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# ============================================================================ 15"""test gat model.""" 16import numpy as np 17 18import mindspore.nn as nn 19import mindspore.context as context 20from mindspore import Tensor 21from mindspore.common.api import _cell_graph_executor 22from gat import GAT 23 24context.set_context(mode=context.GRAPH_MODE) 25 26 27def test_GAT(): 28 ft_sizes = 1433 29 num_class = 7 30 num_nodes = 2708 31 hid_units = [8] 32 n_heads = [8, 1] 33 activation = nn.ELU() 34 residual = False 35 input_data = Tensor( 36 np.array(np.random.rand(1, 2708, 1433), dtype=np.float32)) 37 biases = Tensor(np.array(np.random.rand(1, 2708, 2708), dtype=np.float32)) 38 net = GAT(ft_sizes, 39 num_class, 40 num_nodes, 41 hidden_units=hid_units, 42 num_heads=n_heads, 43 attn_drop=0.6, 44 ftr_drop=0.6, 45 activation=activation, 46 residual=residual) 47 _cell_graph_executor.compile(net, input_data, biases) 48