From ff5cdb1af2d4720e185031636a03200e817c52b1 Mon Sep 17 00:00:00 2001 From: SunAhong1993 Date: Tue, 15 Dec 2020 12:04:54 +0800 Subject: [PATCH] fix --- .../dygraph/onnx2paddle/opset9/opset.py | 51 ++++++------------- .../static/onnx2paddle/opset9/__init__.py | 1 - .../static/onnx2paddle/opset9/opset.py | 20 +++----- 3 files changed, 24 insertions(+), 48 deletions(-) diff --git a/x2paddle/op_mapper/dygraph/onnx2paddle/opset9/opset.py b/x2paddle/op_mapper/dygraph/onnx2paddle/opset9/opset.py index 3889083..f0b51d4 100644 --- a/x2paddle/op_mapper/dygraph/onnx2paddle/opset9/opset.py +++ b/x2paddle/op_mapper/dygraph/onnx2paddle/opset9/opset.py @@ -1588,9 +1588,6 @@ class OpSet9(): @print_mapping_info def ConvTranspose(self, node): - op_name = name_generator("conv", self.nn_name2id) - output_name = node.name - layer_outputs = [op_name, output_name] val_x = self.graph.get_input_node(node, idx=0, copy=True) val_w = self.graph.get_input_node(node, idx=1, copy=True) val_b = None @@ -1604,7 +1601,7 @@ class OpSet9(): assert 2 <= convnd <= 3, 'only Conv2DTranspose and Conv3DTranspose supported' num_in_channels = val_w.out_shapes[0][0] num_out_channels = val_w.out_shapes[0][1] - paddle_op = 'paddle.nn.Conv{}DTranspose'.format(convnd) + paddle_op = 'paddle.nn.functional.conv{}d_transpose'.format(convnd) num_groups = node.get_attr('group', 1) strides = node.get_attr('strides', [1] * convnd) @@ -1622,37 +1619,21 @@ class OpSet9(): output_size[1] = (val_x.out_shapes[0][3] - 1 ) * strides[1] - 2 * paddings[1] + dilations[1] * ( kernel_shape[1] - 1) + 1 + out_padding[1] + # Conv2DTranspose缺少output_size，只能在forward里头传进output_size + inputs_dict = {'x': val_x if isinstance(val_x, str) else val_x.name, + "weight": val_w.name} layer_attrs = { - 'in_channels': num_in_channels, - 'out_channels': num_out_channels, - 'output_size': output_size or None, - 'kernel_size': kernel_shape, - 'padding': paddings, - 'stride': strides, - 'dilation': dilations, - 'groups': num_groups, - 'weight_attr': string(val_w.name), - 'bias_attr': None if val_b is None else string(val_b.name), - } + "stride": strides, + "dilation": dilations, + "padding": paddings, + "groups": num_groups, + "output_size": node.out_shapes[0][2:]} + if val_b is not None: + inputs_dict["bias"] = val_b.name + else: + layer_attrs["bias"] = None self.paddle_graph.add_layer( - paddle_op, - inputs={"x": val_x.name}, - outputs=layer_outputs, + kernel="paddle.nn.functional.conv2d_transpose", + inputs=inputs_dict, + outputs=[node.name], **layer_attrs) -# inputs_dict = {'x': val_x if isinstance(val_x, str) else val_x.name, -# "weight": val_w.name} -# layer_attrs = { -# "stride": strides, -# "dilation": dilations, -# "padding": paddings, -# "groups": num_groups, -# "output_size": node.out_shapes[0][2:]} -# if val_b is not None: -# inputs_dict["bias"] = val_b.name -# else: -# layer_attrs["bias"] = None -# self.paddle_graph.add_layer( -# kernel="paddle.nn.functional.conv2d_transpose", -# inputs=inputs_dict, -# outputs=[node.name], -# **layer_attrs) diff --git a/x2paddle/op_mapper/static/onnx2paddle/opset9/__init__.py b/x2paddle/op_mapper/static/onnx2paddle/opset9/__init__.py index 8563f99..0092e6e 100644 --- a/x2paddle/op_mapper/static/onnx2paddle/opset9/__init__.py +++ b/x2paddle/op_mapper/static/onnx2paddle/opset9/__init__.py @@ -1,2 +1 @@ from .opset import OpSet9 -from .custom_layer import custom_layers diff --git a/x2paddle/op_mapper/static/onnx2paddle/opset9/opset.py b/x2paddle/op_mapper/static/onnx2paddle/opset9/opset.py index a941dfe..53c2870 100644 --- a/x2paddle/op_mapper/static/onnx2paddle/opset9/opset.py +++ b/x2paddle/op_mapper/static/onnx2paddle/opset9/opset.py @@ -17,7 +17,6 @@ from x2paddle.core.graph import GraphNode from x2paddle.core.fluid_code import Layer from x2paddle.core.fluid_code import FluidCode from x2paddle.core.util import string -from x2paddle.op_mapper.static.onnx2paddle.opset9.custom_layer import * from functools import reduce import numpy as np import onnx @@ -508,33 +507,30 @@ class OpSet9(): @print_mapping_info def InstanceNormalization(self, node): - op_name = name_generator("instanse_norm", self.nn_name2id) - output_name = node.name - layer_outputs = [op_name, output_name] val_x = self.graph.get_input_node(node, idx=0, copy=True) val_scale = self.graph.get_input_node(node, idx=1, copy=True) val_b = self.graph.get_input_node(node, idx=2, copy=True) epsilon = node.get_attr('epsilon', 1e-5) layer_attrs = { - 'epsilon': epsilon, + 'eps': epsilon, } dim = len(val_x.out_shapes[0]) if dim ==2 : - layer_attrs["data_format"] = "NC" + layer_attrs["data_format"] = string("NC") elif dim == 3: - layer_attrs["data_format"] = "NCL" + layer_attrs["data_format"] = string("NCL") elif dim == 4: - layer_attrs["data_format"] = "NCHW" + layer_attrs["data_format"] = string("NCHW") elif dim == 5: - layer_attrs["data_format"] = "NCDHW" + layer_attrs["data_format"] = string("NCDHW") else: raise Exception("The paddle only support 2D, 3D, 4D or 5D input in InstanceNormalization.") self.paddle_graph.add_layer( - paddle_op, + "paddle.nn.functional.instance_norm", inputs={"x": val_x.name, "weight": val_scale.name, "bias": val_b.name}, - outputs=layer_outputs, + outputs=[node.name], **layer_attrs) @print_mapping_info @@ -1577,7 +1573,7 @@ class OpSet9(): if val_b is not None: layer_inputs["bias"] = val_b.name self.paddle_graph.add_layer( - kernel="paddle.nn.functional.conv2d_transpose", + kernel=paddle_op, inputs=layer_inputs, outputs=[node.name], **layer_attrs) \ No newline at end of file -- GitLab