From a726827ec88535c4b4aa74cdee308beafd32c763 Mon Sep 17 00:00:00 2001
From: Michael Carilli <mcarilli@nvidia.com>
Date: Fri, 28 Feb 2020 11:37:04 -0800
Subject: [PATCH] Formatting changes for gradient scaling (#33832)

Summary:
hard to get right locally...I can build the docs but never quite match what it looks like live.  the bullet point indentation was just an oversight.

Removing `Returns:` formatting tabs because they take up a lot of space when rendered and add no clarity.  Some functions in Pytorch [do use them](https://pytorch.org/docs/master/torch.html#torch.eye), but [many don't bother](https://pytorch.org/docs/master/torch.html#torch.is_tensor), so apparently some people shared my feelings (Not using them is in line with existing practice).
Pull Request resolved: https://github.com/pytorch/pytorch/pull/33832

Differential Revision: D20135581

Pulled By: ngimel

fbshipit-source-id: bc788a7e57b142f95c4fa5baf3fe01f94c45abd8
---
 torch/cuda/amp/grad_scaler.py | 32 +++++++++++++-------------------
 1 file changed, 13 insertions(+), 19 deletions(-)

diff --git a/torch/cuda/amp/grad_scaler.py b/torch/cuda/amp/grad_scaler.py
index dbb6371d633f..5331c0f8efe1 100644
--- a/torch/cuda/amp/grad_scaler.py
+++ b/torch/cuda/amp/grad_scaler.py
@@ -62,11 +62,11 @@ class GradScaler(object):
     ``scaler.step(optimizer)`` (or optional separate ``scaler.unscale_(optimizer)``, see :meth:`unscale_`).
 
     * If infs/NaNs are found, ``scaler.step(optimizer)`` skips the underlying ``optimizer.step()`` (so the params
-    themselves remain uncorrupted) and ``update()`` multiplies the scale by ``backoff_factor``.
+      themselves remain uncorrupted) and ``update()`` multiplies the scale by ``backoff_factor``.
 
     * If no infs/NaNs are found, ``scaler.step(optimizer)`` runs the underlying ``optimizer.step()`` as usual.
-    If ``growth_interval`` unskipped iterations occur consecutively, ``update()`` multiplies the scale by
-    ``growth_factor``.
+      If ``growth_interval`` unskipped iterations occur consecutively, ``update()`` multiplies the scale by
+      ``growth_factor``.
 
     The scale factor often causes infs/NaNs to appear in gradients for the first few iterations as its
     value calibrates.  ``scaler.step`` will skip the underlying ``optimizer.step()`` for these
@@ -125,11 +125,11 @@ class GradScaler(object):
         """
         Multiplies ('scales') a tensor or list of tensors by the scale factor.
 
+        Returns scaled outputs.  If this instance of :class:`GradScaler` is not enabled, outputs are returned
+        unmodified.
+
         Arguments:
             outputs (Tensor or iterable of Tensors):  Outputs to scale.
-
-        Returns:
-            Scaled outputs.  If this instance of :class:`GradScaler` is not enabled, outputs are returned unmodified.
         """
         if not self._enabled:
             return outputs
@@ -234,14 +234,13 @@ class GradScaler(object):
 
         ``*args`` and ``**kwargs`` are forwarded to ``optimizer.step()``.
 
+        Returns the return value of ``optimizer.step(*args, **kwargs)``.
+
         Arguments:
             optimizer (torch.optim.Optimizer):  Optimizer that applies the gradients.
             args:  Any arguments.
             kwargs:  Any keyword arguments.
 
-        Returns:
-            The return value of ``optimizer.step(*args, **kwargs)``.
-
         .. warning::
             Closure use is not currently supported.
         """
@@ -342,8 +341,7 @@ class GradScaler(object):
 
     def get_scale(self):
         """
-        Returns:
-            A Python float containing the current scale, or 1.0 if scaling is disabled.
+        Returns a Python float containing the current scale, or 1.0 if scaling is disabled.
 
         .. warning::
             :meth:`get_scale` incurs a CPU-GPU sync.
@@ -355,8 +353,7 @@ class GradScaler(object):
 
     def get_growth_factor(self):
         r"""
-        Returns:
-            A Python float containing the scale growth factor.
+        Returns a Python float containing the scale growth factor.
         """
         return self._growth_factor
 
@@ -369,8 +366,7 @@ class GradScaler(object):
 
     def get_backoff_factor(self):
         r"""
-        Returns:
-            A Python float containing the scale backoff factor.
+        Returns a Python float containing the scale backoff factor.
         """
         return self._backoff_factor
 
@@ -383,8 +379,7 @@ class GradScaler(object):
 
     def get_growth_interval(self):
         r"""
-        Returns:
-            A Python int containing the growth interval.
+        Returns a Python int containing the growth interval.
         """
         return self._growth_interval
 
@@ -403,8 +398,7 @@ class GradScaler(object):
 
     def is_enabled(self):
         r"""
-        Returns:
-            A bool indicating whether this instance is enabled.
+        Returns a bool indicating whether this instance is enabled.
         """
         return self._enabled