tacotron
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Published
20 hours ago •
Kyubyong
Kyubyong
Bus error: 10 at training
Hi,
My question could be stupid but I could not run python train.py on my mac
Here's logs on terminal.
When I use prepro = False,
(tacotron) MacBook-Air:tacotron me$ python train.py
Training Graph loaded
0%| | 0/343 [00:00<?, ?b/s]Bus error: 10
When I use prepro = True,
(tacotron) MacBook-Air:tacotron me$ python train.py
Training Graph loaded
0%| | 0/343 [00:00<?, ?b/s]2018-09-08 11:14:51.345998: W tensorflow/core/framework/op_kernel.cc:1192] Invalid argument: TypeError: a bytes-like object is required, not 'str'
2018-09-08 11:14:51.598145: W tensorflow/core/framework/op_kernel.cc:1192] Invalid argument: TypeError: a bytes-like object is required, not 'str'
2018-09-08 11:14:51.598416: W tensorflow/core/framework/op_kernel.cc:1192] Invalid argument: TypeError: a bytes-like object is required, not 'str'
2018-09-08 11:14:51.598518: W tensorflow/core/framework/op_kernel.cc:1192] Invalid argument: TypeError: a bytes-like object is required, not 'str'
2018-09-08 11:14:51.598628: W tensorflow/core/framework/op_kernel.cc:1192] Invalid argument: TypeError: a bytes-like object is required, not 'str'
2018-09-08 11:14:51.600275: W tensorflow/core/framework/op_kernel.cc:1192] Invalid argument: TypeError: a bytes-like object is required, not 'str'
2018-09-08 11:14:51.600851: W tensorflow/core/framework/op_kernel.cc:1192] Invalid argument: TypeError: a bytes-like object is required, not 'str'
2018-09-08 11:14:51.601028: W tensorflow/core/framework/op_kernel.cc:1192] Invalid argument: TypeError: a bytes-like object is required, not 'str'
2018-09-08 11:14:51.601194: W tensorflow/core/framework/op_kernel.cc:1192] Invalid argument: TypeError: a bytes-like object is required, not 'str'
2018-09-08 11:14:51.602308: W tensorflow/core/framework/op_kernel.cc:1192] Invalid argument: TypeError: a bytes-like object is required, not 'str'
2018-09-08 11:14:51.602480: W tensorflow/core/framework/op_kernel.cc:1192] Invalid argument: TypeError: a bytes-like object is required, not 'str'
2018-09-08 11:14:51.602747: W tensorflow/core/framework/op_kernel.cc:1192] Invalid argument: TypeError: a bytes-like object is required, not 'str'
2018-09-08 11:14:51.684756: W tensorflow/core/framework/op_kernel.cc:1192] Invalid argument: TypeError: a bytes-like object is required, not 'str'
2018-09-08 11:14:53.715177: W tensorflow/core/framework/op_kernel.cc:1192] Invalid argument: TypeError: a bytes-like object is required, not 'str'
2018-09-08 11:14:54.001989: W tensorflow/core/framework/op_kernel.cc:1192] Invalid argument: TypeError: a bytes-like object is required, not 'str'
2018-09-08 11:14:54.287296: W tensorflow/core/framework/op_kernel.cc:1192] Invalid argument: TypeError: a bytes-like object is required, not 'str'
Traceback (most recent call last):
File "/Users/me/anaconda3/envs/tacotron/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1323, in _do_call
return fn(*args)
File "/Users/me/anaconda3/envs/tacotron/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1302, in _run_fn
status, run_metadata)
File "/Users/me/anaconda3/envs/tacotron/lib/python3.6/site-packages/tensorflow/python/framework/errors_impl.py", line 473, in __exit__
c_api.TF_GetCode(self.status.status))
tensorflow.python.framework.errors_impl.OutOfRangeError: FIFOQueue '_1_bucket_by_sequence_length/bucket/top_queue' is closed and has insufficient elements (requested 1, current size 0)
[[Node: bucket_by_sequence_length/bucket/dequeue_top = QueueDequeueV2[component_types=[DT_INT32, DT_INT32, DT_INT32, DT_FLOAT, DT_FLOAT, DT_STRING], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](bucket_by_sequence_length/bucket/top_queue)]]
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/Users/me/anaconda3/envs/tacotron/lib/python3.6/site-packages/tensorflow/python/training/supervisor.py", line 954, in managed_session
yield sess
File "train.py", line 103, in <module>
_, gs = sess.run([g.train_op, g.global_step])
File "/Users/me/anaconda3/envs/tacotron/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 889, in run
run_metadata_ptr)
File "/Users/me/anaconda3/envs/tacotron/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1120, in _run
feed_dict_tensor, options, run_metadata)
File "/Users/me/anaconda3/envs/tacotron/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1317, in _do_run
options, run_metadata)
File "/Users/me/anaconda3/envs/tacotron/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1336, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.OutOfRangeError: FIFOQueue '_1_bucket_by_sequence_length/bucket/top_queue' is closed and has insufficient elements (requested 1, current size 0)
[[Node: bucket_by_sequence_length/bucket/dequeue_top = QueueDequeueV2[component_types=[DT_INT32, DT_INT32, DT_INT32, DT_FLOAT, DT_FLOAT, DT_STRING], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](bucket_by_sequence_length/bucket/top_queue)]]
Caused by op 'bucket_by_sequence_length/bucket/dequeue_top', defined at:
File "train.py", line 96, in <module>
g = Graph(); print("Training Graph loaded")
File "train.py", line 33, in __init__
self.x, self.y, self.z, self.fnames, self.num_batch = get_batch()
File "/Volumes/AI/TTS/tacotron/data_load.py", line 117, in get_batch
dynamic_pad=True)
File "/Users/me/anaconda3/envs/tacotron/lib/python3.6/site-packages/tensorflow/contrib/training/python/training/bucket_ops.py", line 414, in bucket_by_sequence_length
shared_name=shared_name)
File "/Users/me/anaconda3/envs/tacotron/lib/python3.6/site-packages/tensorflow/contrib/training/python/training/bucket_ops.py", line 288, in bucket
dequeued = top_queue.dequeue(name="dequeue_top")
File "/Users/me/anaconda3/envs/tacotron/lib/python3.6/site-packages/tensorflow/python/ops/data_flow_ops.py", line 421, in dequeue
self._queue_ref, self._dtypes, name=name)
File "/Users/me/anaconda3/envs/tacotron/lib/python3.6/site-packages/tensorflow/python/ops/gen_data_flow_ops.py", line 2603, in _queue_dequeue_v2
timeout_ms=timeout_ms, name=name)
File "/Users/me/anaconda3/envs/tacotron/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/Users/me/anaconda3/envs/tacotron/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 2956, in create_op
op_def=op_def)
File "/Users/me/anaconda3/envs/tacotron/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1470, in __init__
self._traceback = self._graph._extract_stack() # pylint: disable=protected-access
OutOfRangeError (see above for traceback): FIFOQueue '_1_bucket_by_sequence_length/bucket/top_queue' is closed and has insufficient elements (requested 1, current size 0)
[[Node: bucket_by_sequence_length/bucket/dequeue_top = QueueDequeueV2[component_types=[DT_INT32, DT_INT32, DT_INT32, DT_FLOAT, DT_FLOAT, DT_STRING], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](bucket_by_sequence_length/bucket/top_queue)]]
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "train.py", line 111, in <module>
plot_alignment(al[0], gs)
File "/Users/me/anaconda3/envs/tacotron/lib/python3.6/contextlib.py", line 99, in __exit__
self.gen.throw(type, value, traceback)
File "/Users/me/anaconda3/envs/tacotron/lib/python3.6/site-packages/tensorflow/python/training/supervisor.py", line 964, in managed_session
self.stop(close_summary_writer=close_summary_writer)
File "/Users/me/anaconda3/envs/tacotron/lib/python3.6/site-packages/tensorflow/python/training/supervisor.py", line 792, in stop
stop_grace_period_secs=self._stop_grace_secs)
File "/Users/me/anaconda3/envs/tacotron/lib/python3.6/site-packages/tensorflow/python/training/coordinator.py", line 389, in join
six.reraise(*self._exc_info_to_raise)
File "/Users/me/anaconda3/envs/tacotron/lib/python3.6/site-packages/six.py", line 693, in reraise
raise value
File "/Users/me/anaconda3/envs/tacotron/lib/python3.6/site-packages/tensorflow/python/training/queue_runner_impl.py", line 238, in _run
enqueue_callable()
File "/Users/me/anaconda3/envs/tacotron/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1231, in _single_operation_run
target_list_as_strings, status, None)
File "/Users/me/anaconda3/envs/tacotron/lib/python3.6/site-packages/tensorflow/python/framework/errors_impl.py", line 473, in __exit__
c_api.TF_GetCode(self.status.status))
tensorflow.python.framework.errors_impl.InvalidArgumentError: TypeError: a bytes-like object is required, not 'str'
[[Node: PyFunc = PyFunc[Tin=[DT_STRING], Tout=[DT_STRING, DT_FLOAT, DT_FLOAT], token="pyfunc_0", _device="/job:localhost/replica:0/task:0/device:CPU:0"](input_producer/Gather)]]
(tacotron) MacBook-Air:tacotron me$
python prepro.py seems to be completed without errors.
Versions: MacOS High Sierra: 10.13.6 Python: 3.6.6 Tensorflow: 1.4.0 numpy: 1.15.1 librosa: 0.6.2 tqdm: 4.25.0 matplotlib : 2.2.3 scipy: 1.1.0
I downloaded LJSpeech-1.1 and modified transcript.csv on data_load.py to metadata.csv because LJSpeech-1.1 don't have transcript.csv.
I used Anaconda to install python and pip for other libraries.
I want to feel how text to speech model works locally.
Thanks in advance.
Hello,kouohhashi. I have a problem as same as yours. I run prepro.py completely and have no errors. but when I run train.py after prepro.py, I got this error. Do you have any idea about this? Thank you very much!
Seemingly solved when I use a requirements.txt as follows
NumPy >= 1.12.1
TensorFlow == 1.3
librosa
tqdm
matplotlib
scipy
hmm. @dwanderton thanks for the comment but with tensorflow==1.3 I still get the same error message:
~/Documents/tacotron]$ python train.py
Training Graph loaded
2018-12-26 14:40:18.411812: 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.
2018-12-26 14:40:18.411836: 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.
2018-12-26 14:40:18.411842: 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.
2018-12-26 14:40:18.411846: 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.
0%| | 0/409 [00:00<?, ?b/s]Bus error: 10
and my pip looks like this (under conda env)
Package Version
---------------------- ----------
absl-py 0.6.1
astor 0.7.1
audioread 2.1.6
bleach 1.5.0
certifi 2018.11.29
cycler 0.10.0
decorator 4.3.0
gast 0.2.0
grpcio 1.17.1
h5py 2.9.0
html5lib 0.9999999
joblib 0.13.0
Keras-Applications 1.0.6
Keras-Preprocessing 1.0.5
kiwisolver 1.0.1
librosa 0.6.2
llvmlite 0.26.0
Markdown 3.0.1
matplotlib 3.0.2
numba 0.41.0
numpy 1.15.4
pip 18.1
protobuf 3.6.1
pyparsing 2.3.0
python-dateutil 2.7.5
resampy 0.2.1
scikit-learn 0.20.2
scipy 1.2.0
setuptools 40.6.3
six 1.12.0
tensorboard 1.12.1
tensorflow 1.3.0
tensorflow-tensorboard 0.1.8
termcolor 1.1.0
tqdm 4.28.1
Werkzeug 0.14.1
wheel 0.32.3
Commenting out a few lines seems to have done the trick.
In the file data_load.py, replace the following block:
if hp.prepro:
def _load_spectrograms(fpath):
fname = os.path.basename(fpath)
mel = "mels/{}".format(fname.replace("wav", "npy"))
mag = "mags/{}".format(fname.replace("wav", "npy"))
return fname, np.load(mel), np.load(mag)
fname, mel, mag = tf.py_func(_load_spectrograms, [fpath], [tf.string, tf.float32, tf.float32])
else:
fname, mel, mag = tf.py_func(load_spectrograms, [fpath], [tf.string, tf.float32, tf.float32]) # (None, n_mels)
With the following:
# if hp.prepro:
# def _load_spectrograms(fpath):
# fname = os.path.basename(fpath)
# mel = "mels/{}".format(fname.replace("wav", "npy"))
# mag = "mags/{}".format(fname.replace("wav", "npy"))
# return fname, np.load(mel), np.load(mag)
# fname, mel, mag = tf.py_func(_load_spectrograms, [fpath], [tf.string, tf.float32, tf.float32])
# else:
fname, mel, mag = tf.py_func(load_spectrograms, [fpath], [tf.string, tf.float32, tf.float32]) # (None, n_mels)
