[Question] using saliency.py about lipnet HOT 4 CLOSED

Using TensorFlow backend.

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W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
Traceback (most recent call last):
  File "saliency.py", line 65, in <module>
    video, result = predict(sys.argv[1], sys.argv[2])
  File "saliency.py", line 59, in predict
    heatmap = visualize_saliency(lipnet.model, layer_idx, range(0,28), video.data)
  File "/Users/michiyosony/tensorflow/lib/python2.7/site-packages/vis/visualization/saliency.py", line 125, in visualize_saliency
    return visualize_saliency_with_losses(model.input, losses, seed_input, grad_modifier)
  File "/Users/michiyosony/tensorflow/lib/python2.7/site-packages/vis/visualization/saliency.py", line 72, in visualize_saliency_with_losses
    opt = Optimizer(input_tensor, losses, norm_grads=False)
  File "/Users/michiyosony/tensorflow/lib/python2.7/site-packages/vis/optimizer.py", line 58, in __init__
    self.loss_functions + [overall_loss, grads, self.wrt_tensor])
  File "/Users/michiyosony/tensorflow/lib/python2.7/site-packages/keras/backend/tensorflow_backend.py", line 2095, in function
    return Function(inputs, outputs, updates=updates)
  File "/Users/michiyosony/tensorflow/lib/python2.7/site-packages/keras/backend/tensorflow_backend.py", line 2049, in __init__
    with tf.control_dependencies(self.outputs):
  File "/Users/michiyosony/tensorflow/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 3583, in control_dependencies
    return get_default_graph().control_dependencies(control_inputs)
  File "/Users/michiyosony/tensorflow/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 3314, in control_dependencies
    c = self.as_graph_element(c)
  File "/Users/michiyosony/tensorflow/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2405, in as_graph_element
    return self._as_graph_element_locked(obj, allow_tensor, allow_operation)
  File "/Users/michiyosony/tensorflow/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2494, in _as_graph_element_locked
    % (type(obj).__name__, types_str))
TypeError: Can not convert a list into a Tensor or Operation.