Removing patching of loss.backward, which appears to cause memory leaks...

Removing patching of loss.backward, which appears to cause memory leaks (reference cycles?) in some models

apex/amp/handle.py

@@ -40,16 +40,8 @@ class AmpHandle(object):
                 'use `optimizer.scale_loss(loss)`.')
 
         # TODO: this code block is duplicated here and `opt.py`. Unify.
-        loss_backward = loss.backward
-        def warning_wrapper():
-            warnings.warn("You called .backward() on the unscaled loss "
-                          "inside a scale_loss block. This is almost "
-                          "certainly an error.", stacklevel=2)
-            loss_backward()
-        loss.backward = warning_wrapper
         loss_scale = self._default_scaler.loss_scale()
         yield loss * loss_scale
-        loss.backward = loss_backward
 
         should_skip = self._default_scaler.unscale_and_update(
             optimizer.param_groups, loss_scale)

apex/amp/opt.py

@@ -21,14 +21,6 @@ class OptimWrapper(object):
             yield loss
             return
 
-        loss_backward = loss.backward
-        def warning_wrapper():
-            warnings.warn("You called .backward() on the unscaled loss "
-                          "inside a scale_loss block. This is almost "
-                          "certainly an error.", stacklevel=2)
-            loss_backward()
-        loss.backward = warning_wrapper
-
         # When there are multiple losses per-optimizer, we need
         # to save out current grad accumulation, since we won't be
         # able to unscale this particulare loss once the grads are
@@ -44,7 +36,6 @@ class OptimWrapper(object):
         
         loss_scale = self._cur_loss_scaler().loss_scale()
         yield loss * loss_scale
-        loss.backward = loss_backward
 
         self._skip_next[self._loss_idx] = self._cur_loss_scaler().unscale_and_update(
             self._optimizer.param_groups, loss_scale)