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typo fix
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site/en/r1/tutorials/images/transfer_learning.ipynb

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"\n",
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"# Freeze all the layers before the `fine_tune_at` layer\n",
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"for layer in base_model.layers[:fine_tune_at]:\n",
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" layer.trainable = False"
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" layer.trainable = False"
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]
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},
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{

site/en/tutorials/images/data_augmentation.ipynb

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"outputs": [],
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"source": [
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"cropped = tf.image.central_crop(image, central_fraction=0.5)\n",
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"visualize(image,cropped)"
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"visualize(image, cropped)"
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]
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},
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{
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"Note: `seed` is a `Tensor` of shape `(2,)` whose values are any integers.\n",
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"\n",
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"In the following sections, you will:\n",
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"1. Go over examples of using random image operations to transform an image; and\n",
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"1. Go over examples of using random image operations to transform an image\n",
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"2. Demonstrate how to apply random transformations to a training dataset."
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]
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},
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},
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"outputs": [],
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"source": [
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"# Create a `Counter` object and `Dataset.zip` it together with the trainining set.\n",
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"# Create a `Counter` object and `Dataset.zip` it together with the training set.\n",
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"counter = tf.data.experimental.Counter()\n",
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"train_ds = tf.data.Dataset.zip((train_datasets, (counter, counter)))"
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]

site/en/tutorials/images/transfer_learning.ipynb

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"\n",
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"# Freeze all the layers before the `fine_tune_at` layer\n",
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"for layer in base_model.layers[:fine_tune_at]:\n",
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" layer.trainable = False"
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" layer.trainable = False"
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]
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},
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{

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