def run_imagenet(flags_obj):
"""Run ResNet ImageNet training and eval loop.
Args:
flags_obj: An object containing parsed flag values.
Returns:
Dict of results of the run. Contains the keys `eval_results` and
`train_hooks`. `eval_results` contains accuracy (top_1) and
accuracy_top_5. `train_hooks` is a list the instances of hooks used during
training.
"""
if flags_obj.use_fs:
replace_relu_with_fs()
input_function = (flags_obj.use_synthetic_data and get_synth_input_fn(
flags_core.get_tf_dtype(flags_obj)) or input_fn)
result = resnet_run_loop.resnet_main(
flags_obj,
imagenet_model_fn,
input_function,
DATASET_NAME,
shape=[DEFAULT_IMAGE_SIZE, DEFAULT_IMAGE_SIZE, NUM_CHANNELS])
return result
def run_cifar(flags_obj):
"""Run ResNet CIFAR-10 training and eval loop.
Args:
flags_obj: An object containing parsed flag values.
Returns:
Dictionary of results. Including final accuracy.
"""
if flags_obj.use_fs:
replace_relu_with_fs()
print_spikes = flags_obj.print_spikes
if flags_obj.image_bytes_as_serving_input:
tf.compat.v1.logging.fatal(
'--image_bytes_as_serving_input cannot be set to True for CIFAR. '
'This flag is only applicable to ImageNet.')
return
input_function = (flags_obj.use_synthetic_data and get_synth_input_fn(
flags_core.get_tf_dtype(flags_obj)) or input_fn)
result = resnet_run_loop.resnet_main(flags_obj,
cifar10_model_fn,
input_function,
DATASET_NAME,
shape=[HEIGHT, WIDTH, NUM_CHANNELS])
return result
