1# Copyright 2021 Huawei Technologies Co., Ltd 2# 3# Licensed under the Apache License, Version 2.0 (the "License"); 4# you may not use this file except in compliance with the License. 5# You may obtain a copy of the License at 6# 7# http://www.apache.org/licenses/LICENSE-2.0 8# 9# Unless required by applicable law or agreed to in writing, software 10# distributed under the License is distributed on an "AS IS" BASIS, 11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12# See the License for the specific language governing permissions and 13# limitations under the License. 14# ============================================================================ 15import numpy as np 16import pytest 17import mindspore.context as context 18import mindspore.nn as nn 19from mindspore import Tensor 20from mindspore.ops import operations as P 21 22 23class Net(nn.Cell): 24 def __init__(self): 25 super(Net, self).__init__() 26 self.squared_difference = P.SquaredDifference() 27 28 def construct(self, x, y): 29 return self.squared_difference(x, y) 30 31 32def get_output(x, y, enable_graph_kernel=False): 33 context.set_context(enable_graph_kernel=enable_graph_kernel) 34 net = Net() 35 output = net(x, y) 36 return output 37 38 39def test_squared_difference(shape1, shape2, dtype): 40 x = Tensor(np.random.normal(0, 10, shape1).astype(dtype)) 41 y = Tensor(np.random.normal(0, 10, shape2).astype(dtype)) 42 expect = get_output(x, y, False) 43 output = get_output(x, y, True) 44 45 expect_np = expect.asnumpy().copy() 46 output_np = output.asnumpy().copy() 47 48 assert np.allclose(expect_np, output_np, 0.0001, 0.0001) 49 50 51@pytest.mark.level0 52@pytest.mark.platform_x86_gpu_training 53@pytest.mark.env_onecard 54def test_squared_difference_gpu(): 55 context.set_context(mode=context.GRAPH_MODE, device_target="GPU") 56 test_squared_difference((4, 3), (4, 3), np.float16) 57 test_squared_difference((6, 2), (1), np.int32) 58 test_squared_difference((1), (4, 3), np.float32) 59