mindspore/tests/st/ops/cpu/test_cast_op.py

# 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.common.dtype as mstype
import mindspore.context as context
from mindspore.common.tensor import Tensor
from mindspore.nn import Cell
from mindspore.ops import operations as P


class Net(Cell):
    def __init__(self, dtype):
        super(Net, self).__init__()
        self.Cast = P.Cast()
        self.dtype = dtype

    def construct(self, x):
        return self.Cast(x, self.dtype)


@pytest.mark.level0
@pytest.mark.platform_x86_cpu
@pytest.mark.env_onecard
def test_cast_int32():
    x0 = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float32))
    x1 = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int32))
    x2 = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.bool))
    t = mstype.int32

    context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
    net = Net(t)
    output = net(x0)
    type0 = output.asnumpy().dtype
    assert type0 == 'int32'
    output = net(x1)
    type1 = output.asnumpy().dtype
    assert type1 == 'int32'
    output = net(x2)
    type2 = output.asnumpy().dtype
    assert type2 == 'int32'

@pytest.mark.level0
@pytest.mark.platform_x86_cpu
@pytest.mark.env_onecard
def test_cast_float32():
    x0 = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float32))
    x1 = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int32))
    x2 = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.bool))
    t = mstype.float32

    context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
    net = Net(t)
    output = net(x0)
    type0 = output.asnumpy().dtype
    assert type0 == 'float32'
    output = net(x1)
    type1 = output.asnumpy().dtype
    assert type1 == 'float32'
    output = net(x2)
    type2 = output.asnumpy().dtype
    assert type2 == 'float32'