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138 lines
4.9 KiB
138 lines
4.9 KiB
# Copyright 2019-2020 Huawei Technologies Co., Ltd
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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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# ============================================================================
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import numpy as np
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import pytest
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import mindspore.context as context
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import mindspore.nn as nn
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import mindspore as ms
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from mindspore import Tensor
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from mindspore.ops import operations as P
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class GatherNet(nn.Cell):
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def __init__(self, dim=0):
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super(GatherNet, self).__init__()
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self.gather = P.GatherD()
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self.dim = dim
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def construct(self, x, index):
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return self.gather(x, self.dim, index)
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_gather_pynative_fp32_int32():
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context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
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error = 1e-3
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x = Tensor(np.array([[1.303, 2.333], [3.232, 4.235]]), ms.float32)
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dim = 1
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index = Tensor(np.array([[0, 0], [1, 0]]), ms.int32)
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expect = np.array([[1.303, 1.303], [4.235, 3.232]], np.float32)
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output = P.GatherD()(x, dim, index)
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diff = output.asnumpy() - expect
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assert np.all(diff < error)
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_gather_pynative_fp32_int64():
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context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
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error = 1e-3
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x = Tensor(np.array([[1.303, 2.333], [3.232, 4.235]]), ms.float32)
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dim = 1
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index = Tensor(np.array([[0, 0], [1, 0]]), ms.int64)
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expect = np.array([[1.303, 1.303], [4.235, 3.232]], np.float32)
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output = P.GatherD()(x, dim, index)
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diff = output.asnumpy() - expect
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assert np.all(diff < error)
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_gather_pynative_fp16_int32():
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context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
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error = 1e-3
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x = Tensor(np.array([[1.303, 2.333], [3.232, 4.235]]), ms.float16)
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dim = 1
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index = Tensor(np.array([[0, 0], [1, 0]]), ms.int32)
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expect = np.array([[1.303, 1.303], [4.235, 3.232]], np.float16)
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output = P.GatherD()(x, dim, index)
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diff = output.asnumpy() - expect
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assert np.all(diff < error)
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_gather_pynative_fp16_int64():
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context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
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error = 1e-3
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x = Tensor(np.array([[1.303, 2.333], [3.232, 4.235]]), ms.float16)
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dim = 1
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index = Tensor(np.array([[0, 0], [1, 0]]), ms.int64)
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expect = np.array([[1.303, 1.303], [4.235, 3.232]], np.float16)
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output = P.GatherD()(x, dim, index)
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diff = output.asnumpy() - expect
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assert np.all(diff < error)
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def test_gather_graph_fp32_int32():
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context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
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error = 1e-3
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x = Tensor(np.array([[1.303, 2.333], [3.232, 4.235]]), ms.float32)
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dim = 1
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index = Tensor(np.array([[0, 0], [1, 0]]), ms.int32)
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expect = np.array([[1.303, 1.303], [4.235, 3.232]], np.float32)
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gather = GatherNet(dim)
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output = gather(x, index)
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diff = output.asnumpy() - expect
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assert np.all(diff < error)
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def test_gather_graph_fp32_int64():
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context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
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error = 1e-3
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x = Tensor(np.array([[1.303, 2.333], [3.232, 4.235]]), ms.float32)
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dim = 1
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index = Tensor(np.array([[0, 0], [1, 0]]), ms.int64)
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expect = np.array([[1.303, 1.303], [4.235, 3.232]], np.float32)
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gather = GatherNet(dim)
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output = gather(x, index)
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diff = output.asnumpy() - expect
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assert np.all(diff < error)
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def test_gather_graph_fp16_int32():
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context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
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error = 1e-3
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x = Tensor(np.array([[1.303, 2.333], [3.232, 4.235]]), ms.float16)
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dim = 1
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index = Tensor(np.array([[0, 0], [1, 0]]), ms.int32)
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expect = np.array([[1.303, 1.303], [4.235, 3.232]], np.float16)
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gather = GatherNet(dim)
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output = gather(x, index)
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diff = output.asnumpy() - expect
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assert np.all(diff < error)
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def test_gather_graph_fp16_int64():
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context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
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error = 1e-3
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x = Tensor(np.array([[1.303, 2.333], [3.232, 4.235]]), ms.float16)
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dim = 1
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index = Tensor(np.array([[0, 0], [1, 0]]), ms.int64)
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expect = np.array([[1.303, 1.303], [4.235, 3.232]], np.float16)
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gather = GatherNet(dim)
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output = gather(x, index)
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diff = output.asnumpy() - expect
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assert np.all(diff < error)
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