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)