Merge pull request #478 from SunAhong1993/tf

fix the tf

x2paddle/decoder/tf_decoder.py

@@ -361,6 +361,8 @@ class TFDecoder(object):
                 continue
             graph_node = TFGraphNode(layer)
             dtype = graph_node.layer.attr['dtype'].type
+            if dtype == 10:
+                continue
 
             need_define_shape = 0
             if self.define_input_shape:

x2paddle/op_mapper/dygraph/tf2paddle/tf_op_mapper.py

@@ -676,8 +676,8 @@ class TFOpMapper(OpMapper):
         input = self.graph.get_input_node(node, 0)
         paddings = self.graph.get_input_node(node, 1)
         assert paddings.layer_type == "Const", "Padding should be Const"
-        paddings = np.flip(paddings.value, 0).flatten().tolist()
-        dim = int(len(paddings) / 2)
+        new_paddings = numpy.flip(paddings.value, 0).flatten().tolist()
+        dim = int(len(new_paddings) / 2)
         transpose_name = gen_name("pad", "transpose")
         self.paddle_graph.add_layer(
             kernel="paddle.transpose",
@@ -688,7 +688,7 @@ class TFOpMapper(OpMapper):
             kernel="paddle.nn.Pad{}D".format(dim),
             inputs={"x": transpose_name},
             outputs=layer_outputs,
-            pad=new_padding)
+            pad=new_paddings)
         self.paddle_graph.add_layer(
             kernel="paddle.transpose",
             inputs={"x": node.name},

x2paddle/op_mapper/static/tf2paddle/tf_op_mapper.py

@@ -661,7 +661,7 @@ class TFOpMapper(OpMapper):
         input = self.graph.get_input_node(node, 0)
         paddings = self.graph.get_input_node(node, 1)
         assert paddings.layer_type == "Const", "Padding should be Const"
-        paddings = np.flip(paddings.value, 0).flatten().tolist()
+        new_paddings = numpy.flip(paddings.value, 0).flatten().tolist()
         transpose_name = gen_name("pad", "transpose")
         self.paddle_graph.add_layer(
             kernel="paddle.transpose",
@@ -672,7 +672,7 @@ class TFOpMapper(OpMapper):
             kernel="paddle.nn.functional.pad".format(dim),
             inputs={"x": transpose_name},
             outputs=[node.name],
-            pad=new_padding)
+            pad=new_paddings)
         self.paddle_graph.add_layer(
             kernel="paddle.transpose",
             inputs={"x": node.name},