fix directly_map, Eltwise and crop (#663)

x2paddle/op_mapper/caffe2paddle/caffe_op_mapper.py

@@ -168,13 +168,12 @@ class CaffeOpMapper():
             return False
 
     def directly_map(self, node):
-        inputs = node.layer.input
-        assert len(inputs) == 1, 'directly_map error with multi inputs'
+        assert len(node.layer.bottom) == 1, 'directly_map error with multi inputs'
         op_info = self.directly_map_ops[node.layer_type]
         input = self.graph.get_input_node(node, 0)
         paddle_op = op_info[0]
-        if paddle_op.startswith("paddle.nn"):
-            op_name = paddle_op[10:].lower()
+        if paddle_op.startswith("paddle.nn.layer"):
+            op_name = paddle_op[16:].lower()
             op_name = name_generator(op_name, self.nn_name2id)
             output_name = node.name
             layer_outputs = [op_name, output_name]
@@ -183,9 +182,19 @@ class CaffeOpMapper():
                 inputs={"x": input.name},
                 outputs=layer_outputs)
         else:
-            self.paddle_graph.add_layer(
-                kernel=paddle_op, inputs={"x": input.name},
-                outputs=[node.name])
+            if paddle_op.startswith("paddle.nn") and "layer" not in paddle_op:
+                op_name = paddle_op[10:].lower()
+                op_name = name_generator(op_name, self.nn_name2id)
+                output_name = node.name
+                layer_outputs = [op_name, output_name]
+                self.paddle_graph.add_layer(
+                    kernel=paddle_op,
+                    inputs={"x": input.name},
+                    outputs=layer_outputs)
+            else:
+                self.paddle_graph.add_layer(
+                    kernel=paddle_op, inputs={"x": input.name},
+                    outputs=[node.name])
 
     def Input(self, node):
         self.paddle_graph.add_layer(
@@ -610,8 +619,29 @@ class CaffeOpMapper():
             num_parameters=num_parameters)
 
     def Eltwise(self, node):
+        if len(node.layer.bottom) == 3 and node.layer.eltwise_param.operation == 1:
+            inputs_dict = {}
+            input0 = self.graph.get_input_node(node, idx=0, copy=True)
+            input1 = self.graph.get_input_node(node, idx=1, copy=True)
+            input2 = self.graph.get_input_node(node, idx=2, copy=True)
+            input0_name = input0.name
+            input1_name = input1.name
+            input2_name = input2.name
+            inputs_dict['x'] = input0_name
+            inputs_dict['y'] = input1_name
+            self.paddle_graph.add_layer(
+                "paddle.add", inputs=inputs_dict,
+                outputs=[node.layer_name+"_1"])
+            inputs_dict = {}
+            inputs_dict['x'] = node.layer_name+"_1"
+            inputs_dict['y'] = input2_name
+            self.paddle_graph.add_layer(
+                "paddle.add", inputs=inputs_dict,
+                outputs=[node.layer_name])
+            return
+
         assert len(
-            node.inputs) == 2, "The count of Eltwise node\'s input is not 2."
+            node.layer.bottom) == 2, "The count of Eltwise node\'s input is not 2."
         params = node.layer.eltwise_param
         mode = params.operation
         inputs = []
@@ -894,7 +924,9 @@ class CaffeOpMapper():
             axis += len(input_shape)
         offset_real = [0] * len(input_shape)
         if hasattr(params, "offset") and len(params.offset) > 0:
-            offset = list(params.offset)
+            offset_origin = list(params.offset)
+            if len(offset_origin)==1 :
+                offset = offset_origin * (len(input_shape) - axis)
             assert (len(input_shape) - axis
                     ) == len(offset), "invalid offset[%s] in crop layer" % (
                         str(offset))