Merge pull request #757 from wjj19950828/support_for_SegFlow

Fixed scale and crop op

x2paddle/decoder/caffe_shape_inference.py

@@ -346,7 +346,15 @@ def shape_argmax(layer, input_shape):
 
 def shape_crop(layer, input_shape):
     assert len(input_shape) == 2, "the number of crop's inputs must be 2"
-    return [input_shape[1]]
+    params = layer.crop_param
+    axis = params.axis
+    if axis < 0:
+        axis += len(input_shape[0])
+    if axis > 0:
+        crop_shape = input_shape[0][:axis] + input_shape[1][axis:]
+    else:
+        crop_shape = input_shape[1]
+    return [crop_shape]
 
 
 def shape_flatten(layer, input_shape):

x2paddle/op_mapper/caffe2paddle/caffe_op_mapper.py

@@ -768,7 +768,8 @@ class CaffeOpMapper():
                     node.data[1]).astype("float32")
         params = node.layer.scale_param
         axis = params.axis
-        inputs = []
+        if axis < 0:
+            axis += len(node.in_shapes[0])
         if len(node.inputs) == 2:
             input0 = self.graph.get_input_node(node, idx=0, copy=True)
             input1 = self.graph.get_input_node(node, idx=1, copy=True)
@@ -777,11 +778,6 @@ class CaffeOpMapper():
             inputs_dict = {}
             inputs_dict['x'] = input0_name
             inputs_dict['y'] = input1_name
-            self.paddle_graph.add_layer(
-                "paddle.multiply",
-                inputs=inputs_dict,
-                outputs=[node.layer_name + "_mul"],
-                axis=1)
         else:
             self.paddle_graph.add_layer(
                 "self.create_parameter",
@@ -794,17 +790,17 @@ class CaffeOpMapper():
             inputs_dict = {}
             inputs_dict['x'] = input0_name
             inputs_dict['y'] = node.layer_name + "_cparam1"
-            if len(node.in_shapes[0]) == 2:
-                self.paddle_graph.add_layer(
-                    "paddle.multiply",
-                    inputs=inputs_dict,
-                    outputs=[node.layer_name + "_mul"])
-            else:
-                self.paddle_graph.add_layer(
-                    "paddle.multiply",
-                    inputs=inputs_dict,
-                    outputs=[node.layer_name + "_mul"],
-                    axis=axis)
+        if axis == len(node.in_shapes[0]) - 1:
+            self.paddle_graph.add_layer(
+                "paddle.multiply",
+                inputs=inputs_dict,
+                outputs=[node.layer_name + "_mul"])
+        else:
+            self.paddle_graph.add_layer(
+                "paddle.fluid.layers.elementwise_mul",
+                inputs=inputs_dict,
+                outputs=[node.layer_name + "_mul"],
+                axis=axis)
         self.paddle_graph.add_layer(
             "self.create_parameter",
             inputs={},
@@ -815,12 +811,10 @@ class CaffeOpMapper():
         inputs_dict['x'] = node.layer_name + "_mul"
         inputs_dict['y'] = node.layer_name + "_cparam2"
         output_shape = node.out_shapes[0]
-        if axis == -1:
+        if axis == len(output_shape) - 1:
             self.paddle_graph.add_layer(
                 "paddle.add", inputs=inputs_dict, outputs=[node.layer_name])
         else:
-            if axis < 0:
-                axis = axis + len(output_shape)
             param2_shape = self.params[node.layer_name + "_cparam2"].shape
             param2_shape_len = len(param2_shape)
             diff_len = len(output_shape) - axis - param2_shape_len
@@ -933,11 +927,15 @@ class CaffeOpMapper():
                     ) == len(offset), "invalid offset[%s] in crop layer" % (
                         str(offset))
             offset_real = [0] * axis + offset
+        if axis > 0:
+            crop_shape = node.in_shapes[0][:axis] + node.in_shapes[1][axis:]
+        else:
+            crop_shape = node.in_shapes[1]
         self.paddle_graph.add_layer(
             "paddle.crop",
             inputs={"x": input.name},
             outputs=[node.layer_name],
-            shape=node.in_shapes[1],
+            shape=crop_shape,
             offsets=list(offset_real))
 
     def Flatten(self, node):