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

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/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
* Copyright (c) 2019 Konduit K.K.
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*
* 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_RANDOM_H
#define LIBND4J_HEADERS_RANDOM_H
#include <ops/declarable/headers/common.h>
namespace sd {
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namespace ops {
#if NOT_EXCLUDED(OP_set_seed)
DECLARE_CUSTOM_OP(set_seed, -2, 1, false, 0, -2);
#endif
#if NOT_EXCLUDED(OP_get_seed)
DECLARE_CUSTOM_OP(get_seed, -2, 1, false, 0, 0);
#endif
/*
* random_uniform distribution for types int32,int64, float16, float and double
* by default dtype is float32
*
* input:
* 0 - shape of output (1D int tensor)
* 1 - min val (0D of output type) - optional (0 as default)
* 2 - max val (0D of output type) - optional (inf as default)
*
* output:
* 0 - uniformly distributed values of given type (between min and max)
*/
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#if NOT_EXCLUDED(OP_randomuniform)
DECLARE_CUSTOM_OP(randomuniform, 1, 1, false, 0, 0);
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#endif
Oleh multinomial (#163) * libnd4j: Multinomial op #8570 first raw step of multinomial random data generator implementation Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j: Multinomial op #8570 next step of multinomial random categories generator implementation on both cpu and cuda, need corrections and code clean up before review and testing * libnd4j: Multinomial op #8570 code clean up and fixed issues data selecting, moved from coords to tads * libnd4j: Multinomial op #8570 fixed cuda build add reference for math materials that was used for implementation * libnd4j: Multinomial op #8570 fixed several bugs, added several tests and improved cuda version. current implementation works, need testing of reproduction with the same seed * libnd4j: Multinomial op #8570 fixes and optimization after discussion in both cuda and cpu * libnd4j: Multinomial op #8570 add corrections after review, removed tads, replace 2D parallel loop by 3D Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j: Multinomial op fixed declaration and add tests need discussion * libnd4j: Multinomial op fix in test * libnd4j: Multinomial op corrected behavior to get reproducible results, fixed issue in uniform value getting, tests added, need cuda review and cuda testing Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j: Multinomial op fixed indexing on uniform calculation Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j: Multinomial op some corrections in max min declaration Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j: Multinomial op fixed index calculation, added rewind, corrected input declaration, added stats tests, both cuda and cpu. cuda need testing * libnd4j: Multinomial op fixed bugs on cuda nad cpu. need review Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j: Multinomial op corrected tests to handle different orders Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j: Multinomial op some improvements after code review Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j: Multinomial op more corrections after review Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j: Multinomial op fixed seed usage, update tests, fixed cuda based on comments, fixed bug of rewind, removed one behavior, minor corrections. Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j: Multinomial op minor corrections Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j: Multinomial op rise the bound of fluctuation for random cases Signed-off-by: Oleg <oleg.semeniv@gmail.com> * libnd4j: Multinomial op modified operation inputs and update implementation and tests on both cpu and cuda * libnd4j: Multinomial op corrected data types according ops.proto Co-authored-by: raver119 <raver119@gmail.com>
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/*
* multinomial (categorical) random generator draws samples from a multinomial distribution
*
* Input array:
* 0 - 2D ndarray with unnormalized log-probabilities with shape [batch_size (N), num_classes (K)]
* 1 - array with one int value of samples number, number of independent samples to draw for each experiment 1,N.
* Int arguments:
* 0 - optional argument, corresponds to dimension with batch_size
* 1 - optional argument, integer type to use for the output. Default int64.
*
* Output array:
* 0 - 2D ndarray with the drawn samples of shape [batch_size, num_samples]
*/
#if NOT_EXCLUDED(OP_random_multinomial)
DECLARE_CUSTOM_OP(random_multinomial, 2, 1, false, 0, 0);
#endif
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#if NOT_EXCLUDED(OP_random_normal)
DECLARE_CUSTOM_OP(random_normal, 1, 1, true, 2, 0);
#endif
#if NOT_EXCLUDED(OP_random_bernoulli)
DECLARE_CUSTOM_OP(random_bernoulli, 1, 1, true, 0, 1);
#endif
#if NOT_EXCLUDED(OP_random_exponential)
DECLARE_CUSTOM_OP(random_exponential, 1, 1, true, 1, 0);
#endif
#if NOT_EXCLUDED(OP_random_crop)
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DECLARE_CUSTOM_OP(random_crop, 2, 1, false, 0, 0);
#endif
/**
* random_gamma op.
*/
#if NOT_EXCLUDED(OP_random_gamma)
DECLARE_CUSTOM_OP(random_gamma, 2, 1, false, 0, 0);
#endif
/**
* random_poisson op.
*/
#if NOT_EXCLUDED(OP_random_poisson)
DECLARE_CUSTOM_OP(random_poisson, 2, 1, false, 0, 0);
#endif
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}
}
#endif