fix the gru

x2paddle/op_mapper/dygraph/pytorch2paddle/aten.py

@@ -804,6 +804,47 @@ def aten_clamp(mapper, graph, node):
     return current_inputs, current_outputs
 
 
+def aten_clamp_min(mapper, graph, node):
+    """ 构造元素剪裁的PaddleLayer。
+
+    TorchScript示例:
+        %56 : Tensor = aten::clamp_min(%input.1, %46)
+        参数含义:
+        %56 (Tensor): 输出，累加后的结果。
+        %input.1 (Tensor): 输入，需要剪裁的Tensor。
+        %46 (float/Tensor): 最小值。
+    """
+    scope_name = mapper.normalize_scope_name(node)
+    output_name = mapper._get_outputs_name(node)[0]
+    layer_outputs = [output_name]
+    layer_inputs = {}
+    layer_attrs = {}
+    inputs_name, inputs_node = mapper._get_inputs_name(node)
+    # 获取当前节点输出的list
+    current_outputs = [output_name]
+    # 处理输入0，即%input.1
+    mapper._check_input(graph, inputs_node[0], inputs_name[0], current_outputs, scope_name)
+    layer_inputs["x"] = inputs_name[0]
+    # 获取当前节点输入、输出的list
+    current_inputs = list(layer_inputs.values())
+    # 处理输入1，即%46
+    if inputs_name[1] in mapper.attrs:
+        layer_attrs["min"] = mapper.attrs[inputs_name[1]]
+    else:
+        mapper._check_input(graph, inputs_node[1], inputs_name[1],
+                            current_outputs, scope_name)
+        layer_inputs["min"] = inputs_name[1]
+        current_inputs.append(inputs_name[1])
+
+    graph.add_layer(
+        "paddle.clip",
+        inputs=layer_inputs,
+        outputs=layer_outputs,
+        scope_name=scope_name,
+        **layer_attrs)
+    return current_inputs, current_outputs
+
+
 def aten___contains__(mapper, graph, node):
     """ 构造in的PaddleLayer。
 
@@ -3322,6 +3363,64 @@ def aten_neg(mapper, graph, node):
     return current_inputs, current_outputs
 
 
+def aten_norm(mapper, graph, node):
+    """ 构造计算范数的PaddleLayer。
+
+    TorchScript示例:
+        %25 = aten::norm(%input, %21, %58, %24)
+        参数含义:
+        %25 (Tensor): 取范数后的结果。
+        %input (Tensor): 输入。
+        %21 (int): 范数的种类。
+        %58 (int): 使用范数计算的轴。
+        %24 (bool): 是否在输出的Tensor中保留和输入一样的维度。
+    """
+    scope_name = mapper.normalize_scope_name(node)
+    output_name = mapper._get_outputs_name(node)[0]
+    layer_outputs = [output_name]
+    layer_inputs = {}
+    layer_attrs = {}
+    inputs_name, inputs_node = mapper._get_inputs_name(node)
+    # 获取当前节点输出的list
+    current_outputs = [output_name]
+    # 处理输入0，即%input
+    mapper._check_input(graph, inputs_node[0], inputs_name[0], current_outputs, scope_name)
+    layer_inputs["x"] = inputs_name[0]
+    current_inputs = list(layer_inputs.values())
+    # 处理输入1，即%21
+    if inputs_name[1] in mapper.attrs:
+        layer_attrs["p"] = mapper.attrs[inputs_name[1]]
+    else:
+        mapper._check_input(graph, inputs_node[1], inputs_name[1],
+                            current_outputs, scope_name)
+        layer_inputs["p"] = inputs_name[1]
+        current_inputs.append(inputs_name[1])
+    # 处理输入2，即%58
+    if inputs_name[1] in mapper.attrs:
+        layer_attrs["axis"] = mapper.attrs[inputs_name[2]]
+    else:
+        mapper._check_input(graph, inputs_node[2], inputs_name[2],
+                            current_outputs, scope_name)
+        layer_inputs["axis"] = inputs_name[2]
+        current_inputs.append(inputs_name[2])
+    # 处理输入3，即%24
+    if inputs_name[1] in mapper.attrs:
+        layer_attrs["keepdim"] = mapper.attrs[inputs_name[3]]
+    else:
+        mapper._check_input(graph, inputs_node[3], inputs_name[3],
+                            current_outputs, scope_name)
+        layer_inputs["keepdim"] = inputs_name[3]
+        current_inputs.append(inputs_name[3])
+
+    graph.add_layer(
+        "paddle.norm",
+        inputs=layer_inputs,
+        outputs=layer_outputs,
+        scope_name=scope_name,
+        **layer_attrs)
+    return current_inputs, current_outputs
+
+
 def aten___not__(mapper, graph, node):
     """ 构造对bool型取负的PaddleLayer。
 

x2paddle/op_mapper/dygraph/pytorch2paddle/prim.py

@@ -59,8 +59,17 @@ def prim_Constant(mapper, graph, node):
                     scope_name=scope_name)
                 return [], [output_name]
             else:
-                mapper.pytorch_params[output_name] = tensor_value.cpu().detach().numpy()
-
+#                 mapper.pytorch_params[output_name] = tensor_value.cpu().detach().numpy()
+                mapper.paddle_params[output_name] = tensor_value.cpu().detach().numpy()
+                graph.add_layer(
+                        "self.create_parameter",
+                        inputs={},
+                        outputs=[output_name],
+                        scope_name=scope_name,
+                        dtype=string(str(mapper.paddle_params[output_name].dtype)),
+                        shape = mapper.paddle_params[output_name].shape,
+                        default_initializer="paddle.nn.initializer.Constant(value=0.0)")
+                return [], [output_name]
     if "inf" in str(value):
         t = str(type(value)).split("'")[1]
         if str(value).startswith("-"):