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tflite_model_maker.object_detector.EfficientDetLite2Spec

Creates EfficientDet-Lite2 model spec. See also: tflite_model_maker.object_detector.EfficientDetSpec.

model_name Model name.
uri TF-Hub path/url to EfficientDet module.
hparams Hyperparameters used to overwrite default configuration. Can be

1) Dict, contains parameter names and values; 2) String, Comma separated k=v pairs of hyperparameters; 3) String, yaml filename which's a module containing attributes to use as hyperparameters.

model_dir The location to save the model checkpoint files.
epochs Default training epochs.
batch_size Training & Evaluation batch size.
steps_per_execution Number of steps per training execution.
moving_average_decay Float. The decay to use for maintaining moving averages of the trained parameters.
var_freeze_expr Expression to freeze variables.
tflite_max_detections The max number of output detections in the TFLite model.
strategy A string specifying which distribution strategy to use. Accepted values are 'tpu', 'gpus', None. tpu' means to use TPUStrategy. 'gpus' mean to use MirroredStrategy for multi-gpus. If None, use TF default with OneDeviceStrategy.
tpu The Cloud TPU to use for training. This should be either the name used when creating the Cloud TPU, or a grpc://ip.address.of.tpu:8470 url.
gcp_project Project name for the Cloud TPU-enabled project. If not specified, we will attempt to automatically detect the GCE project from metadata.
tpu_zone GCE zone where the Cloud TPU is located in. If not specified, we will attempt to automatically detect the GCE project from metadata.
use_xla Use XLA even if strategy is not tpu. If strategy is tpu, always use XLA, and this flag has no effect.
profile Enable profile mode.
debug Enable debug mode.
tf_random_seed Fixed random seed for deterministic execution across runs for debugging.
verbose verbosity mode for tf.keras.callbacks.ModelCheckpoint, 0 or 1.