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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.
- # ============================================================================
-
- import numpy as np
- import pytest
-
- import mindspore.context as context
- import mindspore.nn as nn
- from mindspore import Tensor
- from mindspore.ops import operations as P
-
-
- class NetCheckValid(nn.Cell):
- def __init__(self):
- super(NetCheckValid, self).__init__()
- self.valid = P.CheckValid()
-
- def construct(self, anchor, image_metas):
- return self.valid(anchor, image_metas)
-
- def check_valid(nptype):
- anchor = np.array([[50, 0, 100, 700], [-2, 2, 8, 100], [10, 20, 300, 2000]], nptype)
- image_metas = np.array([768, 1280, 1], nptype)
- anchor_box = Tensor(anchor)
- image_metas_box = Tensor(image_metas)
- expect = np.array([True, False, False], np.bool)
-
- context.set_context(mode=context.GRAPH_MODE, device_target='GPU')
- boundingbox_decode = NetCheckValid()
- output = boundingbox_decode(anchor_box, image_metas_box)
- assert np.array_equal(output.asnumpy(), expect)
-
- context.set_context(mode=context.PYNATIVE_MODE, device_target='GPU')
- boundingbox_decode = NetCheckValid()
- output = boundingbox_decode(anchor_box, image_metas_box)
- assert np.array_equal(output.asnumpy(), expect)
-
- @pytest.mark.level0
- @pytest.mark.platform_x86_gpu_training
- @pytest.mark.env_onecard
- def test_check_valid_float32():
- check_valid(np.float32)
-
- @pytest.mark.level0
- @pytest.mark.platform_x86_gpu_training
- @pytest.mark.env_onecard
- def test_check_valid_float16():
- check_valid(np.float16)
-
- @pytest.mark.level0
- @pytest.mark.platform_x86_gpu_training
- @pytest.mark.env_onecard
- def test_check_valid_int16():
- check_valid(np.int16)
-
- @pytest.mark.level0
- @pytest.mark.platform_x86_gpu_training
- @pytest.mark.env_onecard
- def test_check_valid_uint8():
- anchor = np.array([[5, 0, 10, 70], [2, 2, 8, 10], [1, 2, 30, 200]], np.uint8)
- image_metas = np.array([76, 128, 1], np.uint8)
- anchor_box = Tensor(anchor)
- image_metas_box = Tensor(image_metas)
- expect = np.array([True, True, False], np.bool)
-
- context.set_context(mode=context.GRAPH_MODE, device_target='GPU')
- boundingbox_decode = NetCheckValid()
- output = boundingbox_decode(anchor_box, image_metas_box)
- assert np.array_equal(output.asnumpy(), expect)
-
- context.set_context(mode=context.PYNATIVE_MODE, device_target='GPU')
- boundingbox_decode = NetCheckValid()
- output = boundingbox_decode(anchor_box, image_metas_box)
- assert np.array_equal(output.asnumpy(), expect)
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