def define_cifar_flags(): keras_common.define_keras_flags(dynamic_loss_scale=False) flags_core.set_defaults(data_dir='/tmp/cifar10_data/cifar-10-batches-bin', model_dir='/tmp/cifar10_model', train_epochs=182, epochs_between_evals=10, batch_size=128)
def _setup(self): """Setups up and resets flags before each test.""" tf.logging.set_verbosity(tf.logging.DEBUG) if KerasCifar10BenchmarkTests.local_flags is None: keras_common.define_keras_flags() cifar_main.define_cifar_flags() # Loads flags to get defaults to then override. List cannot be empty. flags.FLAGS(['foo']) saved_flag_values = flagsaver.save_flag_values() KerasCifar10BenchmarkTests.local_flags = saved_flag_values return flagsaver.restore_flag_values(KerasCifar10BenchmarkTests.local_flags)
def define_imagenet_keras_flags(): keras_common.define_keras_flags() flags_core.set_defaults(train_epochs=90)
num_eval_steps = (imagenet_main.NUM_IMAGES['validation'] // flags_obj.batch_size) validation_data = eval_input_dataset if flags_obj.skip_eval: num_eval_steps = None validation_data = None model.fit(train_input_dataset, epochs=train_epochs, steps_per_epoch=train_steps, callbacks=[time_callback, lr_callback, tensorboard_callback], validation_steps=num_eval_steps, validation_data=validation_data, verbose=1) if not flags_obj.skip_eval: model.evaluate(eval_input_dataset, steps=num_eval_steps, verbose=1) def main(_): with logger.benchmark_context(flags.FLAGS): run(flags.FLAGS) if __name__ == '__main__': tf.logging.set_verbosity(tf.logging.INFO) imagenet_main.define_imagenet_flags() keras_common.define_keras_flags() absl_app.run(main)
steps_per_epoch=train_steps, callbacks=[ time_callback, lr_callback, tensorboard_callback ], validation_steps=num_eval_steps, validation_data=validation_data, validation_freq=flags_obj.epochs_between_evals, verbose=2) eval_output = None if not flags_obj.skip_eval: eval_output = model.evaluate(eval_input_dataset, steps=num_eval_steps, verbose=2) stats = keras_common.build_stats(history, eval_output, time_callback) return stats def main(_): with logger.benchmark_context(flags.FLAGS): return run(flags.FLAGS) if __name__ == '__main__': tf.compat.v1.logging.set_verbosity(tf.compat.v1.logging.INFO) imagenet_main.define_imagenet_flags() keras_common.define_keras_flags() absl_app.run(main)
def define_imagenet_keras_flags(): imagenet_main.define_imagenet_flags(dynamic_loss_scale=True, enable_xla=True) keras_common.define_keras_flags()
def setUpClass(cls): # pylint: disable=invalid-name super(KerasCifarTest, cls).setUpClass() cifar10_main.define_cifar_flags() keras_common.define_keras_flags()
def setUpClass(cls): # pylint: disable=invalid-name super(KerasCifarTest, cls).setUpClass() cifar10_main.define_cifar_flags() keras_common.define_keras_flags()
def setUpClass(cls): # pylint: disable=invalid-name super(KerasImagenetTest, cls).setUpClass() imagenet_main.define_imagenet_flags() keras_common.define_keras_flags()
def define_imagenet_keras_flags(): keras_common.define_keras_flags() flags_core.set_defaults(train_epochs=90) flags.adopt_module_key_flags(keras_common)
def setUpClass(cls): # pylint: disable=invalid-name super(BaseTest, cls).setUpClass() imagenet_main.define_imagenet_flags() keras_common.define_keras_flags()
def setUpClass(cls): # pylint: disable=invalid-name super(CtlImagenetTest, cls).setUpClass() keras_common.define_keras_flags() ctl_common.define_ctl_flags()