我试图使用tensorflow和Python3.7运行一个用于训练神经网络的代码,但是出现了这个错误。我是新来的tensorflow有人能给我一个如何解决的提示吗
这是我的错误:UnboundLocalError:赋值前引用的局部变量“train\u diretorio”
这是代码的一部分,如果有人能帮忙的话,我是python和tensorflow的新手
..Imports
def train(): model_config = configuration.ModelConfig() model_config.input_file_pattern = input_file_pattern model_config.inception_checkpoint_file = inception_checkpoint_file training_config = configuration.TrainingConfig() # Create training directory. train_diretorio = train_diretorio if not tf.gfile.IsDirectory(train_diretorio): tf.logging.info("Creating training directory: %s", train_diretorio) tf.gfile.MakeDirs(train_diretorio) # Build the TensorFlow graph. g = tf.Graph() with g.as_default(): # Build the model. model = show_and_tell_model.ShowAndTellModel( model_config, mode="train", train_inception=train_inception) model.build() # Set up the learning rate. learning_rate_decay_fn = None if train_inception: learning_rate = tf.constant(training_config.train_inception_learning_rate) else: learning_rate = tf.constant(training_config.initial_learning_rate) if training_config.learning_rate_decay_factor > 0: num_batches_per_epoch = (training_config.num_examples_per_epoch / model_config.batch_size) decay_steps = int(num_batches_per_epoch * training_config.num_epochs_per_decay) def _learning_rate_decay_fn(learning_rate, global_step): return tf.train.exponential_decay( learning_rate, global_step, decay_steps=decay_steps, decay_rate=training_config.learning_rate_decay_factor, staircase=True) learning_rate_decay_fn = _learning_rate_decay_fn # Set up the training ops. train_op = tf.contrib.layers.optimize_loss( loss=model.total_loss, global_step=model.global_step, learning_rate=learning_rate, optimizer=training_config.optimizer, clip_gradients=training_config.clip_gradients, learning_rate_decay_fn=learning_rate_decay_fn) # Set up the Saver for saving and restoring model checkpoints. saver = tf.train.Saver(max_to_keep=training_config.max_checkpoints_to_keep) # Run training. tf.contrib.slim.learning.train( train_op, train_diretorio, log_every_n_steps=log_every_n_steps, graph=g, global_step=model.global_step, number_of_steps=number_of_steps, init_fn=model.init_fn, saver=saver) input_file_pattern = 'im2txt/data/mscoco/train-?????-of-00256' inception_checkpoint_file = 'im2txt/data/inception_v3.ckpt' train_diretorio = 'im2txt/model' train_inception = False number_of_steps = 1000000 log_every_n_steps = 1 train() train_inception = False number_of_steps = 1000000 log_every_n_steps = 1 train()
目前没有回答
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