Upload apex-master/docs/source/fp16_utils.rst with huggingface_hub

apex-master/docs/source/fp16_utils.rst

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+.. role:: hidden
+    :class: hidden-section
+
+apex.fp16_utils
+===================================
+
+This submodule contains utilities designed to streamline the mixed precision training recipe 
+presented by NVIDIA `on Parallel Forall`_ and in GTC 2018 Sessions 
+`Training Neural Networks with Mixed Precision: Theory and Practice`_ and 
+`Training Neural Networks with Mixed Precision: Real Examples`_.
+For Pytorch users, Real Examples in particular is recommended.
+
+Full runnable Python scripts demonstrating ``apex.fp16_utils`` 
+can be found on the Github page:
+
+| `Simple FP16_Optimizer demos`_
+|
+| `Distributed Mixed Precision Training with imagenet`_
+|
+| `Mixed Precision Training with word_language_model`_
+|
+|
+
+.. _`on Parallel Forall`:
+    https://devblogs.nvidia.com/mixed-precision-training-deep-neural-networks/
+.. _`Training Neural Networks with Mixed Precision: Theory and Practice`:
+    http://on-demand.gputechconf.com/gtc/2018/video/S8923/
+.. _`Training Neural Networks with Mixed Precision: Real Examples`:
+    http://on-demand.gputechconf.com/gtc/2018/video/S81012/
+.. _`Simple FP16_Optimizer demos`:
+    https://github.com/NVIDIA/apex/tree/master/examples/FP16_Optimizer_simple
+.. _`Distributed Mixed Precision Training with imagenet`:
+    https://github.com/NVIDIA/apex/tree/master/examples/imagenet
+.. _`Mixed Precision Training with word_language_model`:
+    https://github.com/NVIDIA/apex/tree/master/examples/word_language_model
+
+.. automodule:: apex.fp16_utils
+.. currentmodule:: apex.fp16_utils
+
+Automatic management of master params + loss scaling
+----------------------------------------------------
+
+.. autoclass:: FP16_Optimizer
+    :members:
+
+.. autoclass:: LossScaler
+    :members:
+
+.. autoclass:: DynamicLossScaler
+    :members:
+
+Manual master parameter management
+----------------------------------
+
+.. autofunction:: prep_param_lists
+
+.. autofunction:: master_params_to_model_params
+
+.. autofunction:: model_grads_to_master_grads