def _CreateMetadataDict(benchmark_spec):
"""Create metadata dict to be used in run results.
Args:
benchmark_spec: The benchmark specification. Contains all data that is
required to run the benchmark.
Returns:
metadata dict
"""
return mnist_benchmark.CreateMetadataDict(benchmark_spec)
def _CreateMetadataDict(benchmark_spec):
"""Create metadata dict to be used in run results.
Args:
benchmark_spec: The benchmark specification. Contains all data that is
required to run the benchmark.
Returns:
metadata dict
"""
metadata = mnist_benchmark.CreateMetadataDict(benchmark_spec)
metadata.update({
'model': benchmark_spec.model,
'problem': benchmark_spec.problem,
'hparams_set': benchmark_spec.hparams_set,
'data_dir': benchmark_spec.data_dir,
'model_dir': benchmark_spec.model_dir,
'train_steps': benchmark_spec.train_steps,
'eval_steps': benchmark_spec.eval_steps})
return metadata
def _CreateMetadataDict(benchmark_spec):
"""Create metadata dict to be used in run results.
Args:
benchmark_spec: The benchmark specification. Contains all data that is
required to run the benchmark.
Returns:
metadata dict
"""
metadata = mnist_benchmark.CreateMetadataDict(benchmark_spec)
metadata.update({
'depth': benchmark_spec.depth,
'mode': benchmark_spec.mode,
'data_format': benchmark_spec.data_format,
'precision': benchmark_spec.precision,
'skip_host_call': benchmark_spec.skip_host_call,
'epochs_per_eval': benchmark_spec.epochs_per_eval,
'steps_per_eval': benchmark_spec.steps_per_eval
})
return metadata
def _CreateMetadataDict(benchmark_spec):
"""Create metadata dict to be used in run results.
Args:
benchmark_spec: The benchmark specification. Contains all data that is
required to run the benchmark.
Returns:
metadata dict
"""
metadata = mnist_benchmark.CreateMetadataDict(benchmark_spec)
metadata.update({
'learning_rate': benchmark_spec.learning_rate,
'use_data': benchmark_spec.use_data,
'mode': benchmark_spec.mode,
'save_checkpoints_secs': benchmark_spec.save_checkpoints_secs,
'epochs_per_eval': benchmark_spec.epochs_per_eval,
'steps_per_eval': benchmark_spec.steps_per_eval,
'precision': benchmark_spec.precision
})
return metadata