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/*
* 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.
*/
/*!
* Copyright (c) 2016 by Contributors
* \file sample_op.cc
* \brief CPU Implementation of unique sample op
*/
#include "./unique_sample_op.h"
#include "../tensor/init_op.h"
namespace mxnet {
namespace op {
DMLC_REGISTER_PARAMETER(SampleUniqueZifpianParam);
#define MXNET_OPERATOR_REGISTER_UNIQUE_SAMPLE(name, ParamType) \
NNVM_REGISTER_OP(name) \
.set_num_inputs(0) \
.set_num_outputs(2) \
.set_attr_parser(ParamParser<ParamType>) \
.set_attr<FResourceRequest>("FResourceRequest", UniqueSampleResource) \
.add_arguments(ParamType::__FIELDS__())
MXNET_OPERATOR_REGISTER_UNIQUE_SAMPLE(_sample_unique_zipfian,
SampleUniqueZifpianParam)
.describe(R"code(Draw random samples from an an approximately log-uniform
or Zipfian distribution without replacement.
This operation takes a 2-D shape `(batch_size, num_sampled)`,
and randomly generates *num_sampled* samples from the range of integers [0, range_max)
for each instance in the batch.
The elements in each instance are drawn without replacement from the base distribution.
The base distribution for this operator is an approximately log-uniform or Zipfian distribution:
P(class) = (log(class + 2) - log(class + 1)) / log(range_max + 1)
Additionaly, it also returns the number of trials used to obtain `num_sampled` samples for
each instance in the batch.
Example::
samples, trials = _sample_unique_zipfian(750000, shape=(4, 8192))
unique(samples[0]) = 8192
unique(samples[3]) = 8192
trials[0] = 16435
)code" ADD_FILELINE)
.set_attr<mxnet::FInferShape>("FInferShape", SampleUniqueShape<SampleUniqueZifpianParam>)
.set_attr<nnvm::FInferType>("FInferType", SampleUniqueType<SampleUniqueZifpianParam>)
.set_attr<FCompute>("FCompute<cpu>", SampleUniqueZifpian);
} // namespace op
} // namespace mxnet