def build_inputs(self, params, input_context=None):
input_size = self.task_config.model.input_size
if params.tfds_name:
decoder = simclr_input.TFDSDecoder(params.decoder.decode_label)
else:
decoder = simclr_input.Decoder(params.decoder.decode_label)
parser = simclr_input.Parser(
output_size=input_size[:2],
aug_rand_crop=params.parser.aug_rand_crop,
aug_rand_hflip=params.parser.aug_rand_hflip,
aug_color_distort=params.parser.aug_color_distort,
aug_color_jitter_strength=params.parser.aug_color_jitter_strength,
aug_color_jitter_impl=params.parser.aug_color_jitter_impl,
aug_rand_blur=params.parser.aug_rand_blur,
parse_label=params.parser.parse_label,
test_crop=params.parser.test_crop,
mode=params.parser.mode,
dtype=params.dtype)
reader = input_reader.InputReader(params,
dataset_fn=tf.data.TFRecordDataset,
decoder_fn=decoder.decode,
parser_fn=parser.parse_fn(
params.is_training))
dataset = reader.read(input_context=input_context)
return dataset
def build_inputs(self, params, input_context=None):
input_size = self.task_config.model.input_size
if params.tfds_name:
decoder = simclr_input.TFDSDecoder(params.decoder.decode_label)
else:
decoder = simclr_input.Decoder(params.decoder.decode_label)
parser = simclr_input.Parser(output_size=input_size[:2],
parse_label=params.parser.parse_label,
test_crop=params.parser.test_crop,
mode=params.parser.mode,
dtype=params.dtype)
reader = input_reader.InputReader(params,
dataset_fn=tf.data.TFRecordDataset,
decoder_fn=decoder.decode,
parser_fn=parser.parse_fn(
params.is_training))
dataset = reader.read(input_context=input_context)
return dataset
