diff --git a/x2paddle/op_mapper/pytorch2paddle/aten.py b/x2paddle/op_mapper/pytorch2paddle/aten.py index 28bef458d6b4f8cee325b0e6da037058f9248b7f..683dbad39591a8dc1f3658e46be730b3f0da2b15 100755 --- a/x2paddle/op_mapper/pytorch2paddle/aten.py +++ b/x2paddle/op_mapper/pytorch2paddle/aten.py @@ -1311,12 +1311,16 @@ def aten__convolution(mapper, graph, node): %12 (int): 卷积的组数。 """ scope_name = mapper.normalize_scope_name(node) - op_name = name_generator("conv2d", mapper.nn_name2id) + inputs_name, inputs_node = mapper._get_inputs_name(node) + weights = mapper.pytorch_params[inputs_name[1]] + if len(weights.shape) == 3: + op_name = name_generator("conv1d", mapper.nn_name2id) + else: + op_name = name_generator("conv2d", mapper.nn_name2id) output_name = mapper._get_outputs_name(node)[0] layer_outputs = [op_name, 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.8 @@ -1326,7 +1330,6 @@ def aten__convolution(mapper, graph, node): # 获取当前节点输入的list current_inputs = list(layer_inputs.values()) # 处理输入1，即%18 - weights = mapper.pytorch_params[inputs_name[1]] mapper.paddle_params[op_name + ".weight"] = weights #np.swapaxes(weights, 0, 1) if mapper.attrs[inputs_name[6]]: @@ -1361,20 +1364,36 @@ def aten__convolution(mapper, graph, node): else: layer_attrs['in_channels'] = weights.shape[1] * mapper.attrs[ inputs_name[8]] - if mapper.attrs[inputs_name[6]]: - graph.add_layer( - "paddle.nn.Conv2DTranspose", - inputs=layer_inputs, - outputs=layer_outputs, - scope_name=scope_name, - **layer_attrs) + if len(weights.shape) == 4: + if mapper.attrs[inputs_name[6]]: + graph.add_layer( + "paddle.nn.Conv2DTranspose", + inputs=layer_inputs, + outputs=layer_outputs, + scope_name=scope_name, + **layer_attrs) + else: + graph.add_layer( + "paddle.nn.Conv2D", + inputs=layer_inputs, + outputs=layer_outputs, + scope_name=scope_name, + **layer_attrs) else: - graph.add_layer( - "paddle.nn.Conv2D", - inputs=layer_inputs, - outputs=layer_outputs, - scope_name=scope_name, - **layer_attrs) + if mapper.attrs[inputs_name[6]]: + graph.add_layer( + "paddle.nn.Conv1DTranspose", + inputs=layer_inputs, + outputs=layer_outputs, + scope_name=scope_name, + **layer_attrs) + else: + graph.add_layer( + "paddle.nn.Conv1D", + inputs=layer_inputs, + outputs=layer_outputs, + scope_name=scope_name, + **layer_attrs) return current_inputs, current_outputs @@ -1610,7 +1629,7 @@ def aten_dim(mapper, graph, node): def aten_div(mapper, graph, node): """ 构造除法的PaddleLayer。 TorchScript示例: - %bx_bw0.3 : Tensor = aten::div_(%bx_bw.3, %2678) + %bx_bw0.3 : Tensor = aten::div(%bx_bw.3, %2678) 参数含义: %bx_bw0.3 (-): 除后的结果。 %bx_bw.3 (-): 被除数。 @@ -3341,6 +3360,52 @@ def aten_max(mapper, graph, node): return current_inputs, current_outputs +def aten_max_pool1d(mapper, graph, node): + """ 构造最大池化的PaddleLayer。 + TorchScript示例: + %input.8 : Tensor = aten::max_pool1d(%result.11, %20, %23, %21, %22, %19) + 参数含义: + %input.8 (Tensor): 输出，池化后的结果。 + %result.11 (Tensor): 需要池化的Tensor。 + %20 (list): 池化kernel的大小。 + %23 (list): 步长大小。 + %21 (list): 填充大小。 + %22 (list): 膨胀系数大小。 + %19 (bool): 是否用ceil函数计算输出高度和宽度。 + """ + scope_name = mapper.normalize_scope_name(node) + op_name = name_generator("pool1d", mapper.nn_name2id) + output_name = mapper._get_outputs_name(node)[0] + layer_outputs = [op_name, 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%result.11 + mapper._check_input(graph, inputs_node[0], inputs_name[0], current_outputs, + scope_name) + layer_inputs["input"] = inputs_name[0] + # 获取当前节点输入的list + current_inputs = list(layer_inputs.values()) + # 处理输入1，即%20 + layer_attrs["kernel_size"] = mapper.attrs[inputs_name[1]] + # 处理输入2，即%23 + layer_attrs["stride"] = mapper.attrs[inputs_name[2]] + # 处理输入3，即%21 + layer_attrs["padding"] = mapper.attrs[inputs_name[3]] + # 处理输入5，即%19 + layer_attrs["ceil_mode"] = mapper.attrs[inputs_name[5]] + + graph.add_layer( + "paddle.nn.MaxPool1D", + inputs=layer_inputs, + outputs=layer_outputs, + scope_name=scope_name, + **layer_attrs) + return current_inputs, current_outputs + + def aten_max_pool2d(mapper, graph, node): """ 构造最大池化的PaddleLayer。 TorchScript示例: @@ -3656,6 +3721,56 @@ def aten_neg(mapper, graph, node): return current_inputs, current_outputs +def aten_frobenius_norm(mapper, graph, node): + """ 构造计算范数的PaddleLayer。 + TorchScript示例: + %25 = aten::frobenius_norm(%input, %58, %24) + 参数含义: + %25 (Tensor): 取范数后的结果。 + %input (Tensor): 输入。 + %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()) + layer_attrs["p"] = 2 + # 处理输入1，即%58 + if inputs_name[1] in mapper.attrs: + layer_attrs["axis"] = mapper.attrs[inputs_name[1]] + else: + mapper._check_input(graph, inputs_node[1], inputs_name[1], + current_outputs, scope_name) + layer_inputs["axis"] = inputs_name[1] + current_inputs.append(inputs_name[1]) + # 处理输入2，即%24 + if inputs_name[1] in mapper.attrs: + layer_attrs["keepdim"] = mapper.attrs[inputs_name[2]] + else: + mapper._check_input(graph, inputs_node[2], inputs_name[2], + current_outputs, scope_name) + layer_inputs["keepdim"] = inputs_name[2] + current_inputs.append(inputs_name[2]) + + graph.add_layer( + "paddle.norm", + inputs=layer_inputs, + outputs=layer_outputs, + scope_name=scope_name, + **layer_attrs) + return current_inputs, current_outputs + + def aten_norm(mapper, graph, node): """ 构造计算范数的PaddleLayer。 TorchScript示例: @@ -4168,6 +4283,76 @@ def aten_repeat(mapper, graph, node): return current_inputs, current_outputs +def aten_repeat_interleave(mapper, graph, node): + """ 构造根据参数对输入各维度进行复制的PaddleLayer。 + TorchScript示例: + %701 : Tensor = aten::repeat(%699, %700, %702) + 参数含义: + %701 (Tensor): 输出，复制后的Tensor。 + %699 (Tensor): 需要复制的Tensor。 + %700 (int | Tensor): 指定每个维度复制的次数。 + %702 (int): 指定在哪个轴上进行复制。 + """ + 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%699 + 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%700 + if inputs_name[1] in mapper.attrs: + layer_attrs["repeat_times"] = [int(mapper.attrs[inputs_name[1]])] + else: + mapper._check_input(graph, inputs_node[1], inputs_name[1], + current_outputs, scope_name) + layer_inputs["repeat_times"] = inputs_name[1] + current_inputs.append(inputs_name[1]) + + graph.add_layer( + "paddle.tile", + inputs=layer_inputs, + outputs=layer_outputs, + scope_name=scope_name, + **layer_attrs) + + layer_attrs_reshape = {} + layer_attrs_reshape["shape"] = [0, int(mapper.attrs[inputs_name[1]]), -1] + graph.add_layer( + "paddle.reshape", + inputs={"x": layer_outputs[0]}, + outputs=[layer_outputs[0] + "_reshape"], + scope_name=scope_name, + **layer_attrs_reshape) + + layer_attrs_transpose = {} + layer_attrs_transpose["perm"] = [0, 2, 1] + graph.add_layer( + "paddle.transpose", + inputs={"x": layer_outputs[0] + "_reshape"}, + outputs=[layer_outputs[0] + "_transpose"], + scope_name=scope_name, + **layer_attrs_transpose) + + layer_attrs_reshape = {} + layer_attrs_reshape["shape"] = [0, -1] + graph.add_layer( + "paddle.reshape", + inputs={"x": layer_outputs[0] + "_transpose"}, + outputs=layer_outputs, + scope_name=scope_name, + **layer_attrs_reshape) + + return current_inputs, current_outputs + + def aten_reshape(mapper, graph, node): """ 构造调整大小的PaddleLayer。 TorchScript示例: @@ -4973,19 +5158,6 @@ def aten_sub(mapper, graph, node): return current_inputs, current_outputs -def aten_sub_(mapper, graph, node): - """ 构造数值相减的PaddleLayer。 - TorchScript示例: - %840 : int = aten::sub_(%839, %836, %3) - 参数含义: - %840 (-): 相减结果。 - %839 (-): 输入数值 x。 - %836 (-): 输入数值 y。 - %3 (-): alpha。 - """ - return aten_sub(mapper, graph, node) - - def aten_t(mapper, graph, node): """ 构造矩阵转置的PaddleLayer。 TorchScript示例: