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src/nnet3/nnet-discriminative-diagnostics.h
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// nnet3/nnet-discriminative-diagnostics.h
// Copyright 2012-2015 Johns Hopkins University (author: Daniel Povey)
// Copyright 2014-2015 Vimal Manohar
// See ../../COPYING for clarification regarding multiple authors
//
// Licensed 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
//
// THIS CODE IS PROVIDED *AS IS* BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
// KIND, EITHER EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION ANY IMPLIED
// WARRANTIES OR CONDITIONS OF TITLE, FITNESS FOR A PARTICULAR PURPOSE,
// MERCHANTABLITY OR NON-INFRINGEMENT.
// See the Apache 2 License for the specific language governing permissions and
// limitations under the License.
#ifndef KALDI_NNET3_NNET_DISCRIMINATIVE_DIAGNOSTICS_H_
#define KALDI_NNET3_NNET_DISCRIMINATIVE_DIAGNOSTICS_H_
#include "nnet3/nnet-example.h"
#include "nnet3/nnet-computation.h"
#include "nnet3/nnet-compute.h"
#include "nnet3/nnet-optimize.h"
#include "nnet3/nnet-discriminative-example.h"
#include "nnet3/nnet-diagnostics.h"
#include "nnet3/discriminative-training.h"
namespace kaldi {
namespace nnet3 {
/** This class is for computing objective-function values in a nnet3
discriminative training, for diagnostics. It also supports computing model
derivatives.
*/
class NnetDiscriminativeComputeObjf {
public:
// does not store a reference to 'config' but does store one to 'nnet'.
NnetDiscriminativeComputeObjf(const NnetComputeProbOptions &nnet_config,
const discriminative::DiscriminativeOptions &discriminative_config,
const TransitionModel &tmodel,
const VectorBase<BaseFloat> &priors,
const Nnet &nnet);
// Reset the likelihood stats, and the derivative stats (if computed).
void Reset();
// compute objective on one minibatch.
void Compute(const NnetDiscriminativeExample &eg);
// Prints out the final stats, and return true if there was a nonzero count.
bool PrintTotalStats() const;
// returns the objective-function info for this output name (e.g. "output"),
// or NULL if there is no such info.
const discriminative::DiscriminativeObjectiveInfo *GetObjective(
const std::string &output_name) const;
// if config.compute_deriv == true, returns a reference to the
// computed derivative. Otherwise crashes.
const Nnet &GetDeriv() const;
~NnetDiscriminativeComputeObjf();
private:
void ProcessOutputs(const NnetDiscriminativeExample &eg,
NnetComputer *computer);
NnetComputeProbOptions nnet_config_;
discriminative::DiscriminativeOptions discriminative_config_;
const TransitionModel &tmodel_;
CuVector<BaseFloat> log_priors_;
const Nnet &nnet_;
CachingOptimizingCompiler compiler_;
Nnet *deriv_nnet_;
int32 num_minibatches_processed_; // this is only for diagnostics
unordered_map<std::string, discriminative::DiscriminativeObjectiveInfo, StringHasher> objf_info_;
};
} // namespace nnet3
} // namespace kaldi
#endif // KALDI_NNET3_NNET_DISCRIMINATIVE_DIAGNOSTICS_H_
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