1# Copyright 2020-2021 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# ============================================================================ 15 16import numpy as np 17import pytest 18import mindspore.context as context 19from mindspore import Tensor 20from mindspore.nn import Cell 21import mindspore.ops.operations as P 22 23 24class Net(Cell): 25 def __init__(self): 26 super(Net, self).__init__() 27 self.reduce_mean = P.ReduceMean(keep_dims=False) 28 29 def construct(self, x): 30 return self.reduce_mean(x) 31 32 33def test_reduce_mean(): 34 np.random.seed(0) 35 input_x = np.random.normal(0, 1, [2, 3, 4, 3]).astype(np.float32) 36 expect = np.mean(input_x, keepdims=False) 37 net = Net() 38 result = net(Tensor(input_x)) 39 res = np.allclose(expect, result.asnumpy(), rtol=1.e-4, atol=1.e-7, equal_nan=True) 40 assert res 41 42 43@pytest.mark.level0 44@pytest.mark.platform_x86_gpu_training 45@pytest.mark.env_onecard 46def test_reduce_mean_gpu(): 47 context.set_context(mode=context.GRAPH_MODE, enable_graph_kernel=True, device_target="GPU") 48 test_reduce_mean() 49 50 51@pytest.mark.level0 52@pytest.mark.platform_arm_ascend_training 53@pytest.mark.platform_x86_ascend_training 54@pytest.mark.env_onecard 55def test_reduce_mean_ascend(): 56 context.set_context(mode=context.GRAPH_MODE, enable_graph_kernel=True, device_target="Ascend") 57 test_reduce_mean() 58