Update models inputs (#630)

* Update stargan.md

* fix the paddle_type

* add docs

* add docs

* add acknowledge

* fix the docs

* fix the docs

* add docs

* fix

* add docs

* add docs

* Update README.md

* fix onnx inputs

* fix

* fix

* remove

* remove numpy input

x2paddle/core/program.py

@@ -220,6 +220,7 @@ class PaddleGraph(object):
             self.layers.pop(layer_id)
 
         self.get_inputs()
+
         if len(self.outputs) == 0:
             self.get_outputs()
 
@@ -293,8 +294,13 @@ class PaddleGraph(object):
                         self.inputs.extend(block.inputs)
 
         update(self.layers)
-        self.inputs = list(set(self.inputs))
-        if self.inputs is not None:
+        new_inputs = list()
+        for input_name in self.inputs:
+            if input_name in new_inputs:
+                continue
+            new_inputs.append(input_name)
+        self.inputs = new_inputs
+        if self.source_type == "pytorch" and self.inputs is not None:
             self.inputs.sort()
 
     def get_outputs(self):
@@ -313,6 +319,15 @@ class PaddleGraph(object):
                         self.outputs.append(output_name)
 
     def gen_code(self, code_dir=None, indent=2):
+        # 去除to_tensor的layer
+        invalid_list = list()
+        for layer_id, layer in self.layers.items():
+            if layer.kernel == "paddle.to_tensor":
+                if layer.attrs["data"] in self.inputs:
+                    invalid_list.append(layer_id)
+        for layer_id in invalid_list:
+            self.layers.pop(layer_id)
+
         def gen_codes(code_list, indent=0):
             indent_blank = "    " * indent
             codes = []

x2paddle/op_mapper/caffe2paddle/caffe_op_mapper.py

@@ -128,7 +128,6 @@ class CaffeOpMapper():
         self.params = dict()
         self.paddle_graph = PaddleGraph(parent_layer=None, source_type="caffe")
         self.paddle_graph.outputs = self.graph.output_nodes
-        self.input_index = 0
         self.inputs_info = {}
         self.nn_name2id = {}
         print("Total nodes: {}".format(
@@ -193,11 +192,10 @@ class CaffeOpMapper():
             "paddle.to_tensor",
             inputs={},
             outputs=[node.layer_name],
-            data="x{}".format(self.input_index))
+            data=node.name)
         shape = list(node.layer.input_param.shape[0].dim)[1:]
-        self.inputs_info["x{}".format(self.input_index)] = [[-1] + shape,
+        self.inputs_info[node.name] = [[-1] + shape,
                                                             "float32"]
-        self.input_index += 1
 
     def MemoryData(self, node):
         params = node.layer.memory_data_param
@@ -206,7 +204,7 @@ class CaffeOpMapper():
             "paddle.to_tensor",
             inputs={},
             outputs=[node.layer_name],
-            data="x{}".format(self.input_index))
+            data=node.layer_name)
         shape = list()
         shape.append(params.batch_size)
         shape.append(params.channels)
@@ -216,8 +214,7 @@ class CaffeOpMapper():
         else:
             shape.append(params.width)
             shape.append(params.height)
-        self.inputs_info["x{}".format(self.input_index)] = [shape, "float32"]
-        self.input_index += 1
+        self.inputs_info[node.layer_name] = [shape, "float32"]
 
     def Convolution(self, node):
         conv2d_name = name_generator("conv", self.nn_name2id)

x2paddle/op_mapper/onnx2paddle/opset9/opset.py

@@ -180,7 +180,6 @@ class OpSet9():
         super(OpSet9, self).__init__()
         self.graph = decoder.graph
         self.paddle_graph = paddle_graph
-        self.input_index = 0
         self.inputs_info = dict()
         self.weights = dict()
         self.nn_name2id = dict()
@@ -245,9 +244,8 @@ class OpSet9():
             kernel="paddle.to_tensor",
             inputs={},
             outputs=[node.name],
-            data="x{}".format(self.input_index))
-        self.inputs_info["x{}".format(self.input_index)] = [shape, node.dtype]
-        self.input_index += 1
+            data=node.name)
+        self.inputs_info[node.name] = [shape, node.dtype]
 
     @print_mapping_info
     def create_parameter(self, node, parameter=None):

x2paddle/op_mapper/tf2paddle/tf_op_mapper.py

@@ -91,7 +91,6 @@ class TFOpMapper():
             raise Exception("Model is not supported yet.")
         self.params = dict()
         self.nn_name2id = dict()
-        self.input_index = 0
         self.inputs_info = dict()
         self.paddle_graph = PaddleGraph(parent_layer=None, source_type="tf")
         self.paddle_graph.outputs = self.graph.output_nodes
@@ -213,9 +212,8 @@ class TFOpMapper():
             kernel="paddle.to_tensor",
             inputs={},
             outputs=[node.name],
-            data="x{}".format(self.input_index))
-        self.inputs_info["x{}".format(self.input_index)] = [shape, node.dtype]
-        self.input_index += 1
+            data=node.name)
+        self.inputs_info[node.name] = [shape, node.dtype]
 
     def Const(self, node):
         shape = node.out_shapes[0]