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335 lines
17 KiB
335 lines
17 KiB
# Copyright 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.common.dtype as mstype
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import mindspore.context as context
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from mindspore.common.tensor import Tensor
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from mindspore.nn import Cell
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from mindspore.ops import operations as P
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class Net(Cell):
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def __init__(self, dtype):
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super(Net, self).__init__()
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self.Cast = P.Cast()
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self.dtype = dtype
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def construct(self, x):
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return self.Cast(x, self.dtype)
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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_cast_bool():
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tensor_to_cast = []
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.bool)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float64)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int8)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int64)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint8)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint64)))
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t = mstype.bool_
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context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
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for tensor in tensor_to_cast:
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net = Net(t)
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output = net(tensor)
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assert output.asnumpy().dtype == 'bool'
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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_cast_float16():
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tensor_to_cast = []
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.bool)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float64)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int8)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int64)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint8)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint64)))
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t = mstype.float16
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context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
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for tensor in tensor_to_cast:
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net = Net(t)
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output = net(tensor)
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assert output.asnumpy().dtype == 'float16'
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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_cast_float32():
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tensor_to_cast = []
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.bool)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float64)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int8)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int64)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint8)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint64)))
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t = mstype.float32
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context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
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for tensor in tensor_to_cast:
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net = Net(t)
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output = net(tensor)
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assert output.asnumpy().dtype == 'float32'
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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_cast_float64():
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tensor_to_cast = []
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.bool)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float64)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int8)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int64)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint8)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint64)))
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t = mstype.float64
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context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
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for tensor in tensor_to_cast:
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net = Net(t)
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output = net(tensor)
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assert output.asnumpy().dtype == 'float64'
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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_cast_int8():
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tensor_to_cast = []
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.bool)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float64)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int8)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int64)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint8)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint64)))
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t = mstype.int8
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context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
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for tensor in tensor_to_cast:
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net = Net(t)
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output = net(tensor)
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assert output.asnumpy().dtype == 'int8'
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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_cast_int16():
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tensor_to_cast = []
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.bool)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float64)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int8)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int64)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint8)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint64)))
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t = mstype.int16
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context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
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for tensor in tensor_to_cast:
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net = Net(t)
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output = net(tensor)
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assert output.asnumpy().dtype == 'int16'
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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_cast_int32():
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tensor_to_cast = []
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.bool)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float64)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int8)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int64)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint8)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint64)))
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t = mstype.int32
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context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
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for tensor in tensor_to_cast:
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net = Net(t)
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output = net(tensor)
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assert output.asnumpy().dtype == 'int32'
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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_cast_int64():
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tensor_to_cast = []
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.bool)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float64)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int8)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int64)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint8)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint64)))
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t = mstype.int64
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context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
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for tensor in tensor_to_cast:
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net = Net(t)
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output = net(tensor)
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assert output.asnumpy().dtype == 'int64'
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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_cast_uint8():
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tensor_to_cast = []
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.bool)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float64)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int8)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int64)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint8)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint64)))
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t = mstype.uint8
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context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
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for tensor in tensor_to_cast:
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net = Net(t)
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output = net(tensor)
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assert output.asnumpy().dtype == 'uint8'
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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_cast_uint16():
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tensor_to_cast = []
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.bool)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float64)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int8)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int64)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint8)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint64)))
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t = mstype.uint16
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context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
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for tensor in tensor_to_cast:
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net = Net(t)
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output = net(tensor)
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assert output.asnumpy().dtype == 'uint16'
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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_cast_uint32():
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tensor_to_cast = []
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.bool)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float64)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int8)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int64)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint8)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint64)))
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t = mstype.uint32
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context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
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for tensor in tensor_to_cast:
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net = Net(t)
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output = net(tensor)
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assert output.asnumpy().dtype == 'uint32'
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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_cast_uint64():
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tensor_to_cast = []
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.bool)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float16)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float32)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float64)))
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int8)))
|
|
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int16)))
|
|
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int32)))
|
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int64)))
|
|
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint8)))
|
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint16)))
|
|
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint32)))
|
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tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint64)))
|
|
t = mstype.uint64
|
|
|
|
context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
|
|
for tensor in tensor_to_cast:
|
|
net = Net(t)
|
|
output = net(tensor)
|
|
assert output.asnumpy().dtype == 'uint64'
|