title: AttributeError: 'list' object has no attribute 'value'
body: <p>When I run my code which is downloaded from github to train a CNN model，the unexpected error is occurred.I have searched for similar questions and know the possible reason.But I still can't solve it,have you got an advice?Because the amount of code is large,I try my best to paste some relevant code below.</p>
  <pre><code>class BaseModel(object):
  &quot;&quot;&quot;Base model implementing the training loop and general model interface.&quot;&quot;&quot;
  __metaclass__ = abc.ABCMeta
  
  def __init__(self, inputs, checkpoint_dir, is_training=False,reuse=False):
      &quot;&quot;&quot;Creates a model mapped to a directory on disk for I/O:
  
  Args:
    inputs: input tensor(s), can be placeholders (e.g. for runtime prediction) or
            a queued data_pipeline.
    checkpoint_dir: directory where the trained parameters will be saved/loaded from.
    is_training: allows to parametrize certain layers differently when training (e.g. batchnorm).
    reuse: whether to reuse weights defined by another model.
  &quot;&quot;&quot;
  
      self.inputs = inputs
      self.checkpoint_dir = checkpoint_dir
      self.is_training = is_training
  
      self.layers = {}
      self.summaries = []
      self.eval_summaries = []
  
      self.global_step = tf.Variable(0, name='global_step', trainable=False)
      self._setup_prediction()
      self.saver = tf.compat.v1.train.Saver(tf.compat.v1.global_variables(), max_to_keep=100)
  
  def _tofetch(self):
      &quot;&quot;&quot;Tensors to run/fetch at each training step.
  Returns:
    tofetch: (dict) of Tensors/Ops.
  &quot;&quot;&quot;
      pass
  
  def _train_step(self, sess, start_time, run_options=None, run_metadata=None):
      &quot;&quot;&quot;Step of the training loop.
  Returns:
    data (dict): data from useful for printing in 'summary_step'.
                 Should contain field &quot;step&quot; with the current_step.
  &quot;&quot;&quot;
      tofetch = self._tofetch()
      tofetch['step'] = self.global_step
      tofetch['summaries'] = self.summaries
      data = sess.run(tofetch, options=run_options, run_metadata=run_metadata)
      data['duration'] = time.time() - start_time
      return data
  
  self.summary_writer = tf.compat.v1.summary.FileWriter(self.checkpoint_dir, sess.graph)
  
  self.summary_writer.add_summary(step_data['summaries'], global_step=step)
  </code></pre>
  <p>2021-10-03 14:00:44.444692: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found</p>
  <p>2021-10-03 14:00:44.444956: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.</p>
  <p>WARNING:tensorflow:From D:\school\地球物理\ConvNetQuake-1.0\quakenet\data_pipeline.py:77: TFRecordReader.<strong>init</strong> (from tensorflow.python.ops.io_ops) is deprecated and will be removed in a future version.</p>
  <p>Instructions for updating:
  Queue-based input pipelines have been replaced by <code>tf.data</code>. Use <code>tf.data.TFRecordDataset</code>.</p>
  <p>WARNING:tensorflow:From D:\school\地球物理\ConvNetQuake-1.0\quakenet\data_pipeline.py:92: string_input_producer (from tensorflow.python.training.input) is deprecated and will be removed in a future version.</p>
  <p>Instructions for updating:
  Queue-based input pipelines have been replaced by <code>tf.data</code>. Use <code>tf.data.Dataset.from_tensor_slices(string_tensor).shuffle(tf.shape(input_tensor, out_type=tf.int64)[0]).repeat(num_epochs)</code>. If <code>shuffle=False</code>, omit the <code>.shuffle(...)</code>.</p>
  <p>WARNING:tensorflow:From D:\python\python\lib\site-packages\tensorflow\python\training\input.py:267: input_producer (from tensorflow.python.training.input) is deprecated and will be removed in a future version.</p>
  <p>Instructions for updating:
  Queue-based input pipelines have been replaced by <code>tf.data</code>. Use <code>tf.data.Dataset.from_tensor_slices(input_tensor).shuffle(tf.shape(input_tensor, out_type=tf.int64)[0]).repeat(num_epochs)</code>. If <code>shuffle=False</code>, omit the <code>.shuffle(...)</code>.</p>
  <p>WARNING:tensorflow:From D:\python\python\lib\site-packages\tensorflow\python\training\input.py:189: limit_epochs (from tensorflow.python.training.input) is deprecated and will be removed in a future version.</p>
  <p>Instructions for updating:
  Queue-based input pipelines have been replaced by <code>tf.data</code>. Use <code>tf.data.Dataset.from_tensors(tensor).repeat(num_epochs)</code>.</p>
  <p>WARNING:tensorflow:From D:\python\python\lib\site-packages\tensorflow\python\training\input.py:197: QueueRunner.<strong>init</strong> (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.</p>
  <p>Instructions for updating:
  To construct input pipelines, use the <code>tf.data</code> module.</p>
  <p>WARNING:tensorflow:From D:\python\python\lib\site-packages\tensorflow\python\training\input.py:196: add_queue_runner (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.</p>
  <p>Instructions for updating:
  To construct input pipelines, use the <code>tf.data</code> module.</p>
  <p>WARNING:tensorflow:From D:\school\地球物理\ConvNetQuake-1.0\quakenet\data_pipeline.py:142: shuffle_batch (from tensorflow.python.training.input) is deprecated and will be removed in a future version.</p>
  <p>Instructions for updating:
  Queue-based input pipelines have been replaced by <code>tf.data</code>. Use <code>tf.data.Dataset.shuffle(min_after_dequeue).batch(batch_size)</code>.</p>
  <p>WARNING:tensorflow:From D:\python\python\lib\site-packages\tensorflow\python\util\decorator_utils.py:145: GraphKeys.VARIABLES (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.</p>
  <p>Instructions for updating:
  Use <code>tf.GraphKeys.GLOBAL_VARIABLES</code> instead.</p>
  <p>WARNING:tensorflow:From D:\school\地球物理\ConvNetQuake-1.0\quakenet\models.py:118: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.</p>
  <p>Instructions for updating:
  Use <code>tf.cast</code> instead.</p>
  <p>2021-10-03 14:00:49.467624: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found</p>
  <p>2021-10-03 14:00:49.468871: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cublas64_11.dll'; dlerror: cublas64_11.dll not found</p>
  <p>2021-10-03 14:00:49.470071: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cublasLt64_11.dll'; dlerror: cublasLt64_11.dll not found</p>
  <p>2021-10-03 14:00:49.471424: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cufft64_10.dll'; dlerror: cufft64_10.dll not found</p>
  <p>2021-10-03 14:00:49.472768: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'curand64_10.dll'; dlerror: curand64_10.dll not found</p>
  <p>2021-10-03 14:00:49.474003: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cusolver64_11.dll'; dlerror: cusolver64_11.dll not found</p>
  <p>2021-10-03 14:00:49.475254: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cusparse64_11.dll'; dlerror: cusparse64_11.dll not found</p>
  <p>2021-10-03 14:00:49.476496: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cudnn64_8.dll'; dlerror: cudnn64_8.dll not found</p>
  <p>2021-10-03 14:00:49.476730: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1835] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at <a href="https://www.tensorflow.org/install/gpu" rel="nofollow noreferrer">https://www.tensorflow.org/install/gpu</a> for how to download and setup the required libraries for your platform.</p>
  <p>Skipping registering GPU devices...</p>
  <p>2021-10-03 14:00:49.477635: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX AVX2
  To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.</p>
  <p>Initializing all variables.
  Starting data threads coordinator.
  Starting optimization.</p>
  <p>WARNING:tensorflow:From D:\school\地球物理\ConvNetQuake-1.0\tflib\model.py:242: start_queue_runners (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.</p>
  <p>Instructions for updating:
  To construct input pipelines, use the <code>tf.data</code> module.</p>
  <p>Step 10 | 2s (214ms) | loss = 2.2992 | det. acc. = 50.0% | loc. acc. = 45.3%
  Shutting down data threads.</p>
  <p>2021-10-03 14:00:52.803844: W tensorflow/core/kernels/queue_base.cc:277] _3_inputs_1/input_producer: Skipping cancelled enqueue attempt with queue not closed</p>
  <p>2021-10-03 14:00:52.804091: W tensorflow/core/kernels/queue_base.cc:277] _5_inputs_1/shuffle_batch/random_shuffle_queue: Skipping cancelled enqueue attempt with queue not closed</p>
  <p>Traceback (most recent call last):</p>
  <p>File &quot;D:/school/地球物理/ConvNetQuake-1.0/bin/train&quot;, line 90, in 
  main(args)</p>
  <p>File &quot;D:/school/地球物理/ConvNetQuake-1.0/bin/train&quot;, line 67, in main
  model.train(</p>
  <p>File &quot;D:\school\地球物理\ConvNetQuake-1.0\tflib\model.py&quot;, line 263, in train
  self.summary_writer.add_summary(step_data['summaries'],global_step=step)</p>
  <p>File &quot;D:\python\python\lib\sitepackages\tensorflow\python\summary\writer\writer.py&quot;, line 127, in add_summary
  for value in summary.value:</p>
  <p>AttributeError: 'list' object has no attribute 'value'</p>