wehub-resource-sync
154 lines
4.8 KiB
Python
154 lines
4.8 KiB
Python
# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import unittest
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import numpy as np
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from op_test import is_custom_device
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import paddle
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from paddle import to_tensor
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from paddle.nn import ZeroPad3D, ZeroPad3d
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class TestZeroPad3DAPI(unittest.TestCase):
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def setUp(self):
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if paddle.is_compiled_with_cuda() or is_custom_device():
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paddle.device.set_device('gpu:0')
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else:
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paddle.device.set_device('cpu')
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self.shape = [4, 3, 6, 6, 6]
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self.support_dtypes = ['float32', 'float64', 'int32', 'int64']
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def test_support_dtypes(self):
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for dtype in self.support_dtypes:
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pad = 2
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x = np.random.randint(-255, 255, size=self.shape).astype(dtype)
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expect_res = np.pad(
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x,
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[[0, 0], [0, 0], [pad, pad], [pad, pad], [pad, pad]],
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mode='constant',
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constant_values=0,
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)
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x_tensor = to_tensor(x).astype(dtype)
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zeropad3d = ZeroPad3D(padding=pad)
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ret_res = zeropad3d(x_tensor).numpy()
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np.testing.assert_allclose(expect_res, ret_res, rtol=1e-05)
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def test_support_pad2(self):
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pad = [1, 2, 3, 4, 5, 6]
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x = np.random.randint(-255, 255, size=self.shape)
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expect_res = np.pad(
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x,
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[
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[0, 0],
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[0, 0],
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[pad[4], pad[5]],
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[pad[2], pad[3]],
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[pad[0], pad[1]],
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],
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mode='constant',
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constant_values=0,
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)
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x_tensor = to_tensor(x)
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zeropad3d = ZeroPad3D(padding=pad)
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ret_res = zeropad3d(x_tensor).numpy()
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np.testing.assert_allclose(expect_res, ret_res, rtol=1e-05)
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def test_support_pad3(self):
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pad = (1, 2, 3, 4, 5, 6)
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x = np.random.randint(-255, 255, size=self.shape)
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expect_res = np.pad(
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x,
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[
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[0, 0],
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[0, 0],
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[pad[4], pad[5]],
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[pad[2], pad[3]],
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[pad[0], pad[1]],
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],
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)
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x_tensor = to_tensor(x)
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zeropad3d = ZeroPad3D(padding=pad)
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ret_res = zeropad3d(x_tensor).numpy()
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np.testing.assert_allclose(expect_res, ret_res, rtol=1e-05)
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def test_support_pad4(self):
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pad = [1, 2, 3, 4, 5, 6]
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x = np.random.randint(-255, 255, size=self.shape)
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expect_res = np.pad(
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x,
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[
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[0, 0],
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[0, 0],
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[pad[4], pad[5]],
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[pad[2], pad[3]],
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[pad[0], pad[1]],
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],
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)
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x_tensor = to_tensor(x)
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pad_tensor = to_tensor(pad, dtype='int32')
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zeropad3d = ZeroPad3D(padding=pad_tensor)
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ret_res = zeropad3d(x_tensor).numpy()
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np.testing.assert_allclose(expect_res, ret_res, rtol=1e-05)
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def test_repr(self):
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pad = pad = [1, 2, 3, 4, 5, 6]
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zeropad3d = ZeroPad3D(padding=pad)
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name_str = zeropad3d.extra_repr()
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assert (
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name_str
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== 'padding=[1, 2, 3, 4, 5, 6], mode=constant, value=0.0, data_format=NCDHW'
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)
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def test_compatibility(self):
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pad = [1, 2, 3, 4, 5, 6]
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x = np.random.randint(-255, 255, size=self.shape)
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expect_res = np.pad(
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x,
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[
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[0, 0],
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[0, 0],
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[pad[4], pad[5]],
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[pad[2], pad[3]],
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[pad[0], pad[1]],
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],
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)
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x_tensor = to_tensor(x)
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pad_tensor = to_tensor(pad, dtype='int32')
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# test func alias
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zeropad3d = ZeroPad3d(padding=pad_tensor)
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ret_res = zeropad3d(x_tensor).numpy()
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np.testing.assert_allclose(expect_res, ret_res, rtol=1e-05)
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# test @param_one_alias(["x", "input"])
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ret_res = zeropad3d(input=x_tensor).numpy()
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np.testing.assert_allclose(expect_res, ret_res, rtol=1e-05)
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# test padding attribute
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zeropad3d = ZeroPad3D(
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padding=to_tensor([1, 1, 1, 1, 1, 1], dtype='int32')
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)
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zeropad3d.padding = pad_tensor
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ret_res = zeropad3d(x_tensor).numpy()
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np.testing.assert_allclose(expect_res, ret_res, rtol=1e-05)
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if __name__ == '__main__':
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unittest.main()
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