fix compatibility of batch_norm layer (#310)

* fix compatibility of batch_norm layer

* fix yapf

parl/core/fluid/layers/layer_wrappers.py

@@ -46,6 +46,7 @@ from paddle.fluid.framework import Variable
 from paddle.fluid.layers import *
 from paddle.fluid.param_attr import ParamAttr
 from parl.core.fluid.layers.attr_holder import AttrHolder
+from parl.utils import get_fluid_version
 
 
 def update_attr_name(name, default_name, attr, is_bias):
@@ -497,61 +498,119 @@ def layer_norm(**kwargs):
     raise NotImplementedError()
 
 
-def batch_norm(act=None,
-               momentum=0.9,
-               epsilon=1e-05,
-               param_attr=None,
-               bias_attr=None,
-               data_layout='NCHW',
-               in_place=False,
-               name=None,
-               moving_mean_name=None,
-               moving_variance_name=None,
-               do_model_average_for_mean_and_var=False,
-               fuse_with_relu=False,
-               use_global_stats=False):
-    """
-    Return a function that creates a paddle.fluid.layers.batch_norm.
-
-    """
-    default_name = "batch_norm"
-    param_attr = update_attr_name(name, default_name, param_attr, False)
-    bias_attr = update_attr_name(name, default_name, bias_attr, True)
-    moving_mean_attr = update_attr_name(name, default_name + "_moving_mean",
-                                        None, False)
-    moving_variance_attr = update_attr_name(
-        name, default_name + "_moving_variance", None, False)
-
-    class BatchNorm_(LayerFunc):
-        def __init__(self):
-            super(BatchNorm_, self).__init__(
-                AttrHolder(
-                    param_attr=param_attr,
-                    bias_attr=bias_attr,
-                    moving_mean_attr=moving_mean_attr,
-                    moving_variance_attr=moving_variance_attr))
-
-        def __call__(self, input, is_test=False):
-            return layers.batch_norm(
-                input=input,
-                act=act,
-                is_test=is_test,
-                momentum=momentum,
-                epsilon=epsilon,
-                param_attr=self.attr_holder.param_attr,
-                bias_attr=self.attr_holder.bias_attr,
-                data_layout=data_layout,
-                in_place=in_place,
-                name=name,
-                moving_mean_name=self.attr_holder.moving_mean_attr.name,
-                moving_variance_name=self.attr_holder.moving_variance_attr.
-                name,
-                do_model_average_for_mean_and_var=
-                do_model_average_for_mean_and_var,
-                fuse_with_relu=fuse_with_relu,
-                use_global_stats=use_global_stats)
-
-    return BatchNorm_()
+fluid_version = get_fluid_version()
+if fluid_version >= 162 or fluid_version == 0:
+
+    def batch_norm(act=None,
+                   momentum=0.9,
+                   epsilon=1e-05,
+                   param_attr=None,
+                   bias_attr=None,
+                   data_layout='NCHW',
+                   in_place=False,
+                   name=None,
+                   moving_mean_name=None,
+                   moving_variance_name=None,
+                   do_model_average_for_mean_and_var=False,
+                   use_global_stats=False):
+        """
+        Return a function that creates a paddle.fluid.layers.batch_norm.
+
+        """
+        default_name = "batch_norm"
+        param_attr = update_attr_name(name, default_name, param_attr, False)
+        bias_attr = update_attr_name(name, default_name, bias_attr, True)
+        moving_mean_attr = update_attr_name(
+            name, default_name + "_moving_mean", None, False)
+        moving_variance_attr = update_attr_name(
+            name, default_name + "_moving_variance", None, False)
+
+        class BatchNorm_(LayerFunc):
+            def __init__(self):
+                super(BatchNorm_, self).__init__(
+                    AttrHolder(
+                        param_attr=param_attr,
+                        bias_attr=bias_attr,
+                        moving_mean_attr=moving_mean_attr,
+                        moving_variance_attr=moving_variance_attr))
+
+            def __call__(self, input, is_test=False):
+                return layers.batch_norm(
+                    input=input,
+                    act=act,
+                    is_test=is_test,
+                    momentum=momentum,
+                    epsilon=epsilon,
+                    param_attr=self.attr_holder.param_attr,
+                    bias_attr=self.attr_holder.bias_attr,
+                    data_layout=data_layout,
+                    in_place=in_place,
+                    name=name,
+                    moving_mean_name=self.attr_holder.moving_mean_attr.name,
+                    moving_variance_name=self.attr_holder.moving_variance_attr.
+                    name,
+                    do_model_average_for_mean_and_var=
+                    do_model_average_for_mean_and_var,
+                    use_global_stats=use_global_stats)
+
+        return BatchNorm_()
+else:
+
+    def batch_norm(act=None,
+                   momentum=0.9,
+                   epsilon=1e-05,
+                   param_attr=None,
+                   bias_attr=None,
+                   data_layout='NCHW',
+                   in_place=False,
+                   name=None,
+                   moving_mean_name=None,
+                   moving_variance_name=None,
+                   do_model_average_for_mean_and_var=False,
+                   fuse_with_relu=False,
+                   use_global_stats=False):
+        """
+        Return a function that creates a paddle.fluid.layers.batch_norm.
+
+        """
+        default_name = "batch_norm"
+        param_attr = update_attr_name(name, default_name, param_attr, False)
+        bias_attr = update_attr_name(name, default_name, bias_attr, True)
+        moving_mean_attr = update_attr_name(
+            name, default_name + "_moving_mean", None, False)
+        moving_variance_attr = update_attr_name(
+            name, default_name + "_moving_variance", None, False)
+
+        class BatchNorm_(LayerFunc):
+            def __init__(self):
+                super(BatchNorm_, self).__init__(
+                    AttrHolder(
+                        param_attr=param_attr,
+                        bias_attr=bias_attr,
+                        moving_mean_attr=moving_mean_attr,
+                        moving_variance_attr=moving_variance_attr))
+
+            def __call__(self, input, is_test=False):
+                return layers.batch_norm(
+                    input=input,
+                    act=act,
+                    is_test=is_test,
+                    momentum=momentum,
+                    epsilon=epsilon,
+                    param_attr=self.attr_holder.param_attr,
+                    bias_attr=self.attr_holder.bias_attr,
+                    data_layout=data_layout,
+                    in_place=in_place,
+                    name=name,
+                    moving_mean_name=self.attr_holder.moving_mean_attr.name,
+                    moving_variance_name=self.attr_holder.moving_variance_attr.
+                    name,
+                    do_model_average_for_mean_and_var=
+                    do_model_average_for_mean_and_var,
+                    fuse_with_relu=fuse_with_relu,
+                    use_global_stats=use_global_stats)
+
+        return BatchNorm_()
 
 
 def create_parameter(shape,

parl/utils/utils.py

@@ -20,7 +20,7 @@ import numpy as np
 __all__ = [
     'has_func', 'action_mapping', 'to_str', 'to_byte', 'is_PY2', 'is_PY3',
     'MAX_INT32', '_HAS_FLUID', '_HAS_TORCH', '_IS_WINDOWS', '_IS_MAC',
-    'kill_process'
+    'kill_process', 'get_fluid_version'
 ]