# 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 pytest from tvm import relay from tvm.relay.testing import check_grad def verify_sum_grad(d_shape, axis=None, keepdims=False, exclude=False): data = relay.var("data", relay.TensorType(d_shape, "float32")) fwd_func = relay.Function([data], relay.sum(data, axis=axis, keepdims=keepdims, exclude=exclude)) check_grad(fwd_func) def test_sum_grad(): verify_sum_grad((4, 2)) verify_sum_grad((4, 2), axis=-1, keepdims=True) verify_sum_grad((4, 2, 1), axis=(1, 2), exclude=True) verify_sum_grad((4, 2, 1), axis=1) def verify_max_grad(d_shape, axis=None, keepdims=False, exclude=False): data = relay.var("data", relay.TensorType(d_shape, "float32")) fwd_func = relay.Function([data], relay.max(data, axis=axis, keepdims=keepdims, exclude=exclude)) check_grad(fwd_func, scale=1e-3) def test_max_grad(): verify_max_grad((10, 10), axis=None) verify_max_grad((10, 10), axis=-1) verify_max_grad((6, 3, 2), axis=(1, 2), keepdims=True) verify_max_grad((5, 4, 3), axis=(0, 2), exclude=True) if __name__ == "__main__": pytest.main()