forked from huawei/mindspore2022
114 lines
3.7 KiB
Python
114 lines
3.7 KiB
Python
# Copyright 2021 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
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import mindspore.context as context
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import mindspore.nn as nn
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from mindspore import Tensor
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class TensorArrayNet(nn.Cell):
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def __init__(self, dtype, element_shape, is_dynamic_shape=True, size=0):
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super(TensorArrayNet, self).__init__()
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self.ta = nn.TensorArray(dtype, element_shape, is_dynamic_shape, size)
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def construct(self, index, value):
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self.ta.write(index, value)
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v = self.ta.read(index)
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s = self.ta.stack()
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self.ta.close()
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return v, s
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_tensorarray():
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"""
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Feature: TensorArray gpu TEST.
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Description: Test the function write, read, stack, clear, close in both graph and pynative mode.
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Expectation: success.
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"""
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context.set_context(mode=context.GRAPH_MODE, device_target="CPU")
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index = Tensor(0, mindspore.int64)
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value = Tensor(5, mindspore.int64)
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ta = TensorArrayNet(dtype=mindspore.int64, element_shape=())
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v, s = ta(index, value)
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expect_v = 5
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expect_s = [5]
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assert np.allclose(s.asnumpy(), expect_s)
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assert np.allclose(v.asnumpy(), expect_v)
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context.set_context(mode=context.PYNATIVE_MODE, device_target="CPU")
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ta = nn.TensorArray(mindspore.int64, ())
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for i in range(5):
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ta.write(i, 99)
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v = ta.read(0)
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s = ta.stack()
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expect_v = 99
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expect_s = [99, 99, 99, 99, 99]
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assert np.allclose(s.asnumpy(), expect_s)
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assert np.allclose(v.asnumpy(), expect_v)
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ta_size = ta.size()
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assert np.allclose(ta_size.asnumpy(), 5)
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ta.clear()
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ta_size = ta.size()
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assert np.allclose(ta_size.asnumpy(), 0)
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ta.write(0, 88)
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v = ta.read(0)
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s = ta.stack()
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ta.close()
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expect_v = 88
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expect_s = [88]
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assert np.allclose(s.asnumpy(), expect_s)
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assert np.allclose(v.asnumpy(), expect_v)
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ta = nn.TensorArray(mindspore.float32, ())
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ta.write(5, 1.)
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s = ta.stack()
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expect_s = [0., 0., 0., 0., 0., 1.]
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assert np.allclose(s.asnumpy(), expect_s)
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ta.write(2, 1.)
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s = ta.stack()
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expect_s = [0., 0., 1., 0., 0., 1.]
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assert np.allclose(s.asnumpy(), expect_s)
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ta.close()
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ta = nn.TensorArray(mindspore.bool_, ())
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ta.write(1, Tensor(True, mindspore.bool_))
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s = ta.stack()
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v = ta.read(1)
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expect_s = [False, True]
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assert np.allclose(v.asnumpy(), expect_s[1])
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assert np.allclose(s.asnumpy(), expect_s)
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ta.close()
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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_static_tensorarray():
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"""
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Feature: TensorArray cpu TEST.
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Description: Test the static tensorarray.
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Expectation: success.
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"""
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context.set_context(mode=context.GRAPH_MODE, device_target="CPU")
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index = Tensor(0, mindspore.int64)
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value = Tensor(5, mindspore.int64)
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ta = TensorArrayNet(dtype=mindspore.int64, element_shape=(), is_dynamic_shape=False, size=12)
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v, s = ta(index, value)
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expect_v = 5
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expect_s = [5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
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assert np.allclose(s.asnumpy(), expect_s)
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assert np.allclose(v.asnumpy(), expect_v)
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