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[JA] Translations
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@ilyaspiridonov
ilyaspiridonov committed Nov 4, 2023
1 parent be9af37 commit 3afad22
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Showing 332 changed files with 36,978 additions and 7,407 deletions.
56 changes: 42 additions & 14 deletions site/ja/addons/tutorials/average_optimizers_callback.ipynb
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"cellView": "form",
"id": "tuOe1ymfHZPu"
},
"outputs": [],
"outputs": [

],
"source": [
"#@title Licensed under the Apache License, Version 2.0 (the \"License\");\n",
"# you may not use this file except in compliance with the License.\n",
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"metadata": {
"id": "sXEOqj5cIgyW"
},
"outputs": [],
"outputs": [

],
"source": [
"!pip install -U tensorflow-addons"
]
Expand All @@ -106,7 +110,9 @@
"metadata": {
"id": "IqR2PQG4ZaZ0"
},
"outputs": [],
"outputs": [

],
"source": [
"import tensorflow as tf\n",
"import tensorflow_addons as tfa"
Expand All @@ -118,7 +124,9 @@
"metadata": {
"id": "4hnJ2rDpI38-"
},
"outputs": [],
"outputs": [

],
"source": [
"import numpy as np\n",
"import os"
Expand All @@ -139,7 +147,9 @@
"metadata": {
"id": "KtylpxOmceaC"
},
"outputs": [],
"outputs": [

],
"source": [
"def create_model(opt):\n",
" model = tf.keras.models.Sequential([\n",
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"metadata": {
"id": "mMOeXVmbdilM"
},
"outputs": [],
"outputs": [

],
"source": [
"#Load Fashion MNIST dataset\n",
"train, test = tf.keras.datasets.fashion_mnist.load_data()\n",
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"metadata": {
"id": "_Q76K1fNk7Va"
},
"outputs": [],
"outputs": [

],
"source": [
"#Optimizers \n",
"sgd = tf.keras.optimizers.SGD(0.01)\n",
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"metadata": {
"id": "SnvZjt34qEHY"
},
"outputs": [],
"outputs": [

],
"source": [
"#Callback \n",
"checkpoint_path = \"./training/cp-{epoch:04d}.ckpt\"\n",
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"metadata": {
"id": "Xy8W4LYppadJ"
},
"outputs": [],
"outputs": [

],
"source": [
"#Build Model\n",
"model = create_model(sgd)\n",
Expand All @@ -282,7 +300,9 @@
"metadata": {
"id": "uU2iQ6HAZ6-E"
},
"outputs": [],
"outputs": [

],
"source": [
"#Evalute results\n",
"model.load_weights(checkpoint_dir)\n",
Expand All @@ -306,7 +326,9 @@
"metadata": {
"id": "--NIjBp-mhVb"
},
"outputs": [],
"outputs": [

],
"source": [
"#Build Model\n",
"model = create_model(moving_avg_sgd)\n",
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"metadata": {
"id": "zRAym9EBmnW9"
},
"outputs": [],
"outputs": [

],
"source": [
"#Evalute results\n",
"model.load_weights(checkpoint_dir)\n",
Expand All @@ -345,7 +369,9 @@
"metadata": {
"id": "Ia7ALKefnXWQ"
},
"outputs": [],
"outputs": [

],
"source": [
"#Build Model\n",
"model = create_model(stocastic_avg_sgd)\n",
Expand All @@ -360,7 +386,9 @@
"metadata": {
"id": "EOT2E9NBoeHI"
},
"outputs": [],
"outputs": [

],
"source": [
"#Evalute results\n",
"model.load_weights(checkpoint_dir)\n",
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56 changes: 42 additions & 14 deletions site/ja/addons/tutorials/image_ops.ipynb
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"cellView": "form",
"id": "l-m8KQ-nxK5l"
},
"outputs": [],
"outputs": [

],
"source": [
"#@title Licensed under the Apache License, Version 2.0 (the \"License\");\n",
"# you may not use this file except in compliance with the License.\n",
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"metadata": {
"id": "o_QTX_vHGbj7"
},
"outputs": [],
"outputs": [

],
"source": [
"!pip install -U tensorflow-addons"
]
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"metadata": {
"id": "5hVIKCrhWh4a"
},
"outputs": [],
"outputs": [

],
"source": [
"import tensorflow as tf\n",
"import numpy as np\n",
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"metadata": {
"id": "IgUsVhBQ6dSg"
},
"outputs": [],
"outputs": [

],
"source": [
"img_path = tf.keras.utils.get_file('tensorflow.png','https://tensorflow.org/images/tf_logo.png')"
]
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"metadata": {
"id": "NRlvNQdm1YI8"
},
"outputs": [],
"outputs": [

],
"source": [
"img_raw = tf.io.read_file(img_path)\n",
"img = tf.io.decode_image(img_raw)\n",
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"metadata": {
"id": "tbaIkUCS2eNv"
},
"outputs": [],
"outputs": [

],
"source": [
"bw_img = 1.0 - tf.image.rgb_to_grayscale(img)\n",
"\n",
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"metadata": {
"id": "SutWnbRoHl6i"
},
"outputs": [],
"outputs": [

],
"source": [
"mean = tfa.image.mean_filter2d(img, filter_shape=11)\n",
"_ = plt.imshow(mean)"
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"metadata": {
"id": "9kxUES9sM8Jl"
},
"outputs": [],
"outputs": [

],
"source": [
"rotate = tfa.image.rotate(img, tf.constant(np.pi/8))\n",
"_ = plt.imshow(rotate)"
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"metadata": {
"id": "HTh1Qpps8Rg5"
},
"outputs": [],
"outputs": [

],
"source": [
"transform = tfa.image.transform(img, [1.0, 1.0, -250, 0.0, 1.0, 0.0, 0.0, 0.0])\n",
"_ = plt.imshow(transform)"
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"metadata": {
"id": "zZBI-9XvBSuh"
},
"outputs": [],
"outputs": [

],
"source": [
"delta = 0.5\n",
"lower_saturation = 0.1\n",
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"metadata": {
"id": "vbCdwGtYChnQ"
},
"outputs": [],
"outputs": [

],
"source": [
"delta = 0.5\n",
"saturation = 0.3\n",
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"metadata": {
"id": "dG557eQDDtSK"
},
"outputs": [],
"outputs": [

],
"source": [
"input_img = tf.image.convert_image_dtype(tf.expand_dims(img, 0), tf.dtypes.float32)\n",
"\n",
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"metadata": {
"id": "-OMh6oeRQaYQ"
},
"outputs": [],
"outputs": [

],
"source": [
"gray = tf.image.convert_image_dtype(bw_img,tf.uint8)\n",
"# The op expects a batch of images, so add a batch dimension\n",
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"metadata": {
"accelerator": "GPU",
"colab": {
"collapsed_sections": [],
"collapsed_sections": [

],
"name": "image_ops.ipynb",
"toc_visible": true
},
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32 changes: 24 additions & 8 deletions site/ja/addons/tutorials/layers_normalizations.ipynb
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"cellView": "form",
"id": "aNZ7aEDyQIYU"
},
"outputs": [],
"outputs": [

],
"source": [
"#@title Licensed under the Apache License, Version 2.0 (the \"License\");\n",
"# you may not use this file except in compliance with the License.\n",
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"metadata": {
"id": "_ZQGY_ALnirQ"
},
"outputs": [],
"outputs": [

],
"source": [
"!pip install -U tensorflow-addons"
]
Expand All @@ -123,7 +127,9 @@
"metadata": {
"id": "7aGgPZG_WBHg"
},
"outputs": [],
"outputs": [

],
"source": [
"import tensorflow as tf\n",
"import tensorflow_addons as tfa"
Expand All @@ -144,7 +150,9 @@
"metadata": {
"id": "3wso9oidUZZQ"
},
"outputs": [],
"outputs": [

],
"source": [
"mnist = tf.keras.datasets.mnist\n",
"\n",
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"metadata": {
"id": "aIGjLwYWAm0v"
},
"outputs": [],
"outputs": [

],
"source": [
"model = tf.keras.models.Sequential([\n",
" # Reshape into \"channels last\" setup.\n",
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"metadata": {
"id": "6sLVv-C8f6Kf"
},
"outputs": [],
"outputs": [

],
"source": [
"model = tf.keras.models.Sequential([\n",
" # Reshape into \"channels last\" setup.\n",
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"metadata": {
"id": "Fh-Pp_e5UB54"
},
"outputs": [],
"outputs": [

],
"source": [
"model = tf.keras.models.Sequential([\n",
" # Reshape into \"channels last\" setup.\n",
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],
"metadata": {
"colab": {
"collapsed_sections": [],
"collapsed_sections": [

],
"name": "layers_normalizations.ipynb",
"toc_visible": true
},
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