cavis/libnd4j/include/ops/declarable/headers/transforms.h

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2019-06-06 14:21:15 +02:00
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
//
// @author raver119@gmail.com
//
#ifndef LIBND4J_HEADERS_TRANSFORMS_H
#define LIBND4J_HEADERS_TRANSFORMS_H
#include <ops/declarable/headers/common.h>
namespace nd4j {
namespace ops {
#if NOT_EXCLUDED(OP_clipbyvalue)
DECLARE_CONFIGURABLE_OP(clipbyvalue, 1, 1, true, 2, 0);
#endif
#if NOT_EXCLUDED(OP_clipbynorm)
DECLARE_CONFIGURABLE_OP(clipbynorm, 1, 1, true, 1, 0);
DECLARE_CUSTOM_OP(clipbynorm_bp, 2, 1, false, 1, 0);
#endif
#if NOT_EXCLUDED(OP_clipbyavgnorm)
DECLARE_CONFIGURABLE_OP(clipbyavgnorm, 1, 1, true, 1, 0);
#endif
#if NOT_EXCLUDED(OP_cumsum)
DECLARE_CONFIGURABLE_OP(cumsum, 1, 1, true, 0, 2);
#endif
#if NOT_EXCLUDED(OP_cumprod)
DECLARE_CONFIGURABLE_OP(cumprod, 1, 1, true, 0, 2);
#endif
#if NOT_EXCLUDED(OP_tile)
DECLARE_CUSTOM_OP(tile, 1, 1, false, 0, -2);
DECLARE_CUSTOM_OP(tile_bp, 2, 1, false, 0, -2);
#endif
#if NOT_EXCLUDED(OP_repeat)
DECLARE_CUSTOM_OP(repeat, 1, 1, true, 0, -1);
#endif
#if NOT_EXCLUDED(OP_invert_permutation)
DECLARE_CONFIGURABLE_OP(invert_permutation, 1, 1, false, 0, 0);
#endif
DECLARE_CUSTOM_OP(concat, -1, 1, false, 0, 1);
DECLARE_CUSTOM_OP(concat_bp, -1, -1, false, 0, 1);
#if NOT_EXCLUDED(OP_mergemax)
DECLARE_OP(mergemax, -1, 1, false);
#endif
#if NOT_EXCLUDED(OP_mergemaxindex)
DECLARE_OP(mergemaxindex, -1, 1, false);
#endif
#if NOT_EXCLUDED(OP_mergeadd)
DECLARE_OP(mergeadd, -1, 1, false);
#endif
#if NOT_EXCLUDED(OP_mergeavg)
DECLARE_OP(mergeavg, -1, 1, false);
#endif
#if NOT_EXCLUDED(OP_scatter_update)
DECLARE_CONFIGURABLE_OP(scatter_update, 2, 1, true, 0, -1);
#endif
#if NOT_EXCLUDED(OP_Floor)
DECLARE_OP(Floor, 1, 1, true);
#endif
#if NOT_EXCLUDED(OP_Log1p)
DECLARE_OP(Log1p, 2, 1, true);
#endif
#if NOT_EXCLUDED(OP_reverse)
DECLARE_CONFIGURABLE_OP(reverse, 1, 1, true, 0, -2);
DECLARE_CUSTOM_OP(reverse_bp, 2, 1, false, 0, -2);
#endif
#if NOT_EXCLUDED(OP_gather)
DECLARE_CUSTOM_OP(gather, 1, 1, false, 0, -2);
#endif
#if NOT_EXCLUDED(OP_pad)
DECLARE_CUSTOM_OP(pad, 2, 1, false, 0, 1);
#endif
/**
* creates identity 2D matrix or batch of identical 2D identity matrices
*
* Input array:
* provide some array - in any case operation simply neglects it
*
* Input integer arguments:
* IArgs[0] - order of output identity matrix, 99 -> 'c'-order, 102 -> 'f'-order
* IArgs[1] - the number of rows in output inner-most 2D identity matrix
* IArgs[2] - optional, the number of columns in output inner-most 2D identity matrix, if this argument is not provided then it is taken to be equal to number of rows
* IArgs[3,4,...] - optional, shape of batch, output matrix will have leading batch dimensions of this shape
*/
#if NOT_EXCLUDED(OP_eye)
DECLARE_CUSTOM_OP(eye, -2, 1, false, 0, 2);
#endif
#if NOT_EXCLUDED(OP_gather_nd)
DECLARE_CUSTOM_OP(gather_nd, 2, 1, false, 0, 0);
#endif
#if NOT_EXCLUDED(OP_reverse_sequence)
DECLARE_CUSTOM_OP(reverse_sequence, 2, 1, false, 0, 2);
#endif
#if NOT_EXCLUDED(OP_trace)
DECLARE_CUSTOM_OP(trace, 1, 1, false, 0, 0);
#endif
#if NOT_EXCLUDED(OP_random_shuffle)
DECLARE_OP(random_shuffle, 1, 1, true);
#endif
/**
* clip a list of given tensors with given average norm when needed
*
* Input:
* a list of tensors (at least one)
*
* Input floating point argument:
* clip_norm - a value that used as threshold value and norm to be used
*
* return a list of clipped tensors
* and global_norm as scalar tensor at the end
*/
#if NOT_EXCLUDED(OP_clip_by_global_norm)
DECLARE_CUSTOM_OP(clip_by_global_norm, 1, 2, true, 1, 0);
#endif
DECLARE_CUSTOM_OP(tri, -2, 1, false, 0, 1);
DECLARE_CUSTOM_OP(triu, 1, 1, false, 0, 0);
DECLARE_CUSTOM_OP(triu_bp, 2, 1, false, 0, 0);
#if NOT_EXCLUDED(OP_mirror_pad)
DECLARE_CUSTOM_OP(mirror_pad, 2, 1, false, 0, 1);
#endif
#if NOT_EXCLUDED(OP_cumsum)
DECLARE_CUSTOM_OP(cumsum_bp, 2, -1, false, 0, 2);
#endif
#if NOT_EXCLUDED(OP_cumprod)
DECLARE_CUSTOM_OP(cumprod_bp, 2, -21, false, 0, 2);
#endif
#if NOT_EXCLUDED(OP_flatten)
DECLARE_CUSTOM_OP(flatten, -1, 1, false, 0, 1);
#endif
/**
* returns histogram (as 1D array) with fixed bins width
*
* Input arrays:
* - input array with elements to be binned into output histogram
* - range array with first element being bottom limit and second element being top limit of histogram,
please note that input_value <= range[0] will be mapped to histogram[0], input_value >= range[1] will be mapped to histogram[-1]
*
* Input integer arguments:
* nbins (optional) - number of histogram bins, default value is 100
*/
#if NOT_EXCLUDED(OP_histogram_fixed_width)
DECLARE_CUSTOM_OP(histogram_fixed_width, 2, 1, false, 0, 0);
#endif
/**
* standardizes input array to be zero mean unit variance along the given axis
*
*
*/
#if NOT_EXCLUDED(OP_standardize)
DECLARE_CONFIGURABLE_OP(standardize, 1, 1, true, 0, -2);
DECLARE_CUSTOM_OP(standardize_bp, 2, 1, false, 0, -2);
#endif
/**
* This operation calculates hash code, optionally along dimension
*/
#if NOT_EXCLUDED(OP_hashcode)
DECLARE_REDUCTION_OP(hashcode, 1, 1, false, 0, 0);
#endif
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}
}
#endif