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.')