105 lines
3.5 KiB
C++
105 lines
3.5 KiB
C++
/*
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* ******************************************************************************
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* *
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* *
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* * This program and the accompanying materials are made available under the
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* * terms of the Apache License, Version 2.0 which is available at
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* * https://www.apache.org/licenses/LICENSE-2.0.
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* *
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* * See the NOTICE file distributed with this work for additional
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* * information regarding copyright ownership.
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* * Unless required by applicable law or agreed to in writing, software
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* * distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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* * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* * License for the specific language governing permissions and limitations
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* * under the License.
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* *
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* * SPDX-License-Identifier: Apache-2.0
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* *****************************************************************************
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*/
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//
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// @author raver119@gmail.com
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//
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#ifndef LIBND4J_HEADERS_RANDOM_H
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#define LIBND4J_HEADERS_RANDOM_H
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#include <ops/declarable/headers/common.h>
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namespace sd {
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namespace ops {
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#if NOT_EXCLUDED(OP_set_seed)
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DECLARE_CUSTOM_OP(set_seed, -2, 1, false, 0, -2);
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#endif
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#if NOT_EXCLUDED(OP_get_seed)
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DECLARE_CUSTOM_OP(get_seed, -2, 1, false, 0, 0);
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#endif
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/*
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* random_uniform distribution for types int32,int64, float16, float and double
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* by default dtype is float32
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*
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* input:
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* 0 - shape of output (1D int tensor)
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* 1 - min val (0D of output type) - optional (0 as default)
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* 2 - max val (0D of output type) - optional (inf as default)
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*
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* output:
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* 0 - uniformly distributed values of given type (between min and max)
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*/
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#if NOT_EXCLUDED(OP_randomuniform)
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DECLARE_CUSTOM_OP(randomuniform, 1, 1, false, 0, -1);
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#endif
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/*
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* multinomial (categorical) random generator draws samples from a multinomial distribution
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*
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* Input array:
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* 0 - 2D ndarray with unnormalized log-probabilities with shape [batch_size (N), num_classes (K)]
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* 1 - array with one int value of samples number, number of independent samples to draw for each experiment 1,N.
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* Int arguments:
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* 0 - optional argument, corresponds to dimension with batch_size
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* 1 - optional argument, integer type to use for the output. Default int64.
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*
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* Output array:
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* 0 - 2D ndarray with the drawn samples of shape [batch_size, num_samples]
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*/
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#if NOT_EXCLUDED(OP_random_multinomial)
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DECLARE_CUSTOM_OP(random_multinomial, 2, 1, false, 0, 0);
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#endif
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#if NOT_EXCLUDED(OP_random_normal)
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DECLARE_CUSTOM_OP(random_normal, 1, 1, true, 2, 0);
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#endif
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#if NOT_EXCLUDED(OP_random_bernoulli)
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DECLARE_CUSTOM_OP(random_bernoulli, 1, 1, true, 0, 1);
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#endif
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#if NOT_EXCLUDED(OP_random_exponential)
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DECLARE_CUSTOM_OP(random_exponential, 1, 1, true, 1, 0);
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#endif
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#if NOT_EXCLUDED(OP_random_crop)
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DECLARE_CUSTOM_OP(random_crop, 2, 1, false, 0, 0);
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#endif
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/**
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* random_gamma op.
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*/
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#if NOT_EXCLUDED(OP_random_gamma)
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DECLARE_CUSTOM_OP(random_gamma, 2, 1, false, 0, 0);
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#endif
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/**
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* random_poisson op.
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*/
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#if NOT_EXCLUDED(OP_random_poisson)
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DECLARE_CUSTOM_OP(random_poisson, 2, 1, false, 0, 0);
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#endif
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}
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}
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#endif |