# Copyright 2021 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.context as context
from mindspore import Tensor
from mindspore.nn import Cell
import mindspore.ops.operations as P
import mindspore.common.dtype as mstype

class Net(Cell):
    def __init__(self):
        super(Net, self).__init__()
        self.oneslike = P.OnesLike()

    def construct(self, shape, dtype, x):
        return self.oneslike(x)

def get_output(shape, dtype, nptype, enable_graph_kernel=False):
    context.set_context(enable_graph_kernel=enable_graph_kernel)
    net = Net()
    x = Tensor(np.random.normal(0, 10, shape).astype(nptype))
    output = net(shape, dtype, x)
    return output

def test_basic(shape, dtype, nptype):
    expect = get_output(shape, dtype, nptype, False)
    output = get_output(shape, dtype, nptype, True)
    assert np.allclose(expect.asnumpy(), output.asnumpy(), 1.e-4, 1.e-7)

@pytest.mark.level0
@pytest.mark.platform_x86_gpu_training
@pytest.mark.env_onecard
def test_gpu_1():
    context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
    test_basic((2, 16), mstype.float16, np.float16)

@pytest.mark.level0
@pytest.mark.platform_x86_gpu_training
@pytest.mark.env_onecard
def test_gpu_2():
    context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
    test_basic((4, 32), mstype.float32, np.float32)