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- #!/usr/bin/env python3
- # coding: utf-8
- # Copyright 2019 Huawei Technologies Co., Ltd
- #
- # Licensed 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.
-
- """operator dsl function: reduce_max"""
-
- import akg.tvm
- from akg.ops.math import reduce_min_max_common
- from akg.utils.validation_check import check_input_type
-
-
- @check_input_type(akg.tvm.tensor.Tensor, (int, list, tuple, type(None)), (bool, type(None)))
- def reduce_max(data, axis=None, keepdims=False):
- """
- Computes the maximum of elements over a given axis or a list of axes of a tensor.
-
- Args:
- data (tvm.tensor.Tensor): The input tensor to reduce. Should be of type float16, float32, int8, uint8, int32.
- axis (Union[list, tuple, int, None]): The dimensions to reduce.
- If None, all dimensions will be reduced.
- If int or list, must be in the range [-len(data.shape), len(data.shape) - 1].
- keepdims (bool): If True, retains reduced dimensions with length 1, default value is False.
-
- Returns:
- tvm.tensor.Tensor of same type as input tensor data.
- """
- return reduce_min_max_common.reduce_min_max(data, axis=axis, keepdims=keepdims, method="max")
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