From c05352008d253adf7fe0bf452425252f716bed26 Mon Sep 17 00:00:00 2001
From: zhangbo9674 <82555433+zhangbo9674@users.noreply.github.com>
Date: Wed, 22 Sep 2021 17:31:30 +0800
Subject: [PATCH]  [cherry-pick] fix bug of module 'paddle' has no attribute
 'fluid' for python3.6 (#35862) (#35900)

fix bug of module paddle has no attribute fluid for python3.6.
---
 python/paddle/fluid/dygraph/amp/auto_cast.py | 24 +++++++++-----------
 1 file changed, 11 insertions(+), 13 deletions(-)

diff --git a/python/paddle/fluid/dygraph/amp/auto_cast.py b/python/paddle/fluid/dygraph/amp/auto_cast.py
index 25a73230638..0d02a383c1b 100644
--- a/python/paddle/fluid/dygraph/amp/auto_cast.py
+++ b/python/paddle/fluid/dygraph/amp/auto_cast.py
@@ -23,7 +23,6 @@ import functools
 import paddle
 import operator
 import types
-import paddle.fluid as fluid
 
 __all__ = ['amp_guard', 'amp_decorate']
 
@@ -220,16 +219,16 @@ def amp_guard(enable=True,
      .. code-block:: python
 
         import numpy as np
-        import paddle.fluid as fluid
+        import paddle
 
         data = np.random.uniform(-1, 1, [10, 3, 32, 32]).astype('float32')
-        with fluid.dygraph.guard():
-            conv2d = fluid.dygraph.Conv2D(3, 2, 3)
-            data = fluid.dygraph.to_variable(data)
-            with fluid.dygraph.amp_guard():
+        with paddle.fluid.dygraph.guard():
+            conv2d = paddle.fluid.dygraph.Conv2D(3, 2, 3)
+            data = paddle.fluid.dygraph.to_variable(data)
+            with paddle.fluid.dygraph.amp_guard():
                 conv = conv2d(data)
                 print(conv.dtype) # FP16
-            with fluid.dygraph.amp_guard(enable=False):
+            with paddle.fluid.dygraph.amp_guard(enable=False):
                 conv = conv2d(data)
                 print(conv.dtype) # FP32
 
@@ -301,7 +300,7 @@ class StateDictHook(object):
     def __call__(self, state_dict):
         for key in state_dict:
             param = state_dict[key]
-            with fluid.dygraph.guard():
+            with paddle.fluid.dygraph.guard():
                 param_applied = paddle.cast(param, self._save_dtype)
                 param_applied.name = param.name
                 state_dict[key] = param_applied
@@ -335,16 +334,15 @@ def amp_decorate(models,
         # required: gpu
         # Demo1: single model and optimizer:
         import paddle
-        import paddle.fluid as fluid
 
         model = paddle.nn.Conv2D(3, 2, 3, bias_attr=False)
         optimzier = paddle.optimizer.SGD(parameters=model.parameters())
 
-        model, optimizer = fluid.dygraph.amp_decorate(models=model, optimizers=optimzier, level='O2')
+        model, optimizer = paddle.fluid.dygraph.amp_decorate(models=model, optimizers=optimzier, level='O2')
 
         data = paddle.rand([10, 3, 32, 32])
 
-        with fluid.dygraph.amp_guard(enable=True, custom_white_list=None, custom_black_list=None, level='O2'):
+        with paddle.fluid.dygraph.amp_guard(enable=True, custom_white_list=None, custom_black_list=None, level='O2'):
             output = model(data)
             print(output.dtype) # FP16
 
@@ -353,11 +351,11 @@ def amp_decorate(models,
         model2 = paddle.nn.Conv2D(3, 2, 3, bias_attr=False)
         optimizer2 = paddle.optimizer.Adam(parameters=model2.parameters())
 
-        models, optimizers = fluid.dygraph.amp_decorate(models=[model, model2], optimizers=[optimzier, optimizer2], level='O2')
+        models, optimizers = paddle.fluid.dygraph.amp_decorate(models=[model, model2], optimizers=[optimzier, optimizer2], level='O2')
 
         data = paddle.rand([10, 3, 32, 32])
 
-        with fluid.dygraph.amp_guard(enable=True, custom_white_list=None, custom_black_list=None, level='O2'):
+        with paddle.fluid.dygraph.amp_guard(enable=True, custom_white_list=None, custom_black_list=None, level='O2'):
             output = models[0](data)
             output2 = models[1](data)
             print(output.dtype) # FP16
-- 
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