#!/usr/bin/env python3 # Copyright (c) 2022 CINN 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 unittest from op_mapper_test import OpMapperTest import paddle class TestConv2dOp(OpMapperTest): def init_input_data(self): self.feed_data = { "x": self.random([3, 16, 32, 32], "float32"), "weight": self.random([16, 16, 3, 3], "float32"), } self.data_format = 'NCHW' def set_op_type(self): return "conv2d" def set_op_inputs(self): x = paddle.static.data( 'x', self.feed_data["x"].shape, self.feed_data["x"].dtype ) weight = paddle.static.data( 'weight', self.feed_data["weight"].shape, self.feed_data["weight"].dtype, ) return {'Input': [x], 'Filter': [weight]} def set_op_attrs(self): return { "strides": [1, 1], "paddings": [0, 0], "dilations": [1, 1], "groups": 1, "data_format": self.data_format, "padding_algorithm": "EXPLICIT", "use_cudnn": True, } def set_op_outputs(self): return {'Output': [str(self.feed_data['x'].dtype)]} def test_check_results(self): self.check_outputs_and_grads() class TestConv2dNCHWFP16(TestConv2dOp): def init_input_data(self): self.feed_data = { "x": self.random([3, 16, 32, 32], "float16"), "weight": self.random([16, 16, 3, 3], "float16"), } self.data_format = 'NCHW' def test_check_results(self): self.check_outputs_and_grads(max_relative_error=1e-3) class TestConv2dNHWC(TestConv2dOp): def init_input_data(self): self.feed_data = { "x": self.random([3, 32, 32, 16], "float32"), "weight": self.random([16, 16, 3, 3], "float32"), } self.data_format = 'NHWC' class TestConv2dNHWCFP16(TestConv2dOp): def init_input_data(self): self.feed_data = { "x": self.random([3, 32, 32, 16], "float16"), "weight": self.random([16, 16, 3, 3], "float16"), } self.data_format = 'NHWC' def test_check_results(self): self.check_outputs_and_grads(max_relative_error=1e-3) if __name__ == "__main__": unittest.main()