Python InferExperiment Examples

Example #1

File: infer.py Project: KIngpon/NJUNMT-tf

def main(_argv):
    model_configs = maybe_load_yaml(DEFAULT_INFER_CONFIGS)
    # load flags from config file
    model_configs = load_from_config_path(FLAGS.config_paths, model_configs)
    # replace parameters in configs_file with tf FLAGS
    model_configs = update_infer_model_configs(model_configs, FLAGS)

    model_dirs = FLAGS.model_dir.strip().split(",")
    if len(model_dirs) == 1:
        model_configs = deep_merge_dict(model_configs, ModelConfigs.load(model_dirs[0]))
        model_configs = update_infer_model_configs(model_configs, FLAGS)
        runner = InferExperiment(model_configs=model_configs)
    else:
        runner = EnsembleExperiment(model_configs=model_configs, model_dirs=model_dirs,
                                    weight_scheme=FLAGS.weight_scheme)
    runner.run()

Example #2

def main(_argv):
    model_configs = maybe_load_yaml(DEFAULT_INFER_CONFIGS)
    # load flags from config file
    model_configs = load_from_config_path(FLAGS.config_paths, model_configs)
    # replace parameters in configs_file with tf FLAGS
    model_configs = update_infer_model_configs(model_configs, FLAGS)

    model_dirs = FLAGS.model_dir.strip().split(",")
    if len(model_dirs) == 1:
        model_configs = deep_merge_dict(model_configs,
                                        ModelConfigs.load(model_dirs[0]))
        runner = InferExperiment(model_configs=model_configs)
    else:
        runner = EnsembleExperiment(model_configs=model_configs,
                                    model_dirs=model_dirs,
                                    weight_scheme=FLAGS.weight_scheme)
    runner.run()

Example #3

 def default_inference_options():
     """ Returns a dictionary of default inference options. """
     return InferExperiment.default_inference_options()

Example #4

File: ensemble_experiment.py Project: KIngpon/NJUNMT-tf

 def default_inference_options():
     """ Returns a dictionary of default inference options. """
     return InferExperiment.default_inference_options()