# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License" # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import math import sys import x2paddle import os import numpy as np import paddle.fluid.core as core import paddle.fluid as fluid import onnx from onnx import helper, onnx_pb from x2paddle.op_mapper.paddle2onnx.opset9.opset import OpSet9 class OpSet10(OpSet9): def __init__(self): super(OpSet10, self).__init__() def slice(self, op, block): axes = op.attr('axes') starts = op.attr('starts') ends = op.attr('ends') axes_name = self.get_name(op.type, 'axes') starts_name = self.get_name(op.type, 'starts') ends_name = self.get_name(op.type, 'ends') axes_node = self.make_constant_node(axes_name, onnx_pb.TensorProto.INT64, axes) starts_node = self.make_constant_node(starts_name, onnx_pb.TensorProto.INT64, starts) ends_node = self.make_constant_node(ends_name, onnx_pb.TensorProto.INT64, ends) node = helper.make_node( "Slice", inputs=[op.input('Input')[0], starts_name, ends_name, axes_name], outputs=op.output('Out'), ) return [starts_node, ends_node, axes_node, node] def im2sequence(self, op, block): from .paddle_custom_layer.im2sequence import im2sequence return im2sequence(op, block) def yolo_box(self, op, block): from .paddle_custom_layer.yolo_box import yolo_box return yolo_box(op, block) def multiclass_nms(self, op, block): from .paddle_custom_layer.multiclass_nms import multiclass_nms return multiclass_nms(op, block)