def define_imagenet_flags():
resnet_run_loop.define_resnet_flags(
resnet_size_choices=['18', '34', '50', '101', '152', '200'],
dynamic_loss_scale=True,
fp16_implementation=True)
flags.adopt_module_key_flags(resnet_run_loop)
flags_core.set_defaults(train_epochs=90)
def define_cifar_flags():
resnet_run_loop.define_resnet_flags()
flags.adopt_module_key_flags(resnet_run_loop)
flags_core.set_defaults(data_dir='/tmp/cifar10_data/cifar-10-batches-bin',
model_dir='/tmp/cifar10_model',
resnet_size='56',
train_epochs=182,
epochs_between_evals=10,
batch_size=128,
image_bytes_as_serving_input=False)
def define_cifar_flags():
resnet_run_loop.define_resnet_flags()
flags.adopt_module_key_flags(resnet_run_loop)
flags.DEFINE_bool("use_fs", False, "Use FS coding for Relu")
flags.DEFINE_bool("print_spikes", False,
"Print sum of spikes of fs-neurons")
flags_core.set_defaults(data_dir='/tmp/cifar10_data/cifar-10-batches-bin',
model_dir='/tmp/cifar10_model',
resnet_size='56',
train_epochs=182,
epochs_between_evals=10,
batch_size=128,
use_fs=False,
print_spikes=False,
image_bytes_as_serving_input=False)