fixed TSiT and TSSequencer issues

Author: oguiza

nbs/003_data.validation.ipynb

@@ -265,11 +265,11 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <td>0</td>\n",
-       "      <td>1.458827</td>\n",
-       "      <td>0.300000</td>\n",
-       "      <td>1.362652</td>\n",
+       "      <td>1.620233</td>\n",
+       "      <td>0.200000</td>\n",
+       "      <td>1.466389</td>\n",
        "      <td>0.300000</td>\n",
-       "      <td>00:02</td>\n",
+       "      <td>00:00</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>"
@@ -339,9 +339,9 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <td>0</td>\n",
-       "      <td>1.457477</td>\n",
-       "      <td>0.200000</td>\n",
-       "      <td>00:01</td>\n",
+       "      <td>1.362660</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>00:00</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>"
@@ -413,9 +413,9 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <td>0</td>\n",
-       "      <td>0.749274</td>\n",
-       "      <td>0.721294</td>\n",
-       "      <td>0.666667</td>\n",
+       "      <td>0.792934</td>\n",
+       "      <td>0.762534</td>\n",
+       "      <td>0.444444</td>\n",
        "      <td>00:00</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
@@ -684,11 +684,11 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <td>0</td>\n",
-       "      <td>204.070648</td>\n",
-       "      <td>13.636603</td>\n",
-       "      <td>199.854218</td>\n",
-       "      <td>13.712566</td>\n",
-       "      <td>00:01</td>\n",
+       "      <td>215.481400</td>\n",
+       "      <td>14.030172</td>\n",
+       "      <td>202.221893</td>\n",
+       "      <td>13.798750</td>\n",
+       "      <td>00:00</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>"
@@ -944,11 +944,11 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <td>0</td>\n",
-       "      <td>4539.636719</td>\n",
-       "      <td>50.971386</td>\n",
-       "      <td>7981.193848</td>\n",
-       "      <td>74.748787</td>\n",
-       "      <td>00:01</td>\n",
+       "      <td>4688.818359</td>\n",
+       "      <td>52.336243</td>\n",
+       "      <td>7955.546387</td>\n",
+       "      <td>74.580894</td>\n",
+       "      <td>00:00</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>"
@@ -1016,9 +1016,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "/Users/nacho/notebooks/tsai/nbs/022_tslearner.ipynb saved at 2025-01-22 18:45:21\n",
+      "/Users/nacho/notebooks/tsai/nbs/022_tslearner.ipynb saved at 2025-03-01 15:25:53\n",
       "Correct notebook to script conversion! 😃\n",
-      "Wednesday 22/01/25 18:45:24 CET\n"
+      "Saturday 01/03/25 15:25:56 CET\n"
      ]
     },
     {

nbs/021_calibration.ipynb

@@ -1122,13 +1122,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "py311t25",
+   "display_name": "python3",
    "language": "python",
    "name": "python3"
-  },
-  "language_info": {
-   "name": "python",
-   "version": "3.11.11"
   }
  },
  "nbformat": 4,

nbs/022_tslearner.ipynb

@@ -20,7 +20,7 @@ pip_requirements = torch>=1.10,<2.6
 conda_requirements = pytorch>=1.10,<2.6
 conda_user = timeseriesAI
 extra_requirements = sktime>=0.34.0 tsfresh>=0.20.3 PyWavelets>=1.7.0 nbformat>=5.10.4
-dev_requirements = nbdev>2 ipykernel>6
+dev_requirements = nbdev>2 ipykernel>6 ipython<9
 console_scripts = nb2py=tsai.export:nb2py
 nbs_path = nbs
 doc_path = _docs

nbs/068_models.TSiTPlus.ipynb

@@ -90,13 +90,13 @@ def __init__(self, c_in:int, seq_len:int, depth:int=6, d_model:int=128, act:str=
             self.feature_extractor = nn.Identity()
 
         # Linear projection
+        self.transpose = Transpose(1,2)
         if token_size is None and tokenizer is None and feature_extractor is None:
-            self.linear_proj = nn.Conv1d(c_in, d_model, 1)
+            self.linear_proj = nn.Linear(c_in, d_model)
+            # self.linear_proj = nn.Conv1d(c_in, d_model, 1)
         else:
             self.linear_proj = nn.Identity()
 
-        self.transpose = Transpose(1,2)
-
         # Position embedding & token
         if use_pe:
             self.pos_embed = nn.Parameter(torch.zeros(1, seq_len, d_model))
@@ -122,10 +122,10 @@ def forward(self, x):
         x = self.feature_extractor(x)
 
         # Linear projection
+        x = self.transpose(x)
         x = self.linear_proj(x)
 
         # Position embedding & token
-        x = self.transpose(x)
         if self.use_pe:
             x = x + self.pos_embed
         if self.use_token: # token is concatenated after position embedding so that embedding can be learned using self.supervised learning