View source on GitHub
|
Training utils.
Classes
class BestCheckpointExporter: Keeps track of the best result, and saves its checkpoint.
class ExperimentParser: Constructs the Experiment config from Flags or equivalent object.
class ParseConfigOptions: Use this dataclass instead of FLAGS to customize parse_configuration().
Functions
cast_leaf_nested_dict(...): Cast the leaves of a dictionary with arbitrary depth in place.
convert_variables_to_constants_v2_as_graph(...): Replaces all the variables in a graph with constants of the same values.
create_optimizer(...): A create optimizer util to be backward compatability with new args.
create_trainer(...): Create trainer.
get_leaf_nested_dict(...): Get leaf from a dictionary with arbitrary depth with a list of keys.
maybe_create_best_ckpt_exporter(...): Maybe create a BestCheckpointExporter object, according to the config.
parse_configuration(...): Parses ExperimentConfig from flags.
read_global_step_from_checkpoint(...): Read global step from checkpoint, or get global step from its filename.
remove_ckpts(...): Remove model checkpoints, so we can restart.
save_gin_config(...): Serializes and saves the experiment config.
serialize_config(...): Serializes and saves the experiment config.
try_count_flops(...): Counts and returns model FLOPs.
try_count_params(...): Count the number of parameters if model is possible.
write_json_summary(...): Dump evaluation metrics to json file.
write_model_params(...): Writes the model parameters and shapes to a file.
write_summary(...): Write evaluation metrics to TF summary.
Other Members | |
|---|---|
| BEST_CHECKPOINT_NAME |
'best_ckpt'
|