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// nnet3/nnet-example-test.cc
// Copyright 2015 Johns Hopkins University (author: Daniel Povey)
// 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.
#include "nnet3/nnet-nnet.h"
#include "nnet3/nnet-compile.h"
#include "nnet3/nnet-analyze.h"
#include "nnet3/nnet-test-utils.h"
#include "nnet3/nnet-optimize.h"
#include "nnet3/nnet-compute.h"
#include "nnet3/nnet-example.h"
#include "nnet3/nnet-example-utils.h"
#include "base/kaldi-math.h"
namespace kaldi {
namespace nnet3 {
void UnitTestNnetExample() {
for (int32 n = 0; n < 50; n++) {
NnetExample eg;
int32 num_supervised_frames = RandInt(1, 10),
left_context = RandInt(0, 5),
right_context = RandInt(0, 5),
input_dim = RandInt(1, 10),
output_dim = RandInt(5, 10),
ivector_dim = RandInt(-1, 2);
GenerateSimpleNnetTrainingExample(num_supervised_frames, left_context,
right_context, input_dim, output_dim,
ivector_dim, &eg);
bool binary = (RandInt(0, 1) == 0);
std::ostringstream os;
eg.Write(os, binary);
NnetExample eg_copy;
if (RandInt(0, 1) == 0)
eg_copy = eg;
std::istringstream is(os.str());
eg_copy.Read(is, binary);
std::ostringstream os2;
eg_copy.Write(os2, binary);
if (binary) {
KALDI_ASSERT(os.str() == os2.str());
KALDI_ASSERT(eg_copy == eg);
}
KALDI_ASSERT(ExampleApproxEqual(eg, eg_copy, 0.1));
}
}
void UnitTestNnetMergeExamples() {
for (int32 n = 0; n < 50; n++) {
int32 num_supervised_frames = RandInt(1, 10),
left_context = RandInt(0, 5),
right_context = RandInt(0, 5),
input_dim = RandInt(1, 10),
output_dim = RandInt(5, 10),
ivector_dim = RandInt(-1, 2);
int32 num_egs = RandInt(1, 4);
std::vector<NnetExample> egs_to_be_merged(num_egs);
for (int32 i = 0; i < num_egs; i++) {
NnetExample eg;
// sometimes omit the ivector. just tests things a bit more
// thoroughly.
GenerateSimpleNnetTrainingExample(num_supervised_frames, left_context,
right_context, input_dim, output_dim,
RandInt(0, 1) == 0 ? 0 : ivector_dim,
&eg);
KALDI_LOG << i << "'th example to be merged is: ";
eg.Write(std::cerr, false);
egs_to_be_merged[i].Swap(&eg);
}
NnetExample eg_merged;
bool compress = (RandInt(0, 1) == 0);
MergeExamples(egs_to_be_merged, compress, &eg_merged);
KALDI_LOG << "Merged example is: ";
eg_merged.Write(std::cerr, false);
}
}
} // namespace nnet3
} // namespace kaldi
int main() {
using namespace kaldi;
using namespace kaldi::nnet3;
UnitTestNnetExample();
UnitTestNnetMergeExamples();
KALDI_LOG << "Nnet-example tests succeeded.";
return 0;
}
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