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MarkDaousttensorflower-gardener
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Clear deleted api_guide links.
These guides have been deleted (had no content). fixes #23443 PiperOrigin-RevId: 219881820
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tensorflow/contrib/crf/__init__.py

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# ==============================================================================
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"""Linear-chain CRF layer.
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See the [CRF](https://tensorflow.org/api_guides/python/contrib.crf) guide.
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@@crf_decode
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tensorflow/contrib/framework/__init__.py

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"""Framework utilities.
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See the
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[Contrib Framework](https://tensorflow.org/api_guides/python/contrib.framework)
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guide.
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tensorflow/contrib/layers/__init__.py

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# ==============================================================================
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"""Ops for building neural network layers, regularizers, summaries, etc.
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See the
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[Contrib Layers](https://tensorflow.org/api_guides/python/contrib.layers)
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guide.
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tensorflow/contrib/learn/__init__.py

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[contrib/learn/README.md](https://www.tensorflow.org/code/tensorflow/contrib/learn/README.md)
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for migration instructions.
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See the [Contrib Learn](https://tensorflow.org/api_guides/python/contrib.learn)
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guide.
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@@Estimator
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tensorflow/contrib/rnn/__init__.py

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# ==============================================================================
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"""RNN Cells and additional RNN operations.
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See [Contrib RNN](https://tensorflow.org/api_guides/python/contrib.rnn) guide.
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<!--From core-->
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tensorflow/contrib/util/__init__.py

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"""Utilities for dealing with Tensors.
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See [Contrib Util](https://tensorflow.org/api_guides/python/contrib.util) guide.
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tensorflow/lite/g3doc/convert/cmdline_examples.md

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The TensorFlow Lite Converter is compatible with fixed point quantization models
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described [here](https://www.tensorflow.org/performance/quantization). These are
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float models with
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[`FakeQuant*`](https://www.tensorflow.org/api_guides/python/array_ops#Fake_quantization)
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ops inserted at the boundaries of fused layers to record min-max range
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information. This generates a quantized inference workload that reproduces the
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quantization behavior that was used during training.
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float models with `FakeQuant*` ops inserted at the boundaries of fused layers
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to record min-max range information. This generates a quantized inference
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workload that reproduces the quantization behavior that was used during
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training.
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The following command generates a quantized TensorFlow Lite FlatBuffer from a
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"quantized" TensorFlow GraphDef.

tensorflow/python/client/client_lib.py

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"""Support for launching graphs and executing operations.
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See the [Client](https://tensorflow.org/api_guides/python/client) guide.
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See the [Client](https://www.tensorflow.org/guide/graphs) guide.
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"""
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from __future__ import absolute_import

tensorflow/python/debug/__init__.py

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# ==============================================================================
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"""Public Python API of TensorFlow Debugger (tfdbg).
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See the [TFDBG](https://tensorflow.org/api_guides/python/tfdbg) guide.
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See the [TFDBG](https://www.tensorflow.org/guide/debugger) guide.
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tensorflow/python/lib/io/python_io.py

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# limitations under the License.
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# ==============================================================================
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"""Python functions for directly manipulating TFRecord-formatted files.
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See the [Python IO](https://tensorflow.org/api_guides/python/python_io) guide.
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"""
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"""Python functions for directly manipulating TFRecord-formatted files."""
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from __future__ import absolute_import
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from __future__ import division

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