| /* |
| * 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 |