1# Copyright 2020 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 17 18import mindspore.context as context 19import mindspore.nn as nn 20from mindspore import Tensor 21from mindspore.ops import operations as P 22 23context.set_context(mode=context.GRAPH_MODE, device_target="Ascend") 24 25 26class DynamicGRUV2(nn.Cell): 27 def __init__(self): 28 super(DynamicGRUV2, self).__init__() 29 self.dynamic_gru = P.DynamicGRUV2() 30 31 def construct(self, x, weight_i, weight_h, bias_i, bias_h, init_h): 32 return self.dynamic_gru(x, weight_i, weight_h, bias_i, bias_h, None, init_h) 33 34 35@pytest.mark.level1 36@pytest.mark.env_onecard 37@pytest.mark.platform_arm_ascend_training 38@pytest.mark.platform_x86_ascend_training 39def test_dynamic_gru_v2(): 40 x = Tensor(np.random.rand(2, 8, 64).astype(np.float16)) 41 weight_i = Tensor(np.random.rand(64, 48).astype(np.float16)) 42 weight_h = Tensor(np.random.rand(16, 48).astype(np.float16)) 43 bias_i = Tensor(np.random.rand(48).astype(np.float16)) 44 bias_h = Tensor(np.random.rand(48).astype(np.float16)) 45 init_h = Tensor(np.random.rand(8, 16).astype(np.float16)) 46 gru_net = DynamicGRUV2() 47 output = gru_net(x, weight_i, weight_h, bias_i, bias_h, init_h) 48 assert output[0].shape == (2, 8, 16) 49