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- /**
- * Copyright 2020 Huawei Technologies Co., Ltd
- *
- * 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.
- */
-
- #include <vector>
- #include "common/common_test.h"
- #include "common/trans.h"
- #include "utils/utils.h"
-
- using namespace std;
- namespace mindspore {
- namespace trans {
- class FormatTransTest : public UT::Common {
- public:
- FormatTransTest() = default;
- void SetUp() override {}
- void TearDown() override {}
- };
-
- TEST_F(FormatTransTest, nchw_to_hwcn) {
- uint16_t data[2*2*2*2] = {12581,14220,14937,14302,
- 15004,14951,14694,14564,
- 14069,14554,10507,14787,
- 13016,15263,14872,10838};
- uint16_t res[2*2*2*2] = {12581,14069,15004,13016,
- 14220,14554,14951,15263,
- 14937,10507,14694,14872,
- 14302,14787,14564,10838};
- size_t device_size = 32;
- auto trans_tmp = std::vector<uint8_t>(device_size);
- FormatArgs format_args{data, device_size, kOpFormat_NCHW, kOpFormat_HWCN,
- {2, 2, 2, 2}, {2, 2, 2, 2}, kNumberTypeFloat16};
- EXPECT_EQ(trans::TransFormat(format_args, trans_tmp.data()), true);
- for (size_t i = 0; i < sizeof(res) / sizeof(res[0]); i++) {
- EXPECT_EQ((reinterpret_cast<uint16_t *>(trans_tmp.data()))[i], res[i]);
- }
- }
-
- TEST_F(FormatTransTest, hwcn_to_nchw) {
- uint16_t data[2*2*2*2] = {12581,14069,15004,13016,
- 14220,14554,14951,15263,
- 14937,10507,14694,14872,
- 14302,14787,14564,10838};
-
- uint16_t res[2*2*2*2] = {12581,14220,14937,14302,
- 15004,14951,14694,14564,
- 14069,14554,10507,14787,
- 13016,15263,14872,10838};
-
- size_t device_size = 32;
- auto trans_tmp = std::vector<uint8_t>(device_size);
- FormatArgs format_args{data, device_size, kOpFormat_NCHW, kOpFormat_HWCN,
- {2, 2, 2, 2}, {2, 2, 2, 2}, kNumberTypeFloat16};
- EXPECT_EQ(trans::TransFormatFromDeviceToHost(format_args, trans_tmp.data()), true);
- for (size_t i = 0; i < sizeof(res) / sizeof(res[0]); i++) {
- EXPECT_EQ((reinterpret_cast<uint16_t *>(trans_tmp.data()))[i], res[i]);
- }
- }
-
- TEST_F(FormatTransTest, nchw_to_nhwc) {
- uint16_t data[2*2*2*2] = {11750,13778,15007,15321,
- 15163,13446,15063,14467,
- 15056,13284,15219,14797,
- 12684,14288,14855,14799};
- uint16_t res[2*2*2*2] = {11750,15163,13778,13446,
- 15007,15063,15321,14467,
- 15056,12684,13284,14288,
- 15219,14855,14797,14799};
- size_t device_size = 32;
- auto trans_tmp = std::vector<uint8_t>(device_size);
- FormatArgs format_args{data, device_size, kOpFormat_NCHW, kOpFormat_NHWC,
- {2, 2, 2, 2}, {2, 2, 2, 2}, kNumberTypeFloat16};
- EXPECT_EQ(trans::TransFormat(format_args, trans_tmp.data()), true);
- for (size_t i = 0; i < sizeof(res) / sizeof(res[0]); i++) {
- EXPECT_EQ((reinterpret_cast<uint16_t *>(trans_tmp.data()))[i], res[i]);
- }
- }
- TEST_F(FormatTransTest, nhwc_to_nchw) {
- uint16_t data[2*2*2*2] = {11750,15163,13778,13446,
- 15007,15063,15321,14467,
- 15056,12684,13284,14288,
- 15219,14855,14797,14799};
- uint16_t res[2*2*2*2] = {11750,13778,15007,15321,
- 15163,13446,15063,14467,
- 15056,13284,15219,14797,
- 12684,14288,14855,14799};
-
- size_t device_size = 32;
- auto trans_tmp = std::vector<uint8_t>(device_size);
- FormatArgs format_args{data, device_size, kOpFormat_NCHW, kOpFormat_NHWC,
- {2, 2, 2, 2}, {2, 2, 2, 2}, kNumberTypeFloat16};
- EXPECT_EQ(trans::TransFormatFromDeviceToHost(format_args, trans_tmp.data()), true);
- for (size_t i = 0; i < sizeof(res) / sizeof(res[0]); i++) {
- EXPECT_EQ((reinterpret_cast<uint16_t *>(trans_tmp.data()))[i], res[i]);
- }
- }
- } // namespace trans
- } // namespace mindspore
-
-
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