.BatchNormalization(),\n",
+    "    layers.Dense(n_classes) # nb labels\n",
+    "], name='Classification_head')\n",
+    "\n",
+    "x = layers.Input(input_shape)\n",
+    "\n",
+    "model_fs = models.Model(inputs=x, outputs=class_head(model_feature(x)))\n",
+    "\n",
+    "model_fs.compile(\n",
+    "    optimizer=keras.optimizers.Adam(),\n",
+    "    loss=losses.SparseCategoricalCrossentropy(from_logits=True),\n",
+    "    metrics=[metrics.SparseCategoricalAccuracy()]\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3990ecfe-8645-4cc1-9d2c-b926ae95d899",
+   "metadata": {
+    "scrolled": true
+   },
    "outputs": [
     {
-     "data": {
-      "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x717dc2b5f7d0>]"
-      ]
-     },
-     "execution_count": 16,
-     "metadata": {},
-     "output_type": "execute_result"
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 23:23:06.103741: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:23:07.827731: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:23:09.564491: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:23:11.245902: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:23:12.950104: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:23:14.649688: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:23:16.366624: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:23:18.137140: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:23:19.885219: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:23:21.612479: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:23:23.307689: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:23:25.043767: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:23:26.843528: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:23:28.611822: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:23:30.309525: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:23:32.002211: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:23:33.719745: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:23:35.441658: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:23:37.168086: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:23:38.852251: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:23:40.570698: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:23:42.317625: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:23:44.030740: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:23:45.730524: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:23:47.449266: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:23:49.131988: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:23:50.838340: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:23:52.562252: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:23:54.298426: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:23:55.965667: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:23:57.647358: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:23:59.307964: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:00.999442: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:02.650621: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:04.322892: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:05.980810: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:07.717436: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:09.486661: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:11.259600: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:12.999867: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:14.767534: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:16.496924: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:18.186992: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:19.977258: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:21.811704: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:23.567733: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:25.400293: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:27.230247: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:29.074321: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:30.933470: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:32.722520: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:34.518937: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:36.286001: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:38.038895: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:39.821817: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:41.641524: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:43.484992: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:45.306583: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:47.095063: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:48.902087: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:50.671171: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:52.453699: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:54.156440: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:55.921094: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:57.692652: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:24:59.463394: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:25:01.240765: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:25:03.033429: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:25:04.845368: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:25:06.637660: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:25:08.409125: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:25:10.138350: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:25:11.947371: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:25:13.714282: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:25:15.482270: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:25:17.218127: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:25:19.041704: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:25:20.845979: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:25:22.673368: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:25:24.473637: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:25:26.290840: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:25:28.085072: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:25:29.877714: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:25:31.646223: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:25:33.443290: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:25:35.186182: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:25:37.000768: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:25:38.774106: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:25:40.622494: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:25:42.435414: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Epoch 1/10\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 23:25:46.157614: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:25:47.963331: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:25:49.685787: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:25:51.492916: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:25:53.275559: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:25:55.096678: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:25:56.930823: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:25:58.711536: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:00.533134: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:02.300554: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:04.075202: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:05.913936: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:07.673723: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:09.438143: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:11.158062: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:12.927152: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:14.695258: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:16.535813: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:18.365019: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:20.138631: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:21.948105: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:23.741749: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:25.548821: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:27.284696: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:29.050935: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:30.784518: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:32.548780: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:34.301707: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:36.133125: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:37.972033: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:39.780177: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:41.635296: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:43.454539: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:45.239582: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:46.982364: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:48.702155: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:50.477847: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:52.243839: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:54.001059: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:55.818317: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:57.606092: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:26:59.413103: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:01.204325: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:03.023947: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:04.820626: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:06.562579: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:08.295364: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:10.049181: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:11.778106: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:13.537349: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:15.260494: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:17.080953: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:18.903314: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:20.698711: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:22.499205: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:24.205853: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:25.969236: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:27.717653: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:29.480768: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:31.290222: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:33.003687: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:34.810940: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:36.606363: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:38.401294: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:40.161804: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:41.988917: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:43.709946: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:45.435590: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:47.179635: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:48.971525: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:50.770053: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:52.581240: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:54.330435: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:56.090478: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:57.921747: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:27:59.698909: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:28:01.478007: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:28:03.213041: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:28:05.009518: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:28:06.702401: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:28:08.517675: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:28:10.256925: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:28:12.033947: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:28:13.850676: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:28:15.677459: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:28:17.492148: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:28:19.288519: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:28:21.047944: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:28:22.744138: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:28:24.519089: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:28:26.855945: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "      1/Unknown \u001b[1m164s\u001b[0m 164s/step - loss: 3.6698 - sparse_categorical_accuracy: 0.0469"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 23:28:29.140194: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "     13/Unknown \u001b[1m170s\u001b[0m 450ms/step - loss: 3.5559 - sparse_categorical_accuracy: 0.1009"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 23:28:35.734082: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:28:37.540186: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:28:39.366867: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:28:41.228232: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:28:43.005185: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:28:44.800442: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:28:46.535460: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:28:48.311158: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:28:50.109661: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:28:51.885442: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:28:53.717452: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:28:55.565130: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:28:57.348146: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:28:59.139456: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:29:00.886663: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:29:02.699393: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:29:04.457400: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:29:06.234748: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:29:08.095144: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:29:09.948051: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:29:11.729428: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:29:13.536867: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:29:15.360389: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:29:17.228484: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:29:18.977109: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:29:20.748760: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:29:22.490806: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "     14/Unknown \u001b[1m220s\u001b[0m 4s/step - loss: 3.5343 - sparse_categorical_accuracy: 0.1037   "
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 23:29:24.341290: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "     25/Unknown \u001b[1m224s\u001b[0m 2s/step - loss: 3.3143 - sparse_categorical_accuracy: 0.1385"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 23:29:28.318926: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "     27/Unknown \u001b[1m225s\u001b[0m 2s/step - loss: 3.2802 - sparse_categorical_accuracy: 0.1448"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 23:29:30.713864: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:29:32.590755: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:29:34.394043: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:29:36.164223: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:29:37.955632: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:29:39.678792: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:29:41.472587: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:29:43.250059: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:29:44.970787: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:29:46.773968: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:29:48.539108: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:29:50.320423: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:29:52.172764: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:29:54.000556: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:29:55.760869: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:29:57.510812: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:29:59.252164: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:30:01.028320: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:30:02.837602: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:30:04.567631: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:30:06.403469: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:30:08.182741: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:30:10.039884: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:30:11.814114: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:30:13.660867: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:30:15.426493: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:30:17.204842: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
     },
     {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "plt.plot(hh.history['loss'])"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "a7538a35",
-   "metadata": {},
-   "source": [
-    "### Supervised fine tuning\n",
-    "\n",
-    "From the trained SimCLR model, we extract the feature transformation part which includes the base encoder and the first two dense layers of the projection head. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "id": "f31cbb32",
-   "metadata": {},
-   "outputs": [
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "     28/Unknown \u001b[1m275s\u001b[0m 4s/step - loss: 3.2636 - sparse_categorical_accuracy: 0.1479"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 23:30:19.056516: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "     38/Unknown \u001b[1m279s\u001b[0m 3s/step - loss: 3.1141 - sparse_categorical_accuracy: 0.1782"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 23:30:22.949411: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "     42/Unknown \u001b[1m280s\u001b[0m 3s/step - loss: 3.0625 - sparse_categorical_accuracy: 0.1896"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 23:30:25.464385: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:30:27.272470: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:30:29.098173: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:30:30.885274: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:30:32.718210: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:30:34.459672: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:30:36.220766: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:30:37.995363: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:30:39.799118: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:30:41.641905: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:30:43.447573: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:30:45.217630: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:30:47.051946: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:30:48.849045: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:30:50.728469: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:30:52.584746: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:30:54.359077: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:30:56.104063: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:30:57.912116: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:30:59.654088: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:31:01.474646: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:31:03.261670: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:31:05.089664: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:31:06.876683: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:31:08.666626: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:31:10.448881: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:31:12.164491: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "     43/Unknown \u001b[1m330s\u001b[0m 4s/step - loss: 3.0502 - sparse_categorical_accuracy: 0.1923"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 23:31:14.059501: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "     53/Unknown \u001b[1m334s\u001b[0m 3s/step - loss: 2.9364 - sparse_categorical_accuracy: 0.2182"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 23:31:17.905860: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "     56/Unknown \u001b[1m335s\u001b[0m 3s/step - loss: 2.9054 - sparse_categorical_accuracy: 0.2253"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 23:31:20.340692: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:31:22.095680: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:31:23.897417: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:31:25.652347: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:31:27.466535: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:31:29.292829: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:31:31.059020: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:31:32.820237: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:31:34.540469: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:31:36.319639: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:31:38.097280: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:31:39.918383: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:31:41.710031: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:31:43.529997: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:31:45.328830: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:31:47.139890: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:31:49.006329: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:31:50.745064: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:31:52.525572: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:31:54.281308: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:31:56.053659: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:31:57.862500: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:31:59.672192: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:32:01.450752: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:32:03.242564: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:32:05.062552: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:32:06.878836: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "     57/Unknown \u001b[1m385s\u001b[0m 4s/step - loss: 2.8954 - sparse_categorical_accuracy: 0.2276"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 23:32:08.777503: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "     67/Unknown \u001b[1m388s\u001b[0m 3s/step - loss: 2.8024 - sparse_categorical_accuracy: 0.2493"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 23:32:12.666032: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "     70/Unknown \u001b[1m389s\u001b[0m 3s/step - loss: 2.7769 - sparse_categorical_accuracy: 0.2553"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 23:32:14.973569: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:32:16.760207: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:32:18.610025: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:32:20.395882: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:32:22.174041: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:32:23.947582: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:32:25.763487: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:32:27.611817: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:32:29.381233: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:32:31.141490: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:32:32.891621: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:32:34.661401: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:32:36.417231: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:32:38.179761: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:32:40.023338: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:32:41.795596: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:32:43.589435: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:32:45.376559: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:32:47.201403: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:32:48.937024: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:32:50.716575: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:32:52.491592: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:32:54.240780: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:32:55.969779: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:32:57.767578: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:32:59.580562: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:33:01.317178: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "     71/Unknown \u001b[1m439s\u001b[0m 4s/step - loss: 2.7686 - sparse_categorical_accuracy: 0.2573"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 23:33:03.272835: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "     81/Unknown \u001b[1m443s\u001b[0m 3s/step - loss: 2.6913 - sparse_categorical_accuracy: 0.2759"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 23:33:07.130620: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "     85/Unknown \u001b[1m444s\u001b[0m 3s/step - loss: 2.6628 - sparse_categorical_accuracy: 0.2828"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 23:33:10.299495: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:33:12.092627: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:33:13.895207: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:33:15.661536: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:33:17.471843: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:33:19.243781: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:33:21.072572: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:33:22.909083: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:33:24.727922: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:33:26.462189: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:33:28.184609: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:33:29.948991: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:33:31.689803: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:33:33.514066: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:33:35.343483: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:33:37.144435: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:33:38.961611: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:33:40.818208: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:33:42.636297: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:33:44.472266: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:33:46.211898: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:33:48.026157: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:33:49.774125: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:33:51.607747: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:33:53.382444: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:33:55.237506: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:33:57.017996: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "     86/Unknown \u001b[1m495s\u001b[0m 4s/step - loss: 2.6559 - sparse_categorical_accuracy: 0.2845"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 23:33:58.968315: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "     96/Unknown \u001b[1m499s\u001b[0m 4s/step - loss: 2.5907 - sparse_categorical_accuracy: 0.3004"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 23:34:02.994645: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "     99/Unknown \u001b[1m500s\u001b[0m 3s/step - loss: 2.5725 - sparse_categorical_accuracy: 0.3049"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 23:34:05.267974: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:34:07.045847: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:34:08.830138: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:34:10.642336: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:34:12.430492: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:34:14.164157: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:34:15.989011: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:34:17.814001: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:34:19.664556: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:34:21.501377: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:34:23.275528: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:34:25.068820: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:34:26.829156: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:34:28.545056: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:34:30.294662: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:34:32.064495: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:34:33.895421: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:34:35.719822: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:34:37.564802: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:34:39.379529: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:34:41.215825: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:34:42.943529: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:34:44.693367: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:34:46.444481: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:34:48.209709: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:34:49.998225: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:34:51.740424: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "    100/Unknown \u001b[1m549s\u001b[0m 4s/step - loss: 2.5665 - sparse_categorical_accuracy: 0.3064"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 23:34:53.673774: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "    110/Unknown \u001b[1m553s\u001b[0m 4s/step - loss: 2.5091 - sparse_categorical_accuracy: 0.3208"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 23:34:57.656442: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "    114/Unknown \u001b[1m555s\u001b[0m 3s/step - loss: 2.4874 - sparse_categorical_accuracy: 0.3263"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 23:35:00.205278: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:35:01.932100: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:35:03.688239: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:35:05.449312: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:35:07.203362: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:35:08.965019: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:35:10.713952: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:35:12.491283: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:35:14.286320: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:35:16.079008: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:35:17.917383: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:35:19.667893: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:35:21.457596: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:35:23.216910: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:35:25.004337: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:35:26.793726: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:35:28.600367: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:35:30.355146: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:35:32.111792: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:35:33.979910: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:35:35.779325: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:35:37.628620: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:35:39.462963: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:35:41.202371: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:35:42.955568: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:35:44.702552: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:35:46.432608: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "    115/Unknown \u001b[1m604s\u001b[0m 4s/step - loss: 2.4821 - sparse_categorical_accuracy: 0.3276"
+     ]
+    },
     {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"SimCLR_feature\"</span>\n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[1mModel: \"SimCLR_feature\"\u001b[0m\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 23:35:48.333975: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
     },
     {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
-       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">       Param # </span>┃\n",
-       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
-       "│ input_layer_2 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">InputLayer</span>)      │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">3</span>)      │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
-       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
-       "│ resnet50 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Functional</span>)           │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">2048</span>)           │    <span style=\"color: #00af00; text-decoration-color: #00af00\">23,587,712</span> │\n",
-       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
-       "│ functional_2 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Functional</span>)       │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)            │       <span style=\"color: #00af00; text-decoration-color: #00af00\">558,464</span> │\n",
-       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
-       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
-       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
-       "│ input_layer_2 (\u001b[38;5;33mInputLayer\u001b[0m)      │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m64\u001b[0m, \u001b[38;5;34m3\u001b[0m)      │             \u001b[38;5;34m0\u001b[0m │\n",
-       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
-       "│ resnet50 (\u001b[38;5;33mFunctional\u001b[0m)           │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m2048\u001b[0m)           │    \u001b[38;5;34m23,587,712\u001b[0m │\n",
-       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
-       "│ functional_2 (\u001b[38;5;33mFunctional\u001b[0m)       │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m)            │       \u001b[38;5;34m558,464\u001b[0m │\n",
-       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "    125/Unknown \u001b[1m608s\u001b[0m 4s/step - loss: 2.4309 - sparse_categorical_accuracy: 0.3407"
+     ]
     },
     {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">24,146,176</span> (92.11 MB)\n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m24,146,176\u001b[0m (92.11 MB)\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 23:35:52.146777: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
     },
     {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">557,952</span> (2.13 MB)\n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m557,952\u001b[0m (2.13 MB)\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "    128/Unknown \u001b[1m609s\u001b[0m 4s/step - loss: 2.4162 - sparse_categorical_accuracy: 0.3445"
+     ]
     },
     {
-     "data": {
-      "text/html": [
-       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">23,588,224</span> (89.98 MB)\n",
-       "</pre>\n"
-      ],
-      "text/plain": [
-       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m23,588,224\u001b[0m (89.98 MB)\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "x = layers.Input(input_shape)\n",
-    "\n",
-    "# same same\n",
-    "# _proj = models.Model(inputs=model._projector.inputs, outputs=model._projector.layers[3].output)\n",
-    "_proj = models.Model(inputs=model._projector.layers[0].input, outputs=model._projector.layers[3].output)\n",
-    "\n",
-    "# _proj.summary()  # shows a concrete value for batch\n",
-    "\n",
-    "f = _proj(model._encoder(x))\n",
-    "\n",
-    "model_feature = models.Model(inputs=x, outputs=f, name='SimCLR_feature')\n",
-    "\n",
-    "model_feature.summary()  # shows `None` for batch"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "523390dc",
-   "metadata": {},
-   "source": [
-    "Test the feature transformation model to see how it acts across the batch."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "id": "1546bef6",
-   "metadata": {},
-   "outputs": [
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 23:35:54.601516: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:35:56.444906: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:35:58.236827: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:36:00.011922: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:36:01.781544: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:36:03.562944: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:36:05.317447: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:36:07.079106: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:36:08.823955: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:36:10.633755: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:36:12.412399: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:36:14.210073: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:36:16.072407: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:36:17.823396: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:36:19.613157: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:36:21.381903: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:36:23.194126: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:36:24.993245: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:36:26.770034: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:36:28.573555: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:36:30.334200: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:36:32.069745: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:36:33.897030: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:36:35.734084: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:36:37.449792: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:36:39.193012: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:36:41.011441: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "    129/Unknown \u001b[1m659s\u001b[0m 4s/step - loss: 2.4114 - sparse_categorical_accuracy: 0.3457"
+     ]
+    },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2024-06-18 12:52:30.855289: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+      "2024-06-18 23:36:42.894608: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 2s/step\n",
-      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 2s/step\n"
+      "    139/Unknown \u001b[1m663s\u001b[0m 4s/step - loss: 2.3650 - sparse_categorical_accuracy: 0.3577"
      ]
     },
     {
-     "data": {
-      "text/plain": [
-       "array([[ 0.0000000e+00,  0.0000000e+00,  0.0000000e+00,  0.0000000e+00,\n",
-       "         0.0000000e+00,  0.0000000e+00,  1.7881393e-06,  0.0000000e+00,\n",
-       "         0.0000000e+00,  0.0000000e+00, -1.1920929e-06, -1.0132790e-06,\n",
-       "         0.0000000e+00, -2.3841858e-07,  4.1769817e-07,  0.0000000e+00,\n",
-       "         0.0000000e+00,  2.3841858e-07, -8.9406967e-07, -1.1920929e-07,\n",
-       "         5.3644180e-07,  0.0000000e+00,  0.0000000e+00,  0.0000000e+00,\n",
-       "         0.0000000e+00,  0.0000000e+00,  4.7683716e-07,  0.0000000e+00,\n",
-       "        -4.7683716e-07,  1.7881393e-07, -2.3841858e-07,  0.0000000e+00,\n",
-       "         2.3841858e-07, -8.3446503e-07, -1.1920929e-07,  0.0000000e+00,\n",
-       "         4.7683716e-07, -3.5762787e-07,  0.0000000e+00,  0.0000000e+00,\n",
-       "         0.0000000e+00, -7.1525574e-07,  0.0000000e+00,  3.5762787e-07,\n",
-       "         0.0000000e+00,  0.0000000e+00,  0.0000000e+00, -1.1920929e-06,\n",
-       "        -1.1920929e-06,  3.5762787e-07,  1.2293458e-06,  0.0000000e+00,\n",
-       "         0.0000000e+00,  0.0000000e+00,  0.0000000e+00, -1.2516975e-06,\n",
-       "        -1.6689301e-06,  2.3841858e-07,  0.0000000e+00, -2.5033951e-06,\n",
-       "         0.0000000e+00, -3.5762787e-07,  1.4305115e-06,  0.0000000e+00,\n",
-       "         0.0000000e+00,  0.0000000e+00,  7.1525574e-07,  5.3644180e-07,\n",
-       "        -1.3113022e-06,  0.0000000e+00,  0.0000000e+00,  5.9604645e-07,\n",
-       "        -8.3446503e-07, -7.1525574e-07,  3.2410026e-07,  0.0000000e+00,\n",
-       "         0.0000000e+00,  0.0000000e+00,  3.7439167e-07,  0.0000000e+00,\n",
-       "        -5.9604645e-07,  2.4437904e-06,  0.0000000e+00,  0.0000000e+00,\n",
-       "         0.0000000e+00,  0.0000000e+00, -1.0728836e-06,  0.0000000e+00,\n",
-       "         0.0000000e+00, -1.6391277e-07, -1.0728836e-06,  5.0663948e-07,\n",
-       "         0.0000000e+00,  0.0000000e+00,  0.0000000e+00, -1.6093254e-06,\n",
-       "        -7.1525574e-07,  0.0000000e+00,  0.0000000e+00, -8.3446503e-07,\n",
-       "         0.0000000e+00,  0.0000000e+00,  0.0000000e+00,  0.0000000e+00,\n",
-       "         0.0000000e+00,  1.4305115e-06,  0.0000000e+00,  0.0000000e+00,\n",
-       "        -1.7881393e-06,  0.0000000e+00, -7.1525574e-07,  7.1525574e-07,\n",
-       "         0.0000000e+00, -3.5762787e-07,  7.1525574e-07,  0.0000000e+00,\n",
-       "        -5.9604645e-07,  0.0000000e+00,  1.9073486e-06,  1.6093254e-06,\n",
-       "         0.0000000e+00, -1.6689301e-06,  0.0000000e+00,  0.0000000e+00,\n",
-       "         0.0000000e+00,  0.0000000e+00,  0.0000000e+00,  0.0000000e+00]],\n",
-       "      dtype=float32)"
-      ]
-     },
-     "execution_count": 18,
-     "metadata": {},
-     "output_type": "execute_result"
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 23:36:46.988963: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "    142/Unknown \u001b[1m664s\u001b[0m 4s/step - loss: 2.3517 - sparse_categorical_accuracy: 0.3612"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-06-18 23:36:49.336961: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:36:51.169367: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:36:52.996509: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:36:54.803502: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:36:56.628022: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
+      "2024-06-18 23:36:58.387585: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+     ]
     }
    ],
    "source": [
-    "# eles = list(ds_train.take(1))[0]\n",
-    "eles = list(ds_train.take(1).as_numpy_iterator())[0]\n",
-    "\n",
-    "xx = ops.take(eles[0][0], [2], axis=0)\n",
-    "yy = model_feature.predict(xx)  # apply on a single input\n",
-    "zz = model_feature.predict(eles[0][0])[2]  # apply on a batch of inputs then take the corresponding output\n",
-    "\n",
-    "# yy = model._encoder.predict(xx)\n",
-    "# zz = model._encoder.predict(eles[0][0])[2]\n",
-    "\n",
-    "# Comparison: NOT zero.\n",
-    "yy-zz"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "1a654d92",
-   "metadata": {},
-   "source": [
-    "#### Classfication head and fine tuning\n",
-    "\n",
-    "We add a classification head to the feature transformation network and fine tune the model on some new data.\n",
-    "\n",
-    "Let's first prepare new data of few-shot learning style. This consists in splitting separately each category (i.e. a label) of data."
+    "hh = model_fs.fit(\n",
+    "    dw_train,\n",
+    "    validation_data=dw_val,\n",
+    "    epochs=10\n",
+    ")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
-   "id": "e5431a18",
+   "execution_count": null,
+   "id": "6b1029de-e257-4da5-a740-4e701503930f",
    "metadata": {},
    "outputs": [],
    "source": [
-    "slider = transformer.WindowSlider(extractor.dataset, window_size=(64,64), hop_size=(64,64))\n",
-    "# fp = tempfile.mkdtemp()\n",
-    "# slider.serialize(str(workdir), compression='GZIP')\n",
-    "# slider.dataset = tf.data.Dataset.load(str(workdir), compression='GZIP')\n",
-    "\n",
-    "preproc = preprocessing.get_mapping_supervised(labels)\n",
-    "\n",
-    "splits = {'train':0.7, 'val':0.2, 'test':0.1}\n",
-    "batch_size = 64\n",
-    "\n",
-    "n_classes = len(labels) + 1"
+    "model_fs.evaluate(dw_test)"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "88aad085",
-   "metadata": {},
-   "source": [
-    "Two equivalent ways of doing this: split before preprocess or preprocess before split."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 45,
-   "id": "a76b48fc",
+   "id": "2d550c67-ba48-466a-af89-93af0ca699ba",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "2024-06-18 13:49:16.274706: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
-      "2024-06-18 13:49:16.277779: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
-     ]
-    }
-   ],
    "source": [
-    "# Way 1: split first\n",
-    "\n",
-    "dw = utils.restore_cardinality(\n",
-    "    slider.dataset\n",
-    ")\n",
-    "\n",
-    "dw_split = utils.split_dataset(dw, splits, ds_size=int(dw.cardinality()), labels=labels)\n",
-    "\n",
-    "dw_train = dw_split['train']\\\n",
-    "    .map(preproc, num_parallel_calls=tf.data.AUTOTUNE)\\\n",
-    "    .shuffle(ds_size, reshuffle_each_iteration=True)\\\n",
-    "    .batch(batch_size, drop_remainder=True)\\\n",
-    "    .prefetch(tf.data.AUTOTUNE)\n",
-    "dw_val = dw_split['val']\\\n",
-    "    .map(preproc, num_parallel_calls=tf.data.AUTOTUNE)\\\n",
-    "    .batch(batch_size, drop_remainder=True)\n",
-    "dw_test = dw_split['test']\\\n",
-    "    .map(preproc, num_parallel_calls=tf.data.AUTOTUNE)\\\n",
-    "    .batch(1, drop_remainder=True)"
+    "# EOF"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": 31,
-   "id": "58b73bef",
+   "cell_type": "markdown",
+   "id": "95dfee16-cf0b-4761-9e66-8a42e6e63c2b",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "2024-06-18 13:07:28.605078: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n",
-      "2024-06-18 13:07:28.609527: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
-     ]
-    }
-   ],
    "source": [
-    "# Way 2: preprocess first\n",
-    "\n",
-    "dw = utils.restore_cardinality(\n",
-    "    slider.dataset.map(preproc, num_parallel_calls=tf.data.AUTOTUNE)\n",
-    ")\n",
-    "\n",
-    "dw_split = utils.split_dataset(dw, splits, ds_size=int(dw.cardinality()), labels=np.arange(n_classes))\n",
-    "\n",
-    "dw_train = dw_split['train']\\\n",
-    "    .shuffle(ds_size, reshuffle_each_iteration=True)\\\n",
-    "    .batch(batch_size, drop_remainder=True)\\\n",
-    "    .prefetch(tf.data.AUTOTUNE)\n",
-    "dw_val = dw_split['val'].batch(batch_size, drop_remainder=True)\n",
-    "dw_test = dw_split['test'].batch(1, drop_remainder=True)"
+    "Test the feature transformation model to see how it acts across the batch."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
-   "id": "91e4d711",
+   "execution_count": null,
+   "id": "1546bef6",
    "metadata": {},
    "outputs": [],
    "source": [
-    "model_feature.trainable = False\n",
-    "\n",
-    "model_clas = models.Sequential([\n",
-    "    layers.Dense(128, activation='relu'),\n",
-    "    layers.BatchNormalization(),\n",
-    "    layers.Dense(n_classes) # nb labels\n",
-    "], name='Classification_head')\n",
+    "# eles = list(ds_train.take(1))[0]\n",
+    "eles = list(ds_train.take(1).as_numpy_iterator())[0]\n",
     "\n",
-    "x = layers.Input(input_shape)\n",
+    "xx = ops.take(eles[0][0], [2], axis=0)\n",
+    "yy = model_feature.predict(xx)  # apply on a single input\n",
+    "zz = model_feature.predict(eles[0][0])[2]  # apply on a batch of inputs then take the corresponding output\n",
     "\n",
-    "model_fine = models.Model(inputs=x, outputs=model_clas(model_feature(x)))\n",
+    "# yy = model._encoder.predict(xx)\n",
+    "# zz = model._encoder.predict(eles[0][0])[2]\n",
     "\n",
-    "model_fine.compile(\n",
-    "    optimizer=keras.optimizers.Adam(),\n",
-    "    loss=losses.SparseCategoricalCrossentropy(from_logits=True),\n",
-    "    # metrics=[metrics.SparseCategoricalAccuracy()]\n",
-    ")"
+    "# Comparison: NOT zero.\n",
+    "np.abs(yy-zz)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "03fca33b",
+   "id": "75b7e8b5-6d23-4b77-b9ec-1ee0ec1431d1",
    "metadata": {},
    "outputs": [],
-   "source": [
-    "hh = model_fine.fit(\n",
-    "    dw_val,\n",
-    "    validation_data=dw_test,\n",
-    "    epochs=2\n",
-    ")"
-   ]
+   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "dpmhm-yVS8YoI0-py3.11",
+   "display_name": "Python (dpmhm-yVS8YoI0-py3.11)",
    "language": "python",
-   "name": "python3"
+   "name": "dpmhm-yvs8yoi0-py3.11"
   },
   "language_info": {
    "codemirror_mode": {