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)