def main(argv):
del argv # Unused.
params = params_dict.ParamsDict(unet_config.UNET_CONFIG,
unet_config.UNET_RESTRICTIONS)
params = params_dict.override_params_dict(params,
FLAGS.config_file,
is_strict=False)
if FLAGS.training_file_pattern:
params.override({'training_file_pattern': FLAGS.training_file_pattern},
is_strict=True)
if FLAGS.eval_file_pattern:
params.override({'eval_file_pattern': FLAGS.eval_file_pattern},
is_strict=True)
train_epoch_steps = params.train_item_count // params.train_batch_size
eval_epoch_steps = params.eval_item_count // params.eval_batch_size
params.override(
{
'model_dir': FLAGS.model_dir,
'min_eval_interval': FLAGS.min_eval_interval,
'eval_timeout': FLAGS.eval_timeout,
'tpu_config': tpu_executor.get_tpu_flags(),
'lr_decay_steps': train_epoch_steps,
'train_steps': params.train_epochs * train_epoch_steps,
'eval_steps': eval_epoch_steps,
},
is_strict=False)
params = params_dict.override_params_dict(params,
FLAGS.params_override,
is_strict=True)
params.validate()
params.lock()
train_input_fn = None
eval_input_fn = None
train_input_shapes = None
eval_input_shapes = None
if FLAGS.mode in ('train', 'train_and_eval'):
train_input_fn = input_reader.LiverInputFn(
params.training_file_pattern,
params,
mode=tf.estimator.ModeKeys.TRAIN)
train_input_shapes = train_input_fn.get_input_shapes(params)
if FLAGS.mode in ('eval', 'train_and_eval'):
eval_input_fn = input_reader.LiverInputFn(
params.eval_file_pattern, params, mode=tf.estimator.ModeKeys.EVAL)
eval_input_shapes = eval_input_fn.get_input_shapes(params)
assert train_input_shapes is not None or eval_input_shapes is not None
run_executer(params,
train_input_shapes=train_input_shapes,
eval_input_shapes=eval_input_shapes,
train_input_fn=train_input_fn,
eval_input_fn=eval_input_fn)
def main(argv):
del argv # Unused.
params = params_dict.ParamsDict(unet_config.UNET_CONFIG,
unet_config.UNET_RESTRICTIONS)
params = params_dict.override_params_dict(
params, FLAGS.config_file, is_strict=False)
params = params_dict.override_params_dict(
params, FLAGS.params_overrides, is_strict=False)
params.override(
{
'training_file_pattern': FLAGS.training_file_pattern,
'eval_file_pattern': FLAGS.eval_file_pattern,
'model_dir': FLAGS.model_dir,
'min_eval_interval': FLAGS.min_eval_interval,
'eval_timeout': FLAGS.eval_timeout,
'tpu_config': tpu_executor.get_tpu_flags()
},
is_strict=False)
params.validate()
params.lock()
train_input_fn = None
eval_input_fn = None
if FLAGS.mode in ('train', 'train_and_eval'):
train_input_fn = input_reader.LiverInputFn(
params.training_file_pattern, params, mode=tf.estimator.ModeKeys.TRAIN)
if FLAGS.mode in ('eval', 'train_and_eval'):
eval_input_fn = input_reader.LiverInputFn(
params.eval_file_pattern, params, mode=tf.estimator.ModeKeys.EVAL)
run_executer(
params, train_input_fn=train_input_fn, eval_input_fn=eval_input_fn)