def define_classifier_flags():
"""Defines common flags for image classification."""
hyperparams_flags.initialize_common_flags()
flags.DEFINE_string(
'data_dir', default=None, help='The location of the input data.')
flags.DEFINE_string(
'mode',
default=None,
help='Mode to run: `train`, `eval`, `train_and_eval` or `export`.')
flags.DEFINE_bool(
'run_eagerly',
default=None,
help='Use eager execution and disable autograph for debugging.')
flags.DEFINE_string(
'model_type',
default=None,
help='The type of the model, e.g. EfficientNet, etc.')
flags.DEFINE_string(
'dataset',
default=None,
help='The name of the dataset, e.g. ImageNet, etc.')
flags.DEFINE_integer(
'log_steps',
default=100,
help='The interval of steps between logging of batch level stats.')
def define_classifier_flags():
"""Defines common flags for image classification."""
hyperparams_flags.initialize_common_flags()
flags.DEFINE_bool('freeze_lr',
default=False,
help='True if using same lr scheduler after switch')
flags.DEFINE_integer('SWITCH_FROM',
default=-1,
help='The batch size of the checkpoint model.')
flags.DEFINE_integer('SWITCH_TO',
default=-1,
help='The batch size of the current model.')
flags.DEFINE_string('init_chkpt',
default=None,
help='The location of the inital checkpoint.')
flags.DEFINE_string('data_dir',
default=None,
help='The location of the input data.')
flags.DEFINE_string(
'mode',
default=None,
help='Mode to run: `train`, `eval`, `train_and_eval` or `export`.')
flags.DEFINE_bool(
'run_eagerly',
default=None,
help='Use eager execution and disable autograph for debugging.')
flags.DEFINE_string('model_type',
default=None,
help='The type of the model, e.g. EfficientNet, etc.')
flags.DEFINE_string('dataset',
default=None,
help='The name of the dataset, e.g. ImageNet, etc.')
flags.DEFINE_integer(
'log_steps',
default=100,
help='The interval of steps between logging of batch level stats.')
from absl import logging
import tensorflow as tf
from official.common import distribute_utils
from official.modeling.hyperparams import params_dict
from official.utils import hyperparams_flags
from official.utils.flags import core as flags_core
from official.utils.misc import keras_utils
from official.vision.detection.configs import factory as config_factory
from official.vision.detection.dataloader import input_reader
from official.vision.detection.dataloader import mode_keys as ModeKeys
from official.vision.detection.executor import distributed_executor as executor
from official.vision.detection.executor.detection_executor import DetectionDistributedExecutor
from official.vision.detection.modeling import factory as model_factory
hyperparams_flags.initialize_common_flags()
flags_core.define_log_steps()
flags.DEFINE_bool('enable_xla', default=False, help='Enable XLA for GPU')
flags.DEFINE_string('mode',
default='train',
help='Mode to run: `train`, `eval` or `eval_once`.')
flags.DEFINE_string(
'model',
default='retinanet',
help='Model to run: `retinanet`, `mask_rcnn` or `shapemask`.')
flags.DEFINE_string('training_file_pattern', None,
'Location of the train data.')
