| # 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. |
| |
| # pylint: skip-file |
| import mxnet as mx |
| import numpy as np |
| from common import models |
| from mxnet import autograd |
| from mxnet.test_utils import assert_almost_equal |
| |
| def test_infer_multiout_op(): |
| data = mx.nd.arange(16, dtype=np.float64).reshape((4, 4)) |
| data.attach_grad() |
| |
| with autograd.record(): |
| y = mx.nd.split(data, axis=0, num_outputs=2) |
| y[0].backward() |
| assert data.grad.dtype == np.float64 |
| mx.nd.waitall() |
| |
| def test_infer_multiout_op2(): |
| def test_func(a): |
| q, l = mx.nd.linalg.gelqf(a) |
| return mx.nd.sum(l) |
| |
| data32 = mx.nd.random.normal(shape=(2, 3), ctx=mx.cpu(), dtype=np.float32) |
| data32.attach_grad() |
| with autograd.record(): |
| test32 = test_func(data32) |
| test32.backward() |
| |
| data64 = mx.nd.Cast(data32, dtype=np.float64) |
| data64.attach_grad() |
| with autograd.record(): |
| test64 = test_func(data64) |
| test64.backward() |
| assert_almost_equal(data64.grad.asnumpy(), data32.grad.asnumpy(), atol=1e-5, rtol=1e-5) |
| |