Unimplemented Error: TensorArray has size zero - tensorflow

Question

I am getting this weird error when trying to train a sequence to sequence model in tensorflow. The sequence to sequence model is a video captioning system. I have encoded the frames of the videos in sequence features of the SequenceExampleProto. After I prefetch the features containing the list of jpeg encoded strings, I decode them using the following function:
video = tf.map_fn(lambda x: tf.image.decode_jpeg(x, channels=3), encoded_video, dtype=tf.uint8)
The model compiles but during training time, I'm getting the following error which is caused by this code. The error says that the TensorArray is zero, whereas here the TensorArray should not be zero. Any help is appreciated:
tensorflow.python.framework.errors_impl.UnimplementedError: TensorArray has size zero, but element shape [?,?,3] is not fully defined. Currently only static shapes are supported when packing zero-size TensorArrays.
[[Node: input_fn/decode/map/TensorArrayStack/TensorArrayGatherV3 = TensorArrayGatherV3[_class=["loc:#input_fn/decode/map/TensorArray_1"], dtype=DT_UINT8, element_shape=[?,?,3], _device="/job:localhost/replica:0/task:0/cpu:0"](input_fn/decode/map/TensorArray_1, input_fn/decode/map/TensorArrayStack/range, input_fn/decode/map/while/Exit_1/_479)]]
Caused by op u'input_fn/decode/map/TensorArrayStack/TensorArrayGatherV3', defined at:
File "/usr/lib/python2.7/runpy.py", line 162, in _run_module_as_main
"__main__", fname, loader, pkg_name)
File "/usr/lib/python2.7/runpy.py", line 72, in _run_code
exec code in run_globals
File "/home/ubuntu/ASLNet/seq2seq/bin/train.py", line 277, in <module>
tf.app.run()
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/platform/app.py", line 48, in run
_sys.exit(main(_sys.argv[:1] + flags_passthrough))
File "/home/ubuntu/ASLNet/seq2seq/bin/train.py", line 272, in main
schedule=FLAGS.schedule)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/learn_runner.py", line 111, in run
return _execute_schedule(experiment, schedule)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/learn_runner.py", line 46, in _execute_schedule
return task()
File "seq2seq/contrib/experiment.py", line 104, in continuous_train_and_eval
monitors=self._train_monitors)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/util/deprecation.py", line 281, in new_func
return func(*args, **kwargs)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 430, in fit
loss = self._train_model(input_fn=input_fn, hooks=hooks)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 925, in _train_model
features, labels = input_fn()
File "seq2seq/training/utils.py", line 274, in input_fn
frame_format="jpeg")
File "seq2seq/training/utils.py", line 365, in process_video
video = tf.map_fn(lambda x: tf.image.decode_jpeg(x, channels=3), encoded_video, dtype=tf.uint8)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/functional_ops.py", line 390, in map_fn
results_flat = [r.stack() for r in r_a]
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/tensor_array_ops.py", line 301, in stack
return self.gather(math_ops.range(0, self.size()), name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/tensor_array_ops.py", line 328, in gather
element_shape=element_shape)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gen_data_flow_ops.py", line 2244, in _tensor_array_gather_v3
element_shape=element_shape, name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/op_def_library.py", line 768, in apply_op
op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 2336, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 1228, in __init__
self._traceback = _extract_stack()
UnimplementedError (see above for traceback): TensorArray has size zero, but element shape [?,?,3] is not fully defined. Currently only static shapes are supported when packing zero-size TensorArrays.
[[Node: input_fn/decode/map/TensorArrayStack/TensorArrayGatherV3 = TensorArrayGatherV3[_class=["loc:#input_fn/decode/map/TensorArray_1"], dtype=DT_UINT8, element_shape=[?,?,3], _device="/job:localhost/replica:0/task:0/cpu:0"](input_fn/decode/map/TensorArray_1, input_fn/decode/map/TensorArrayStack/range, input_fn/decode/map/while/Exit_1/_479)]]

Answer 1

Fixed. I followed the suggestion from tensorflow map_fn TensorArray has inconsistent shapes and implemented the following:
with tf.name_scope("decode", values=[encoded_video]):
input_jpeg_strings = tf.TensorArray(tf.string, video_length)
input_jpeg_strings = input_jpeg_strings.unstack(encoded_video)
init_array = tf.TensorArray(tf.float32, size=video_length)
def cond(i, ta):
return tf.less(i, video_length)
def body(i, ta):
image = input_jpeg_strings.read(i)
image = tf.image.decode_jpeg(image, 3, name='decode_image')
image = tf.image.convert_image_dtype(image, dtype=tf.float32)
assert (resize_height > 0) == (resize_width > 0)
image = tf.image.resize_images(image, size=[resize_height, resize_width], method=tf.image.ResizeMethod.BILINEAR)
return i + 1, ta.write(i, image)
_, input_image = tf.while_loop(cond, body, [0, init_array])