[Dy2Stat]Add apply_optimization for @to_static and remove...

[Dy2Stat]Add apply_optimization for @to_static and remove BreakTransformOptimizer by default (#43320)

* [Dy2Stat]Add apply_optimization for @to_static and remove BreakTransformOptimizer by default

* fix unittest

python/paddle/fluid/dygraph/dygraph_to_static/ast_transformer.py

@@ -18,6 +18,7 @@ from __future__ import print_function
 # It provides a compatibility layer between the AST of various Python versions,
 # as produced by ast.parse from the standard ast module.
 # See details in https://github.com/serge-sans-paille/gast/
+import os
 from paddle.utils import gast
 from paddle.fluid.dygraph.dygraph_to_static.assert_transformer import AssertTransformer
 from paddle.fluid.dygraph.dygraph_to_static.basic_api_transformer import BasicApiTransformer
@@ -44,6 +45,18 @@ __all__ = ['DygraphToStaticAst']
 DECORATOR_NAMES = ['declarative', 'to_static', 'dygraph_to_static_func']
 
 
+def apply_optimization(transformers):
+    """
+    Judge wheter to apply optimized transformation, such as BreakTransformOptimizer.
+    And not all optimized transformations are applied by default. It's controlled by
+    'export FLAGS_optim_transformation=1'
+    """
+    flag = str(
+        os.environ.get('FLAGS_optim_transformation')) in ['1', 'True', 'true']
+    if flag:
+        transformers.insert(3, BreakTransformOptimizer)
+
+
 class DygraphToStaticAst(gast.NodeTransformer):
     """
     Main class to transform Dygraph to Static Graph
@@ -77,7 +90,6 @@ class DygraphToStaticAst(gast.NodeTransformer):
             BasicApiTransformer,  # Basic Api
             TensorShapeTransformer,  # Tensor.shape -> layers.shape(Tensor)
             ListTransformer,  # List used in control flow
-            BreakTransformOptimizer,  # optimize transfromation of break in loops
             BreakContinueTransformer,  # break/continue in loops
             ReturnTransformer,  # return in functions
             LogicalTransformer,  # logical and/or/not
@@ -90,6 +102,8 @@ class DygraphToStaticAst(gast.NodeTransformer):
             GradTransformer,  # transform paddle.grad to paddle.gradients
         ]
 
+        apply_optimization(transformers)
+
         for index, transformer in enumerate(transformers):
             self._apply(transformer, node_wrapper, log_level=index + 1)
 

python/paddle/fluid/tests/unittests/dygraph_to_static/test_loop.py

@@ -122,10 +122,12 @@ def for_loop_dyfunc_not_support(max_len):
 
 
 def for_break_single_return(max_len):
+    x = 0
     for i in range(3):
         if i == 2:
             break
-    return i
+        x += 1
+    return x
 
 
 def while_loop_bool_op(x):
@@ -324,6 +326,7 @@ class TestTransformWhileLoop(unittest.TestCase):
     def test_ast_to_func(self):
         static_numpy = self._run_static()
         dygraph_numpy = self._run_dygraph()
+        print(static_numpy, dygraph_numpy)
         self.assertTrue(np.allclose(dygraph_numpy, static_numpy))