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Minor update the resnet runloop. #4113

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merged 1 commit into from
Apr 27, 2018
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Minor update the resnet runloop. #4113

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33 changes: 17 additions & 16 deletions official/resnet/resnet_run_loop.py
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Original file line number Diff line number Diff line change
Expand Up @@ -401,28 +401,29 @@ def resnet_main(flags, model_function, input_function, shape=None):
benchmark_logger = logger.config_benchmark_logger(flags.benchmark_log_dir)
benchmark_logger.log_run_info('resnet')

for _ in range(flags.train_epochs // flags.epochs_between_evals):
train_hooks = hooks_helper.get_train_hooks(
flags.hooks,
batch_size=flags.batch_size,
benchmark_log_dir=flags.benchmark_log_dir)
train_hooks = hooks_helper.get_train_hooks(
flags.hooks,
batch_size=flags.batch_size,
benchmark_log_dir=flags.benchmark_log_dir)

print('Starting a training cycle.')
def input_fn_train():
return input_function(True, flags.data_dir, flags.batch_size,
flags.epochs_between_evals,
flags.num_parallel_calls, flags.multi_gpu)

def input_fn_train():
return input_function(True, flags.data_dir, flags.batch_size,
flags.epochs_between_evals,
flags.num_parallel_calls, flags.multi_gpu)
def input_fn_eval():
return input_function(False, flags.data_dir, flags.batch_size,
1, flags.num_parallel_calls, flags.multi_gpu)

total_training_cycle = flags.train_epochs // flags.epochs_between_evals
for cycle_index in range(total_training_cycle):
tf.logging.info('Starting a training cycle: %d/%d',
cycle_index, total_training_cycle)

classifier.train(input_fn=input_fn_train, hooks=train_hooks,
max_steps=flags.max_train_steps)

print('Starting to evaluate.')
# Evaluate the model and print results
def input_fn_eval():
return input_function(False, flags.data_dir, flags.batch_size,
1, flags.num_parallel_calls, flags.multi_gpu)

tf.logging.info('Starting to evaluate.')
# flags.max_train_steps is generally associated with testing and profiling.
# As a result it is frequently called with synthetic data, which will
# iterate forever. Passing steps=flags.max_train_steps allows the eval
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