| # Licensed to the Apache Software Foundation (ASF) under one |
| # or more contributor license agreements. See the NOTICE file |
| # distributed with this work for additional information |
| # regarding copyright ownership. The ASF licenses this file |
| # to you under the Apache License, Version 2.0 (the |
| # "License"); you may not use this file except in compliance |
| # with the License. You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, |
| # software distributed under the License is distributed on an |
| # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
| # KIND, either express or implied. See the License for the |
| # specific language governing permissions and limitations |
| # under the License. |
| |
| import numpy as np |
| import mxnet as mx |
| from mxnet import gluon |
| from numpy.testing import assert_allclose, assert_array_equal |
| from mxnet.test_utils import * |
| from mxnet.base import _as_list |
| from mxnet.attribute import AttrScope |
| from common import with_seed |
| |
| |
| def test_dynamic_shape(): |
| |
| class _TestBlock(gluon.HybridBlock): |
| |
| def __init__(self): |
| super(_TestBlock, self).__init__() |
| |
| def hybrid_forward(self, F, data, index): |
| return F.contrib.boolean_mask(data, index) |
| |
| block = _TestBlock() |
| block.hybridize() |
| data = mx.nd.array([[1, 2, 3],[4, 5, 6],[7, 8, 9]]) |
| index = mx.nd.array([0, 1, 1]) |
| data.attach_grad() |
| with mx.autograd.record(): |
| result = block(data, index) |
| result.backward() |
| result_nd = np.array([[4, 5, 6], [7, 8, 9]]) |
| data_grad_nd = np.array([[0., 0., 0.], [1., 1., 1.], [1., 1., 1.]]) |
| assert_almost_equal(result.asnumpy(), result_nd) |
| assert_almost_equal(data.grad.asnumpy(), data_grad_nd) |
| |
| |
| if __name__ == '__main__': |
| import nose |
| nose.runmodule() |