Merge remote-tracking branch 'upstream/develop' into fixed_topk

x2paddle/op_mapper/onnx2paddle/opset9/opset.py

@@ -262,6 +262,8 @@ class OpSet9():
         shape = node.out_shapes[0]
 
         if hasattr(node.weight, "shape") and len(node.weight.shape) == 0:
+            if node.weight == float('inf') or node.weight == float('-inf'):
+                node.weight = string(node.weight)
             self.paddle_graph.add_layer(
                 "paddle.full",
                 inputs={},
@@ -792,6 +794,8 @@ class OpSet9():
         if len(value) == 1:
             value = value.tolist()
             value = value[0]
+            if value == float('inf') or value == float('-inf'):
+                value = string(value)
             self.paddle_graph.add_layer(
                 "paddle.full",
                 inputs={},
@@ -1195,7 +1199,6 @@ class OpSet9():
     @print_mapping_info
     def ConstantOfShape(self, node):
         val_shape = self.graph.get_input_node(node, idx=0, copy=True)
-        val_y = self.graph.get_node(node.layer.output[0], copy=True)
 
         value = node.get_attr('value')
         dtype = value.dtype
@@ -1204,6 +1207,8 @@ class OpSet9():
                                  'this is not supported')
         if len(value) == 1:
             value = value[0]
+            if value == float('inf') or value == float('-inf'):
+                value = string(value)
             layer_attrs = {'dtype': string(dtype), 'fill_value': value}
             self.paddle_graph.add_layer(
                 "paddle.full",
@@ -1563,20 +1568,37 @@ class OpSet9():
         val_x = self.graph.get_input_node(node, idx=0, copy=True)
         output_shape = val_x.out_shapes[0]
         axis = node.get_attr('axis', 1)
-        shape_list = [1, 1]
         if axis == 0:
-            for s in output_shape:
-                shape_list[1] *= s
+            self.paddle_graph.add_layer(
+                'paddle.reshape',
+                inputs={"x": val_x.name},
+                outputs=[node.name],
+                shape=[1, -1])
         else:
-            for s in output_shape[:axis]:
-                shape_list[0] *= s
-            for s in output_shape[axis:]:
-                shape_list[1] *= s
-        self.paddle_graph.add_layer(
-            'paddle.reshape',
-            inputs={"x": val_x.name},
-            outputs=[node.name],
-            shape=shape_list)
+            if len(output_shape) != 0:
+                shape_list = [1, 1]
+                for s in output_shape[:axis]:
+                    shape_list[0] *= s
+                for s in output_shape[axis:]:
+                    shape_list[1] *= s
+                self.paddle_graph.add_layer(
+                    'paddle.reshape',
+                    inputs={"x": val_x.name},
+                    outputs=[node.name],
+                    shape=shape_list)
+            else:
+                # flatten + reshape
+                self.paddle_graph.add_layer(
+                    "paddle.flatten",
+                    inputs={"input": val_x.name},
+                    outputs=[val_x.name + "_flatten"],
+                    start_axis=[0],
+                    stop_axis=[axis])
+                self.paddle_graph.add_layer(
+                    'paddle.reshape',
+                    inputs={'x': val_x.name + "_flatten"},
+                    outputs=[node.name],
+                    shape=[0, -1])
 
     @print_mapping_info
     def Gemm(self, node):
@@ -1846,40 +1868,13 @@ class OpSet9():
         val_x = self.graph.get_input_node(node, idx=1, copy=True)
         val_y = self.graph.get_input_node(node, idx=2, copy=True)
 
-        not_condition = condition.name + '_not'
-        self.paddle_graph.add_layer(
-            "paddle.logical_not",
-            inputs={"x": condition.name},
-            outputs=[not_condition])
-        cast_not_condition = not_condition + '_cast'
-        self.paddle_graph.add_layer(
-            "paddle.cast",
-            inputs={"x": not_condition},
-            outputs=[cast_not_condition],
-            dtype=string(val_x.dtype))
-        cast_condition = condition.name + '_cast'
-        self.paddle_graph.add_layer(
-            "paddle.cast",
-            inputs={"x": condition.name},
-            outputs=[cast_condition],
-            dtype=string(val_x.dtype))
-        mul_val_x = val_x.name + '_mul'
-        self.paddle_graph.add_layer(
-            "paddle.multiply",
-            inputs={'x': val_x.name,
-                    'y': cast_condition},
-            outputs=[mul_val_x])
-        mul_val_y = val_y.name + '_mul'
-        self.paddle_graph.add_layer(
-            "paddle.multiply",
-            inputs={'x': val_y.name,
-                    'y': cast_not_condition},
-            outputs=[mul_val_y])
-
         self.paddle_graph.add_layer(
-            "paddle.add",
-            inputs={'x': mul_val_x,
-                    'y': mul_val_y},
+            "paddle.where",
+            inputs={
+                'condition': condition.name,
+                'x': val_x.name,
+                'y': val_y.name
+            },
             outputs=[node.name])
 
     @print_mapping_info