1# Copyright 2023 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 18 19import mindspore as ms 20import mindspore.nn as nn 21from mindspore import Tensor 22 23 24class Net(nn.Cell): 25 def __init__(self): 26 super(Net, self).__init__() 27 self.embeddinglookup = nn.EmbeddingLookup(4, 2, dtype=ms.float32) 28 29 def construct(self, x): 30 out = self.embeddinglookup(x) 31 return out 32 33 34@pytest.mark.level1 35@pytest.mark.platform_x86_cpu 36@pytest.mark.platform_arm_cpu 37@pytest.mark.platform_x86_gpu_training 38@pytest.mark.platform_arm_ascend_training 39@pytest.mark.platform_x86_ascend_training 40@pytest.mark.env_onecard 41@pytest.mark.parametrize('mode', [ms.GRAPH_MODE, ms.PYNATIVE_MODE]) 42def test_embeddinglookup_para_customed_dtype(mode): 43 """ 44 Feature: EmbeddingLookup 45 Description: Verify the result of EmbeddingLookup specifying customed para dtype. 46 Expectation: success 47 """ 48 ms.set_context(mode=mode) 49 net = Net() 50 x = Tensor(np.array([[1, 0], [3, 2]]), ms.int32) 51 output = net(x) 52 expect_output_shape = (2, 2, 2) 53 assert np.allclose(expect_output_shape, output.shape) 54