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Merge pull request #2010 from sushreebarsa:patch-9
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site/en/tutorials/distribute/input.ipynb

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"id": "lNy9GxjSlMKQ"
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},
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"source": [
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"To use `tf.distribute` APIs to scale, it is recommended that users use `tf.data.Dataset` to represent their input. `tf.distribute` has been made to work efficiently with `tf.data.Dataset` (for example, automatic prefetch of data onto each accelerator device) with performance optimizations being regularly incorporated into the implementation. If you have a use case for using something other than `tf.data.Dataset`, please refer a later [section](\"tensorinputs\") in this guide.\n",
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"To use `tf.distribute` APIs to scale, it is recommended that users use `tf.data.Dataset` to represent their input. `tf.distribute` has been made to work efficiently with `tf.data.Dataset` (for example, automatic prefetch of data onto each accelerator device) with performance optimizations being regularly incorporated into the implementation. If you have a use case for using something other than `tf.data.Dataset`, please refer a later [section](#tensorinputs) in this guide.\n",
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"In a non distributed training loop, users first create a `tf.data.Dataset` instance and then iterate over the elements. For example:\n"
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]
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"colab": {
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"collapsed_sections": [],
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"name": "input.ipynb",
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"provenance": [],
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"toc_visible": true
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},
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"kernelspec": {

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