def eval_input():
"""Input function returning the entire validation data
set for evaluation. Shuffling is not required.
"""
return input_module.input_fn(
args.eval_files,
batch_size=args.eval_batch_size,
shuffle=False,
num_parallel_calls=args.num_parallel_calls)
def train_input():
"""Input function returning batches from the training
data set from training.
"""
return input_module.input_fn(
args.train_files,
num_epochs=args.num_epochs,
batch_size=args.train_batch_size,
num_parallel_calls=args.num_parallel_calls)
def eval_input():
"""Input function returning the entire validation data
set for evaluation. Shuffling is not required.
"""
return input_module.input_fn(
args.eval_files,
batch_size=args.eval_batch_size,
shuffle=False,
num_parallel_calls=args.num_parallel_calls,
prefetch_buffer_size=args.prefetch_buffer_size)
def train_input():
"""Input function returning batches from the training
data set from training.
"""
return input_module.input_fn(
args.train_files,
num_epochs=args.num_epochs,
batch_size=args.train_batch_size,
num_parallel_calls=args.num_parallel_calls,
prefetch_buffer_size=args.prefetch_buffer_size)
def eval_input(): return input_module.input_fn( args.eval_file, num_epochs=100, shuffle=False, batch_size=1)
def train_input(): return input_module.input_fn( args.training_file, num_epochs=args.num_epochs, shuffle=True, batch_size=args.train_batch_size)