def __init__(self, params):
self._use_bfloat16 = params.architecture.use_bfloat16
self._l2_weight_decay = params.train.l2_weight_decay
# Optimization.
self._optimizer_fn = OptimizerFactory(params.train.optimizer)
self._learning_rate_fn = learning_rates.learning_rate_generator(
params.train.learning_rate)
self._gradient_clip_norm = params.train.gradient_clip_norm
self._frozen_variable_prefix = params.train.frozen_variable_prefix
# Checkpoint restoration.
self._checkpoint = params.train.checkpoint.path
self._checkpoint_prefix = params.train.checkpoint.prefix
# Summary.
self._enable_summary = params.enable_summary
self._summaries = {}
self._model_dir = params.model_dir
self._iterations_per_loop = params.train.iterations_per_loop
# Platform device.
self._use_tpu = params.use_tpu
def __init__(self, params):
self._transpose_input = params.train.transpose_input
self._space_to_depth_block_size = (
params.architecture.space_to_depth_block_size)
self._use_bfloat16 = params.architecture.use_bfloat16
self._l2_weight_decay = float(params.train.l2_weight_decay)
# Optimization.
self._optimizer_fn = OptimizerFactory(params.train.optimizer)
self._learning_rate_fn = learning_rates.learning_rate_generator(
params.train.learning_rate, params.train.total_steps)
self._gradient_clip_norm = params.train.gradient_clip_norm
self._frozen_var_prefix = params.train.frozen_variable_prefix
self._regularization_var_regex = params.train.regularization_variable_regex
# Checkpoint restoration.
self._checkpoint = params.train.checkpoint.path
self._checkpoint_prefix = params.train.checkpoint.prefix
self._skip_variables_regex = params.train.checkpoint.skip_variables_regex
# Summary.
self._enable_summary = params.enable_summary
self._summaries = {}
self._image_summaries = {}
self._model_dir = params.model_dir
self._iterations_per_loop = params.train.iterations_per_loop
# Platform device.
self._use_tpu = params.use_tpu
def __init__(self, params):
self._use_bfloat16 = params.architecture.use_bfloat16
if params.architecture.use_bfloat16:
policy = tf.compat.v2.keras.mixed_precision.experimental.Policy(
'mixed_bfloat16')
tf.compat.v2.keras.mixed_precision.experimental.set_policy(policy)
# Optimization.
self._optimizer_fn = OptimizerFactory(params.train.optimizer)
self._learning_rate = learning_rates.learning_rate_generator(
params.train.learning_rate)
self._frozen_variable_prefix = params.train.frozen_variable_prefix
self._regularization_var_regex = params.train.regularization_variable_regex
self._l2_weight_decay = params.train.l2_weight_decay
# Checkpoint restoration.
self._checkpoint = params.train.checkpoint.as_dict()
# Summary.
self._enable_summary = params.enable_summary
self._model_dir = params.model_dir