add NCHW change

x2paddle/core/op_mapper.py

@@ -116,7 +116,7 @@ class OpMapper(object):
                                           feeded_var_names=input_names,
                                           target_vars=outputs,
                                           executor=exe,
-                                          params_filename="__params__")
+                                          params_filename=None)
         except:
             raise Exception(
                 "Paddle code was saved in {}/model.py, but seems there's wrong exist, please check model.py manually."

x2paddle/decoder/tf_decoder.py

@@ -24,7 +24,7 @@ import sys
 
 
 class TFGraphNode(GraphNode):
-    def __init__(self, layer, layer_name=None):
+    def __init__(self, layer, layer_name=None, data_format="NHWC"):
         if layer_name is None:
             super(TFGraphNode,
                   self).__init__(layer,
@@ -35,6 +35,8 @@ class TFGraphNode(GraphNode):
                                  layer_name.replace('/', '_').replace('-', '_'))
 
         self.layer_type = layer.op
+        self.tf_data_format = data_format
+        self.pd_data_format = "NCHW"
         self.fluid_code = FluidCode()
 
         self.dtype_map = {1: "float32", 3: "int32", 4: "int8", 9: "int64"}
@@ -86,15 +88,16 @@ class TFGraphNode(GraphNode):
 
 
 class TFGraph(Graph):
-    def __init__(self, model):
+    def __init__(self, model, data_format="NHWC"):
         super(TFGraph, self).__init__(model)
         self.identity_map = dict()
         self.multi_out_ops = ['Split', 'SplitV']
+        self.tf_data_format = data_format
 
     def build(self):
         for layer in self.model.node:
             self.node_map[layer.name.replace('/', '_').replace(
-                '-', '_')] = TFGraphNode(layer)
+                '-', '_')] = TFGraphNode(layer, data_format=self.tf_data_format)
 
         for layer_name, node in self.node_map.items():
             for in_node in node.layer.input:
@@ -166,9 +169,20 @@ class TFGraph(Graph):
                 idx = self.output_nodes.index(node_name)
                 self.output_nodes[idx] = input_node.layer_name
 
+    def data_format_propagation(self, node):
+        current_node = self.node_map[node.layer_name]
+        current_node = node.tf_data_format
+        outputs = current_node.outputs
+        if len(outputs) == 0:
+            return
+        for out in outputs:
+            next_node = self.node_map[out]
+            next_node.tf_data_format = node.tf_data_format
+            self.data_format_propagation(next_node)
+
 
 class TFDecoder(object):
-    def __init__(self, pb_model):
+    def __init__(self, pb_model, data_format="NHWC"):
         self.sess = tf.Session()
         self.input_info = dict()
         with gfile.FastGFile(pb_model, 'rb') as f:
@@ -186,7 +200,7 @@ class TFDecoder(object):
         self.sess.run(tf.global_variables_initializer())
 
         self.tf_graph = TFGraph(
-            self.sess.graph._as_graph_def(add_shapes=True)[0])
+            self.sess.graph._as_graph_def(add_shapes=True)[0], data_format)
         self.tf_graph.build()
 
     def _fix_output_shape(self, graph):