Training Question

I'm training TensorFlow Wavenet on a g2.2xlarge spot instance.
I've restarted training several times after having the instance pre-empted.
How much additional training is necessary?

 Consider decreasing trim_silence threshold, or adjust volume of the audio.

ubuntu@ip-10-0-1-4:~$ !1956
tensorboard --logdir=/hdfs/train
I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcublas.so.7.5 locally
I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcudnn.so.5 locally
I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcufft.so.7.5 locally
I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcuda.so.1 locally
I tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcurand.so.7.5 locally
Starting TensorBoard 41 on port 6006
(You can navigate to http://<IP_ADDRESS>:6006)
----------------------------------------
Exception happened during processing of request from ('<IP_ADDRESS>', 64357)
Traceback (most recent call last):
----------------------------------------
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 599, in process_request_thread
Exception happened during processing of request from ('<IP_ADDRESS>', 64359)
Traceback (most recent call last):
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 599, in process_request_thread
    self.finish_request(request, client_address)
    self.finish_request(request, client_address)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 334, in finish_request
    self.RequestHandlerClass(request, client_address, self)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 334, in finish_request
    self.RequestHandlerClass(request, client_address, self)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 102, in __init__
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 102, in __init__
    BaseHTTPServer.BaseHTTPRequestHandler.__init__(self, *args)
    BaseHTTPServer.BaseHTTPRequestHandler.__init__(self, *args)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 655, in __init__
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 655, in __init__
    self.handle()
    self.handle()
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 340, in handle
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 340, in handle
    self.handle_one_request()
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 328, in handle_one_request
    method()
    self.handle_one_request()
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 530, in do_GET
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 328, in handle_one_request
    self.data_handlers[clean_path](query_params)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 241, in _serve_scalars
    method()
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 530, in do_GET
    values = self._multiplexer.Scalars(run, tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_multiplexer.py", line 237, in Scalars
    self.data_handlers[clean_path](query_params)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 241, in _serve_scalars
    values = self._multiplexer.Scalars(run, tag)
    return accumulator.Scalars(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_multiplexer.py", line 237, in Scalars
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_accumulator.py", line 378, in Scalars
    return accumulator.Scalars(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_accumulator.py", line 378, in Scalars
    return self._scalars.Items(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/impl/reservoir.py", line 104, in Items
    return self._scalars.Items(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/impl/reservoir.py", line 104, in Items
    raise KeyError('Key %s was not found in Reservoir' % key)
KeyError: 'Key wavenet_1/loss/loss was not found in Reservoir'
    raise KeyError('Key %s was not found in Reservoir' % key)
----------------------------------------
KeyError: 'Key wavenet_1/loss/loss was not found in Reservoir'
----------------------------------------
----------------------------------------
Exception happened during processing of request from ('<IP_ADDRESS>', 64363)
Traceback (most recent call last):
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 599, in process_request_thread
    self.finish_request(request, client_address)
----------------------------------------
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 334, in finish_request
    self.RequestHandlerClass(request, client_address, self)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 102, in __init__
Exception happened during processing of request from ('<IP_ADDRESS>', 64361)
Traceback (most recent call last):
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 599, in process_request_thread
    self.finish_request(request, client_address)
    BaseHTTPServer.BaseHTTPRequestHandler.__init__(self, *args)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 334, in finish_request
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 655, in __init__
    self.RequestHandlerClass(request, client_address, self)
    self.handle()
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 102, in __init__
    BaseHTTPServer.BaseHTTPRequestHandler.__init__(self, *args)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 655, in __init__
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 340, in handle
    self.handle()
    self.handle_one_request()
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 340, in handle
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 328, in handle_one_request
    method()
    self.handle_one_request()
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 530, in do_GET
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 328, in handle_one_request
    self.data_handlers[clean_path](query_params)
    method()
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 241, in _serve_scalars
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 530, in do_GET
    self.data_handlers[clean_path](query_params)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 241, in _serve_scalars
    values = self._multiplexer.Scalars(run, tag)
    values = self._multiplexer.Scalars(run, tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_multiplexer.py", line 237, in Scalars
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_multiplexer.py", line 237, in Scalars
    return accumulator.Scalars(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_accumulator.py", line 378, in Scalars
    return accumulator.Scalars(tag)
    return self._scalars.Items(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/impl/reservoir.py", line 104, in Items
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_accumulator.py", line 378, in Scalars
    raise KeyError('Key %s was not found in Reservoir' % key)
    return self._scalars.Items(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/impl/reservoir.py", line 104, in Items
KeyError: 'Key wavenet_1/loss/loss was not found in Reservoir'
----------------------------------------
    raise KeyError('Key %s was not found in Reservoir' % key)
KeyError: 'Key wavenet_1/loss/loss was not found in Reservoir'
----------------------------------------
----------------------------------------
Exception happened during processing of request from ('<IP_ADDRESS>', 64366)
Traceback (most recent call last):
----------------------------------------
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 599, in process_request_thread
Exception happened during processing of request from ('<IP_ADDRESS>', 64367)
Traceback (most recent call last):
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 599, in process_request_thread
    self.finish_request(request, client_address)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 334, in finish_request
    self.finish_request(request, client_address)
    self.RequestHandlerClass(request, client_address, self)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 102, in __init__
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 334, in finish_request
    self.RequestHandlerClass(request, client_address, self)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 102, in __init__
    BaseHTTPServer.BaseHTTPRequestHandler.__init__(self, *args)
    BaseHTTPServer.BaseHTTPRequestHandler.__init__(self, *args)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 655, in __init__
    self.handle()
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 340, in handle
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 655, in __init__
    self.handle_one_request()
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 328, in handle_one_request
    method()
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 530, in do_GET
    self.handle()
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 340, in handle
    self.data_handlers[clean_path](query_params)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 241, in _serve_scalars
    self.handle_one_request()
    values = self._multiplexer.Scalars(run, tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_multiplexer.py", line 237, in Scalars
    return accumulator.Scalars(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_accumulator.py", line 378, in Scalars
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 328, in handle_one_request
    return self._scalars.Items(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/impl/reservoir.py", line 104, in Items
    method()
    raise KeyError('Key %s was not found in Reservoir' % key)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 530, in do_GET
KeyError: 'Key wavenet_1/loss/loss was not found in Reservoir'
----------------------------------------
    self.data_handlers[clean_path](query_params)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 241, in _serve_scalars
    values = self._multiplexer.Scalars(run, tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_multiplexer.py", line 237, in Scalars
    return accumulator.Scalars(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_accumulator.py", line 378, in Scalars
    return self._scalars.Items(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/impl/reservoir.py", line 104, in Items
    raise KeyError('Key %s was not found in Reservoir' % key)
KeyError: 'Key wavenet_1/loss/loss was not found in Reservoir'
----------------------------------------
----------------------------------------
Exception happened during processing of request from ('<IP_ADDRESS>', 64369)
Traceback (most recent call last):
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 599, in process_request_thread
    self.finish_request(request, client_address)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 334, in finish_request
    self.RequestHandlerClass(request, client_address, self)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 102, in __init__
    BaseHTTPServer.BaseHTTPRequestHandler.__init__(self, *args)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 655, in __init__
    self.handle()
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 340, in handle
    self.handle_one_request()
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 328, in handle_one_request
    method()
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 530, in do_GET
    self.data_handlers[clean_path](query_params)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 241, in _serve_scalars
    values = self._multiplexer.Scalars(run, tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_multiplexer.py", line 237, in Scalars
    return accumulator.Scalars(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_accumulator.py", line 378, in Scalars
    return self._scalars.Items(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/impl/reservoir.py", line 104, in Items
    raise KeyError('Key %s was not found in Reservoir' % key)
KeyError: 'Key wavenet_1/loss/loss was not found in Reservoir'
----------------------------------------
----------------------------------------
Exception happened during processing of request from ('<IP_ADDRESS>', 64371)
Traceback (most recent call last):
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 599, in process_request_thread
    self.finish_request(request, client_address)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 334, in finish_request
    self.RequestHandlerClass(request, client_address, self)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 102, in __init__
    BaseHTTPServer.BaseHTTPRequestHandler.__init__(self, *args)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 655, in __init__
    self.handle()
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 340, in handle
    self.handle_one_request()
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 328, in handle_one_request
    method()
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 530, in do_GET
    self.data_handlers[clean_path](query_params)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 241, in _serve_scalars
    values = self._multiplexer.Scalars(run, tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_multiplexer.py", line 237, in Scalars
    return accumulator.Scalars(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_accumulator.py", line 378, in Scalars
    return self._scalars.Items(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/impl/reservoir.py", line 104, in Items
    raise KeyError('Key %s was not found in Reservoir' % key)
KeyError: 'Key wavenet_1/loss/loss was not found in Reservoir'
----------------------------------------
----------------------------------------
Exception happened during processing of request from ('<IP_ADDRESS>', 64373)
Traceback (most recent call last):
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 599, in process_request_thread
----------------------------------------
    self.finish_request(request, client_address)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 334, in finish_request
    self.RequestHandlerClass(request, client_address, self)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 102, in __init__
Exception happened during processing of request from ('<IP_ADDRESS>', 64375)
Traceback (most recent call last):
    BaseHTTPServer.BaseHTTPRequestHandler.__init__(self, *args)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 655, in __init__
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 599, in process_request_thread
    self.finish_request(request, client_address)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 334, in finish_request
    self.handle()
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 340, in handle
    self.handle_one_request()
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 328, in handle_one_request
    method()
    self.RequestHandlerClass(request, client_address, self)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 102, in __init__
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 530, in do_GET
    BaseHTTPServer.BaseHTTPRequestHandler.__init__(self, *args)
    self.data_handlers[clean_path](query_params)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 241, in _serve_scalars
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 655, in __init__
    self.handle()
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 340, in handle
    values = self._multiplexer.Scalars(run, tag)
    self.handle_one_request()
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 328, in handle_one_request
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_multiplexer.py", line 237, in Scalars
    method()
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 530, in do_GET
    return accumulator.Scalars(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_accumulator.py", line 378, in Scalars
    return self._scalars.Items(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/impl/reservoir.py", line 104, in Items
    self.data_handlers[clean_path](query_params)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 241, in _serve_scalars
    values = self._multiplexer.Scalars(run, tag)
    raise KeyError('Key %s was not found in Reservoir' % key)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_multiplexer.py", line 237, in Scalars
KeyError: 'Key wavenet_1/loss/loss was not found in Reservoir'
    return accumulator.Scalars(tag)
----------------------------------------
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_accumulator.py", line 378, in Scalars
    return self._scalars.Items(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/impl/reservoir.py", line 104, in Items
    raise KeyError('Key %s was not found in Reservoir' % key)
KeyError: 'Key wavenet_1/loss/loss was not found in Reservoir'
----------------------------------------
----------------------------------------
Exception happened during processing of request from ('<IP_ADDRESS>', 64377)
Traceback (most recent call last):
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 599, in process_request_thread
    self.finish_request(request, client_address)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 334, in finish_request
    self.RequestHandlerClass(request, client_address, self)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 102, in __init__
    BaseHTTPServer.BaseHTTPRequestHandler.__init__(self, *args)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 655, in __init__
    self.handle()
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 340, in handle
    self.handle_one_request()
----------------------------------------
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 328, in handle_one_request
Exception happened during processing of request from ('<IP_ADDRESS>', 64379)
    method()
Traceback (most recent call last):
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 599, in process_request_thread
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 530, in do_GET
    self.data_handlers[clean_path](query_params)
    self.finish_request(request, client_address)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 241, in _serve_scalars
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 334, in finish_request
    values = self._multiplexer.Scalars(run, tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_multiplexer.py", line 237, in Scalars
    self.RequestHandlerClass(request, client_address, self)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 102, in __init__
    return accumulator.Scalars(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_accumulator.py", line 378, in Scalars
    BaseHTTPServer.BaseHTTPRequestHandler.__init__(self, *args)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 655, in __init__
    return self._scalars.Items(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/impl/reservoir.py", line 104, in Items
    self.handle()
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 340, in handle
    raise KeyError('Key %s was not found in Reservoir' % key)
KeyError: 'Key wavenet_1/loss/loss was not found in Reservoir'
----------------------------------------
    self.handle_one_request()
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 328, in handle_one_request
    method()
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 530, in do_GET
    self.data_handlers[clean_path](query_params)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 241, in _serve_scalars
    values = self._multiplexer.Scalars(run, tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_multiplexer.py", line 237, in Scalars
    return accumulator.Scalars(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_accumulator.py", line 378, in Scalars
    return self._scalars.Items(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/impl/reservoir.py", line 104, in Items
    raise KeyError('Key %s was not found in Reservoir' % key)
KeyError: 'Key wavenet_1/loss/loss was not found in Reservoir'
----------------------------------------
----------------------------------------
Exception happened during processing of request from ('<IP_ADDRESS>', 64381)
Traceback (most recent call last):
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 599, in process_request_thread
    self.finish_request(request, client_address)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 334, in finish_request
----------------------------------------
    self.RequestHandlerClass(request, client_address, self)
Exception happened during processing of request from ('<IP_ADDRESS>', 64383)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 102, in __init__
Traceback (most recent call last):
    BaseHTTPServer.BaseHTTPRequestHandler.__init__(self, *args)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 599, in process_request_thread
    self.finish_request(request, client_address)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 655, in __init__
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 334, in finish_request
    self.RequestHandlerClass(request, client_address, self)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 102, in __init__
    BaseHTTPServer.BaseHTTPRequestHandler.__init__(self, *args)
    self.handle()
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 655, in __init__
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 340, in handle
    self.handle_one_request()
    self.handle()
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 328, in handle_one_request
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 340, in handle
    self.handle_one_request()
    method()
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 328, in handle_one_request
    method()
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 530, in do_GET
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 530, in do_GET
    self.data_handlers[clean_path](query_params)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 241, in _serve_scalars
    values = self._multiplexer.Scalars(run, tag)
    self.data_handlers[clean_path](query_params)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_multiplexer.py", line 237, in Scalars
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 241, in _serve_scalars
    values = self._multiplexer.Scalars(run, tag)
    return accumulator.Scalars(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_multiplexer.py", line 237, in Scalars
    return accumulator.Scalars(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_accumulator.py", line 378, in Scalars
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_accumulator.py", line 378, in Scalars
    return self._scalars.Items(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/impl/reservoir.py", line 104, in Items
    return self._scalars.Items(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/impl/reservoir.py", line 104, in Items
    raise KeyError('Key %s was not found in Reservoir' % key)
KeyError: 'Key wavenet_1/loss/loss was not found in Reservoir'
    raise KeyError('Key %s was not found in Reservoir' % key)
KeyError: 'Key wavenet_1/loss/loss was not found in Reservoir'
----------------------------------------
----------------------------------------
----------------------------------------
Exception happened during processing of request from ('<IP_ADDRESS>', 64385)
 ----------------------------------------
Traceback (most recent call last):
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 599, in process_request_thread
    self.finish_request(request, client_address)
Exception happened during processing of request from ('<IP_ADDRESS>', 64387)
Traceback (most recent call last):
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 599, in process_request_thread
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 334, in finish_request
    self.RequestHandlerClass(request, client_address, self)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 102, in __init__
    self.finish_request(request, client_address)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 334, in finish_request
    BaseHTTPServer.BaseHTTPRequestHandler.__init__(self, *args)
    self.RequestHandlerClass(request, client_address, self)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 102, in __init__
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 655, in __init__
    BaseHTTPServer.BaseHTTPRequestHandler.__init__(self, *args)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 655, in __init__
    self.handle()
    self.handle()
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 340, in handle
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 340, in handle
    self.handle_one_request()
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 328, in handle_one_request
    method()
    self.handle_one_request()
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 530, in do_GET
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 328, in handle_one_request
    self.data_handlers[clean_path](query_params)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 241, in _serve_scalars
    values = self._multiplexer.Scalars(run, tag)
    method()
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_multiplexer.py", line 237, in Scalars
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 530, in do_GET
    return accumulator.Scalars(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_accumulator.py", line 378, in Scalars
    self.data_handlers[clean_path](query_params)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 241, in _serve_scalars
    return self._scalars.Items(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/impl/reservoir.py", line 104, in Items
    values = self._multiplexer.Scalars(run, tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_multiplexer.py", line 237, in Scalars
    raise KeyError('Key %s was not found in Reservoir' % key)
KeyError: 'Key wavenet_1/loss/loss was not found in Reservoir'
    return accumulator.Scalars(tag)
----------------------------------------
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_accumulator.py", line 378, in Scalars
    return self._scalars.Items(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/impl/reservoir.py", line 104, in Items
    raise KeyError('Key %s was not found in Reservoir' % key)
KeyError: 'Key wavenet_1/loss/loss was not found in Reservoir'
----------------------------------------
----------------------------------------
Exception happened during processing of request from ('<IP_ADDRESS>', ----------------------------------------
64389)
Traceback (most recent call last):
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 599, in process_request_thread
Exception happened during processing of request from ('<IP_ADDRESS>', 64391)
    self.finish_request(request, client_address)
Traceback (most recent call last):
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 599, in process_request_thread
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 334, in finish_request
    self.finish_request(request, client_address)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 334, in finish_request
    self.RequestHandlerClass(request, client_address, self)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 102, in __init__
    self.RequestHandlerClass(request, client_address, self)
    BaseHTTPServer.BaseHTTPRequestHandler.__init__(self, *args)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 655, in __init__
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 102, in __init__
    BaseHTTPServer.BaseHTTPRequestHandler.__init__(self, *args)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 655, in __init__
    self.handle()
    self.handle()
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 340, in handle
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 340, in handle
    self.handle_one_request()
    self.handle_one_request()
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 328, in handle_one_request
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 328, in handle_one_request
    method()
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 530, in do_GET
    method()
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 530, in do_GET
    self.data_handlers[clean_path](query_params)
    self.data_handlers[clean_path](query_params)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 241, in _serve_scalars
    values = self._multiplexer.Scalars(run, tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 241, in _serve_scalars
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_multiplexer.py", line 237, in Scalars
    values = self._multiplexer.Scalars(run, tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_multiplexer.py", line 237, in Scalars
    return accumulator.Scalars(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_accumulator.py", line 378, in Scalars
    return accumulator.Scalars(tag)
    return self._scalars.Items(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/impl/reservoir.py", line 104, in Items
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_accumulator.py", line 378, in Scalars
    return self._scalars.Items(tag)
    raise KeyError('Key %s was not found in Reservoir' % key)
KeyError: 'Key wavenet_1/loss/loss was not found in Reservoir'
----------------------------------------
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/impl/reservoir.py", line 104, in Items
    raise KeyError('Key %s was not found in Reservoir' % key)
KeyError: 'Key wavenet_1/loss/loss was not found in Reservoir'
----------------------------------------
----------------------------------------
Exception happened during processing of request from ('<IP_ADDRESS>', ----------------------------------------
Exception happened during processing of request from64395 ('<IP_ADDRESS>', 64393)
Traceback (most recent call last):
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 599, in process_request_thread
    self.finish_request(request, client_address)
)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 334, in finish_request
Traceback (most recent call last):
    self.RequestHandlerClass(request, client_address, self)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 599, in process_request_thread
    self.finish_request(request, client_address)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 102, in __init__
    BaseHTTPServer.BaseHTTPRequestHandler.__init__(self, *args)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 334, in finish_request
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 655, in __init__
    self.handle()
    self.RequestHandlerClass(request, client_address, self)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 102, in __init__
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 340, in handle
    BaseHTTPServer.BaseHTTPRequestHandler.__init__(self, *args)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 655, in __init__
    self.handle_one_request()
    self.handle()
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 340, in handle
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 328, in handle_one_request
    method()
    self.handle_one_request()
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 530, in do_GET
    self.data_handlers[clean_path](query_params)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 241, in _serve_scalars
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 328, in handle_one_request
    values = self._multiplexer.Scalars(run, tag)
    method()
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_multiplexer.py", line 237, in Scalars
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 530, in do_GET
    return accumulator.Scalars(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_accumulator.py", line 378, in Scalars
    self.data_handlers[clean_path](query_params)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 241, in _serve_scalars
    values = self._multiplexer.Scalars(run, tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_multiplexer.py", line 237, in Scalars
    return self._scalars.Items(tag)
    return accumulator.Scalars(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/impl/reservoir.py", line 104, in Items
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_accumulator.py", line 378, in Scalars
    raise KeyError('Key %s was not found in Reservoir' % key)
    return self._scalars.Items(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/impl/reservoir.py", line 104, in Items
KeyError: 'Key wavenet_1/loss/loss was not found in Reservoir'
----------------------------------------
    raise KeyError('Key %s was not found in Reservoir' % key)
KeyError: 'Key wavenet_1/loss/loss was not found in Reservoir'
----------------------------------------
----------------------------------------
Exception happened during processing of request from ('<IP_ADDRESS>', 64397)
Traceback (most recent call last):
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 599, in process_request_thread
    self.finish_request(request, client_address)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 334, in finish_request
    self.RequestHandlerClass(request, client_address, self)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 102, in __init__
----------------------------------------
    BaseHTTPServer.BaseHTTPRequestHandler.__init__(self, *args)
Exception happened during processing of request from ('<IP_ADDRESS>', 64399)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 655, in __init__
Traceback (most recent call last):
    self.handle()
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 599, in process_request_thread
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 340, in handle
    self.finish_request(request, client_address)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 334, in finish_request
    self.RequestHandlerClass(request, client_address, self)
    self.handle_one_request()
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 328, in handle_one_request
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 102, in __init__
    method()
    BaseHTTPServer.BaseHTTPRequestHandler.__init__(self, *args)
  File "/home/ubuntu/anaconda/lib/python2.7/SocketServer.py", line 655, in __init__
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 530, in do_GET
    self.handle()
    self.data_handlers[clean_path](query_params)
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 340, in handle
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 241, in _serve_scalars
    values = self._multiplexer.Scalars(run, tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_multiplexer.py", line 237, in Scalars
    self.handle_one_request()
  File "/home/ubuntu/anaconda/lib/python2.7/BaseHTTPServer.py", line 328, in handle_one_request
    method()
    return accumulator.Scalars(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_accumulator.py", line 378, in Scalars
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 530, in do_GET
    return self._scalars.Items(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/impl/reservoir.py", line 104, in Items
    self.data_handlers[clean_path](query_params)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/tensorboard/backend/handler.py", line 241, in _serve_scalars
    values = self._multiplexer.Scalars(run, tag)
    raise KeyError('Key %s was not found in Reservoir' % key)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_multiplexer.py", line 237, in Scalars
    return accumulator.Scalars(tag)
KeyError: 'Key wavenet_1/loss/loss was not found in Reservoir'
----------------------------------------
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/event_accumulator.py", line 378, in Scalars
    return self._scalars.Items(tag)
  File "/home/ubuntu/anaconda/lib/python2.7/site-packages/tensorflow/python/summary/impl/reservoir.py", line 104, in Items
    raise KeyError('Key %s was not found in Reservoir' % key)
KeyError: 'Key wavenet_1/loss/loss was not found in Reservoir'
----------------------------------------
WARNING:tensorflow:Found more than one graph event per run, or there was a metagraph containing a graph_def, as well as one or more graph events.  Overwriting the graph with the newest event.
WARNING:tensorflow:Found more than one graph event per run, or there was a metagraph containing a graph_def, as well as one or more graph events.  Overwriting the graph with the newest event.
WARNING:tensorflow:Found more than one graph event per run, or there was a metagraph containing a graph_def, as well as one or more graph events.  Overwriting the graph with the newest event.
WARNING:tensorflow:Found more than one graph event per run, or there was a metagraph containing a graph_def, as well as one or more graph events.  Overwriting the graph with the newest event.
WARNING:tensorflow:Found more than one graph event per run, or there was a metagraph containing a graph_def, as well as one or more graph events.  Overwriting the graph with the newest event.

The amount of training you need will depend on your training data and your parameters specified in wavenet_params.json file. That said, from https://github.com/ibab/tensorflow-wavenet/issues/195 it sounds like people need around 88k steps to reach convergence on VLTK, and sometime train on as much as 100's of thousands of iterations for other datasets.
I tried training WaveNet models on AWS, and in my experience, it was actually more economical just to buy a 1070 GTX and be able to run it for several days continuously at home (I actually had to buy a whole new computer since I only have a laptop, but it's still cheaper since I can just resell the thing to a gamer on Craigslist when I'm done running WaveNet experiments XD).

Would WaveNet training benefit from tensor2tensor?

On Apr 15, 2017, at 4:35 PM, Devin Platt<EMAIL_ADDRESS>wrote:
The amount of training you need will depend on your training data and your parameters specified in wavenet_params.json file. That said, from #195 https://github.com/ibab/tensorflow-wavenet/issues/195 it sounds like people need around 88k steps to reach convergence on VLTK, and sometime train on as much as 100's of thousands of iterations for other datasets.
I tried training WaveNet models on AWS, and in my experience, it was actually more economical just to buy a 1070 GTX and be able to run it for several days continuously at home (I actually had to buy a whole new computer since I only have a laptop, but it's still cheaper since I can just resell the thing to a gamer on Craigslist when I'm done running WaveNet experiments XD).
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub https://github.com/ibab/tensorflow-wavenet/issues/249#issuecomment-294323974, or mute the thread https://github.com/notifications/unsubscribe-auth/AC9i2_RdWZ4x0azyIFUdKCxQ02SO1Xaiks5rwVQygaJpZM4Mx1lN.


support for sunos5 in get_machine_id()

.. to get tests passed on illumos.

Is this an operating system still used in the wild nowadays? seems a bit esoteric, so not sure if we want explicit code for it, especially in a pure development util

Is this an operating system still used in the wild nowadays? seems a bit esoteric, so not sure if we want explicit code for it, especially in a pure development util

Of course, it is.  An illumos distro: https://www.openindiana.org/

Thanks, but I don't plan to merge this. It implies a level of support we can't provide. The debugger will still work without this (and note that the dev server and debugger should never be accessible externally anyway, so being able to generate a more random pin is the last thing to worry about).

Okay, np.  Your project, your rules. :-)


[tool_crash] Invalid argument(s): Cannot find executable for /Volumes/Mac/flutter/bin/cache/artifacts/engine/ios-release/gen_snapshot_x86_64.

Command
flutter assemble --output=/Volumes/Mac/work/iEnglish/code/flutter_ienglish_fine/ios/Flutter/ -dTargetPlatform=ios -dTargetFile=/Volumes/Mac/work/iEnglish/code/flutter_ienglish_fine/lib/main.dart -dBuildMode=release -dIosArchs=x86_64 -dSplitDebugInfo= -dTreeShakeIcons=false -dTrackWidgetCreation=true -dDartObfuscation=false -dEnableBitcode= --DartDefines=flutter.inspector.structuredErrors=true -dExtraFrontEndOptions= release_ios_bundle_flutter_assets

Steps to Reproduce

...
...
...

Logs
ArgumentError: Invalid argument(s): Cannot find executable for /Volumes/Mac/flutter/bin/cache/artifacts/engine/ios-release/gen_snapshot_x86_64.
#0      _getExecutable (package:process/src/interface/local_process_manager.dart:127:5)
#1      LocalProcessManager.start (package:process/src/interface/local_process_manager.dart:43:30)
#2      _DefaultProcessUtils.start (package:flutter_tools/src/base/process.dart:462:28)
#3      _DefaultProcessUtils.stream (package:flutter_tools/src/base/process.dart:480:35)
#4      GenSnapshot.run (package:flutter_tools/src/base/build.dart:74:26)
#5      AOTSnapshotter.build (package:flutter_tools/src/base/build.dart:198:56)
#6      AotAssemblyBase.build (package:flutter_tools/src/build_system/targets/ios.dart:69:31)
#7      _BuildInstance._invokeInternal (package:flutter_tools/src/build_system/build_system.dart:614:25)
<asynchronous suspension>
#8      _BuildInstance.invokeTarget.<anonymous closure> (package:flutter_tools/src/build_system/build_system.dart:569:35)
#9      new Future.sync (dart:async/future.dart:224:31)
#10     AsyncMemoizer.runOnce (package:async/src/async_memoizer.dart:43:45)
#11     _BuildInstance.invokeTarget (package:flutter_tools/src/build_system/build_system.dart:569:21)
<asynchronous suspension>
<asynchronous suspension>
#12     BuildSystem.build (package:flutter_tools/src/build_system/build_system.dart:498:36)
#13     AssembleCommand.runCommand (package:flutter_tools/src/commands/assemble.dart:189:58)
#14     FlutterCommand.verifyThenRunCommand (package:flutter_tools/src/runner/flutter_command.dart:722:18)
<asynchronous suspension>
#15     FlutterCommand.run.<anonymous closure> (package:flutter_tools/src/runner/flutter_command.dart:619:33)

[✓] Flutter (Channel stable, v1.17.0, on Mac OS X 10.15.5 19F101, locale zh-Hans-CN)
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Hi @ihsh,
Please see this related issue. You seem to be on old version of Flutter. I'd suggest you to upgrade to latest stable or master and try again. This issue was fixed and merged.
duplicate of https://github.com/flutter/flutter/issues/65924
Thanks.

Ok kill/
Sent from my iPhone

On 17 Sep 2020, at 23:08, Taha Tesser<EMAIL_ADDRESS>wrote:

Closed #66018.
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Ok thx


Added review mode

Upon completing a quiz, the user will now be able to review the questions they got wrong.

Upon completing the review, the usual restart functionality will be called.

Awesome rocket
Just one thing: can we add the "restart" button next to the "next" button to skip the review process?

Yeah of course, I've added a "Skip review" button, since I think a "normal" user should always review


Eval clears all variables

Hey,
I have a small TICKscript for monitoring when the server runs out of free disk space. Looks like this:
// Alerts when more than 3 GB + 10% of the server total disk space are used up.

var gb = 1000 * 1000 * 1000

stream
	|from()
		.measurement('disk')
// Some unexplainable magic happens with this eval. It would be lovely to use but as long as
// it breaks everything, let it be commented out.
//	|eval(lambda: "free" / gb)
//	        .as('free_gb')
//		.keep('free', 'total', 'used', 'used_percent')
	|groupBy('host', 'path')
	|window()
		.period(30s)
		.every(30s)
	|alert()
		.id('Free disk space @ {{ index .Tags "host" }}')
		.message('{{ .ID }} is {{ .Level }}! {{ index .Fields "used_percent" | printf "%0.2f" }}% is used up.')

		.crit(lambda: gb / 2 + "total" / 100 * 10 > "free")
		.warn(lambda: 3 * gb + "total" / 100 * 10 > "free")
		.stateChangesOnly(12h)

		.email()
		.slack()

		.log('/var/log/kapacitor/low_disk.log')

PS. Although Github displays it weird, I don't have indentation like that in the actual script.
Problem is the commented out |eval() part that for some reason clears all my incoming variables and if I comment that in, no alerts are triggered since all variables are <nil>. Is this desired behavior? I guess one problem might be that I'm passing more variables to keep() than are changed in that |eval(), but I tried it with only free as well and got the same results. It seems to me that I copied the |eval() directly from documentation and can't figure out what's wrong with it.
But the reason I need it at all is that the incoming data gives free space on disk in bytes and I would like to send out MB-s or GB-s instead of<PHONE_NUMBER> bytes. :) So another question, is there a way to
a) add the eval() output to message()?
or b) do that in any other way? I tried to do some magic with the printf thingie, but I couldn't find any documentation for it anywhere so didn't get anywhere with that either.
I'm running on a 64bit Ubuntu 14.04 and have the latest Kapacitor installed from https://dl.influxdata.com/kapacitor/releases/kapacitor_1.0.2_amd64.deb.

@wanaryytel Your example looks correct. Can you share some sample data that can reproduce the error?

@nathanielc How should that data be gathered? By recording and saving it to a file?

Sure that works well, the recording data files are stored in /var/lib/kapacitor/replays by default. Or just a text file with line protocol that reproduces the error would be enough. Thanks

@nathanielc Is there a way to go through the .srpl file data to make sure there isn't any sensitive data in that? It seems to be binary format by default. Or another way to get the output of the recording?

@wanaryytel Sure, the .srpl file is really just gzipped text data so you can extract it and take a look.

@nathanielc
Here you go :)
8b940579-27f7-4d90-9a91-cdf74e1ad96d.txt

@nathanielc Hey, I updated to the latest release but it didn't fix the problem. I think you missed the part in the initial description that said "I guess one problem might be that I'm passing more variables to keep() than are changed in that |eval(), but I tried it with only free as well and got the same results."
That's exactly what I'm seeing. Output from the same script's kapactior show low_disk:
`ID: low_disk
Error:
Template:
Type: stream
Status: enabled
Executing: true
Created: 20 Oct 16 06:55 EDT
Modified: 06 Nov 16 17:35 EST
LastEnabled: 06 Nov 16 17:35 EST
Databases Retention Policies: ["telegraf"."autogen"]
TICKscript:
// Alerts when more than 3 GB + 10% of the server total disk space are used up.
var gb = 1000 * 1000 * 1000
stream
|from()
.measurement('disk')
// Some unexplainable magic happens with this eval. It would be lovely to use but as long as
// it breaks everything, let it be commented out.
|eval(lambda: "free" / gb)
.as('free_gb')
.keep('free', 'free_gb')
|groupBy('host', 'path')
|window()
.period(30s)
.every(30s)
|alert()
.id('Free disk space @ {{ index .Tags "host" }}')
.message('{{ .ID }} is {{ .Level }}! {{ index .Fields "used_percent" | printf "%0.2f" }}% is used up.')
.crit(lambda: gb / 2 + "total" / 100 * 10 > "free")
.warn(lambda: 3 * gb + "total" / 100 * 10 > "free")
// 		.stateChangesOnly(12h)
.email()
.slack()
.log('/var/log/kapacitor/low_disk.log')
DOT:
digraph low_disk {
graph [throughput="0.00 points/s"];
stream0 [avg_exec_time_ns="0" ];
stream0 -> from1 [processed="69"];
from1 [avg_exec_time_ns="6.097µs" ];
from1 -> eval2 [processed="69"];
eval2 [avg_exec_time_ns="114.429µs" eval_errors="0" ];
eval2 -> groupby3 [processed="69"];
groupby3 [avg_exec_time_ns="4.01µs" ];
groupby3 -> window4 [processed="69"];
window4 [avg_exec_time_ns="5.229µs" ];
window4 -> alert5 [processed="13"];
alert5 [alerts_triggered="0" avg_exec_time_ns="320.375µs" crits_triggered="0" infos_triggered="0" oks_triggered="0" warns_triggered="0" ];
stats6 [avg_exec_time_ns="0" ];
stats6 -> derivative7 [processed="6"];
derivative7 [avg_exec_time_ns="0" ];
derivative7 -> alert8 [processed="5"];
alert8 [alerts_triggered="5" avg_exec_time_ns="763.275µs" crits_triggered="5" infos_triggered="0" oks_triggered="0" warns_triggered="0" ];
}
`
No alerts are triggered with this script. When I comment out the eval, everything works fine.

@wanaryytel I tested this again with your replay file and the above script. It works as is. Both the free and free_gb fields exist on the data when it is passed to the alert node.
Specifically which version did you test?

@nathanielc Both v1.0.2 and v1.1.0-rc2. Exactly the same behavior. I'm not 100% sure if all the variables are cleared, but when the eval is commented in, no alerts are triggered. It was just my assumption that when all variables are undefined, then that could be a probable reason for not triggering alerts.

@wanaryytel Hmm, that is odd.
Can you try this TICKscript? It just has a few log nodes added in:
stream
    |from()
        .measurement('disk')
    // Some unexplainable magic happens with this eval. It would be lovely to use but as long as
    // it breaks everything, let it be commented out.
    |log()
        .prefix('PRE EVAL')
    |eval(lambda: "free" / gb)
        .as('free_gb')
        .keep('free', 'free_gb')
    |log()
        .prefix('POST EVAL')
    |groupBy('host', 'path')
    |window()
        .period(30s)
        .every(30s)
    |alert()
        .id('Free disk space @ `{{ index .Tags "host" }}`')
        .message('{{ .ID }} is *{{ .Level }}*! {{ index .Fields "used_percent" | printf "%0.2f" }}% is used up.')
        .crit(lambda: gb / 2 + "total" / 100 * 10 > "free")
        .warn(lambda: 3 * gb + "total" / 100 * 10 > "free")
        //      .stateChangesOnly(12h)
        .email()
        .slack()
        .log('/var/log/kapacitor/low_disk.log')

Then could you share the log lines that start with PRE/POST EVAL? That should help us get to the bottom of what is going on.

@nathanielc Ran your script (and added the gb variable at the start) for about 5 minutes, but again - no alerts triggered and no log file created for it.
ID: ld
Error:
Template:
Type: stream
Status: enabled
Executing: true
Created: 08 Nov 16 04:54 EST
Modified: 08 Nov 16 04:54 EST
LastEnabled: 08 Nov 16 04:54 EST
Databases Retention Policies: ["telegraf"."autogen"]
TICKscript:
var gb = 1000 * 1000 * 1000

stream
    |from()
        .measurement('disk')
    // Some unexplainable magic happens with this eval. It would be lovely to use but as long as
    // it breaks everything, let it be commented out.
    |log()
        .prefix('PRE EVAL')
    |eval(lambda: "free" / gb)
        .as('free_gb')
        .keep('free', 'free_gb')
    |log()
        .prefix('POST EVAL')
    |groupBy('host', 'path')
    |window()
        .period(30s)
        .every(30s)
    |alert()
        .id('Free disk space @ `{{ index .Tags "host" }}`')
        .message('{{ .ID }} is *{{ .Level }}*! {{ index .Fields "used_percent" | printf "%0.2f" }}% is used up.')
        .crit(lambda: gb / 2 + "total" / 100 * 10 > "free")
        .warn(lambda: 3 * gb + "total" / 100 * 10 > "free")
        //      .stateChangesOnly(12h)
        .email()
        .slack()
        .log('/var/log/kapacitor/ld.log')

DOT:
digraph ld {
graph [throughput="0.00 points/s"];

stream0 [avg_exec_time_ns="0s" ];
stream0 -> from1 [processed="253"];

from1 [avg_exec_time_ns="8.359µs" ];
from1 -> log2 [processed="253"];

log2 [avg_exec_time_ns="0s" ];
log2 -> eval3 [processed="253"];

eval3 [avg_exec_time_ns="59.18µs" eval_errors="0" ];
eval3 -> log4 [processed="253"];

log4 [avg_exec_time_ns="0s" ];
log4 -> groupby5 [processed="253"];

groupby5 [avg_exec_time_ns="3.283µs" ];
groupby5 -> window6 [processed="253"];

window6 [avg_exec_time_ns="16.909µs" ];
window6 -> alert7 [processed="70"];

alert7 [alerts_triggered="0" avg_exec_time_ns="464.241µs" crits_triggered="0" infos_triggered="0" oks_triggered="0" warns_triggered="0" ];

stats8 [avg_exec_time_ns="13.33µs" ];
stats8 -> derivative9 [processed="23"];

derivative9 [avg_exec_time_ns="5.774µs" ];
derivative9 -> alert10 [processed="22"];

alert10 [alerts_triggered="22" avg_exec_time_ns="0s" crits_triggered="22" infos_triggered="0" oks_triggered="0" warns_triggered="0" ];
}

File at /var/log/kapacitor/ld.log wasn't created, but I do have logfiles for all the other scripts that don't include an eval function. Also checked the kapacitord.err log, which indicated that everything was fine. Any more ideas what I could try?

Can you check the /var/log/kapacitor/kapacitor.log file? It will have the PRE EVAL and POST EVAL log lines so we can determine what might be causing the issue.

@nathanielc
Hey,
here's an excerpt:
[ld:log2] 2016/11/15 17:27:01 I! PRE EVAL {"Name":"disk","Database":"telegraf","RetentionPolicy":"autogen","Group":"","Dimensions":{"ByName":false,"TagNames":null},"Tags":{"dc":"eu-west-1","fstype":"ext4","host":"host1.company.com","hosttype":"alfa","path":"/","provider":"big"},"Fields":{"free":7524429824,"inodes_free":838045,"inodes_total":1310720,"inodes_used":472675,"total":21137846272,"used":12539834368,"used_percent":62.4983515368576},"Time":"2016-11-15T22:27:00Z"}

[ld:log2] 2016/11/15 17:27:01 I! PRE EVAL {"Name":"disk","Database":"telegraf","RetentionPolicy":"autogen","Group":"","Dimensions":{"ByName":false,"TagNames":null},"Tags":{"dc":"eu-west-1","fstype":"ext3","host":"host1.company.com","hosttype":"alfa","path":"/disk","provider":"big"},"Fields":{"free":3931746304,"inodes_free":262133,"inodes_total":262144,"inodes_used":11,"total":4221763584,"used":75558912,"used_percent":1.8855292503878998},"Time":"2016-11-15T22:27:00Z"}

[ld:log2] 2016/11/15 17:27:01 I! PRE EVAL {"Name":"disk","Database":"telegraf","RetentionPolicy":"autogen","Group":"","Dimensions":{"ByName":false,"TagNames":null},"Tags":{"dc":"eu-west-1","fstype":"ext4","host":"host1.company.com","hosttype":"alfa","path":"/disk2","provider":"big"},"Fields":{"free":17060515840,"inodes_free":1310544,"inodes_total":1310720,"inodes_used":176,"total":21137846272,"used":3003588608,"used_percent":14.969960985721439},"Time":"2016-11-15T22:27:00Z"}

[ld:log4] 2016/11/15 17:27:01 I! POST EVAL {"Name":"disk","Database":"telegraf","RetentionPolicy":"autogen","Group":"","Dimensions":{"ByName":false,"TagNames":null},"Tags":{"dc":"eu-west-1","fstype":"ext4","host":"host1.company.com","hosttype":"alfa","path":"/","provider":"big"},"Fields":{"free":7524429824,"free_gb":7},"Time":"2016-11-15T22:27:00Z"}

[ld:log4] 2016/11/15 17:27:01 I! POST EVAL {"Name":"disk","Database":"telegraf","RetentionPolicy":"autogen","Group":"","Dimensions":{"ByName":false,"TagNames":null},"Tags":{"dc":"eu-west-1","fstype":"ext3","host":"host1.company.com","hosttype":"alfa","path":"/disk","provider":"big"},"Fields":{"free":3931746304,"free_gb":3},"Time":"2016-11-15T22:27:00Z"}

[ld:log4] 2016/11/15 17:27:01 I! POST EVAL {"Name":"disk","Database":"telegraf","RetentionPolicy":"autogen","Group":"","Dimensions":{"ByName":false,"TagNames":null},"Tags":{"dc":"eu-west-1","fstype":"ext4","host":"host1.company.com","hosttype":"alfa","path":"/disk2","provider":"big"},"Fields":{"free":17060515840,"free_gb":17},"Time":"2016-11-15T22:27:00Z"}

@wanaryytel Great, the logs show that the fields are being kept correctly. As for why the alert is not triggering it seems to be a different issue. Could it be that these conditions are not correct?
        .crit(lambda: gb / 2 + "total" / 100 * 10 > "free")
        .warn(lambda: 3 * gb + "total" / 100 * 10 > "free")

@nathanielc It is the first thing that comes to mind, but considering

I have another script (without eval) that has the same threshold values that does alert me with the same data
I have tried much higher thresholds with no avail

it seems improbable at best.
Is there anything else I can try?

@wanaryytel Use the |log() to debug why your alert is not firing. With the log node you can see exactly the data that the alert node is processing and determine if it is working as expected.


Some thoughts

I built my system around the same architectural concepts you have here. Some things I've found useful:

When you have multiple bridge types, its nice to add a "location" to topics. I.e., I have two Logitech Harmony Hubs, one in the bedroom and one in the family room, and I use "harmony/bedroom/" and "harmony/familyRoom/" for this.
Probably a taste thing, but I like tagging command vs status at the END of a topic instead of the beginning, i.e., "zwave/familyRoom/familyRoomLight" for the status topic, and "/set" and "/get" as additional suffixes to that for those operations. It makes it easier to see whats going on at least for me, as you always get "device" and then "operation" instead of having to parse the topic to see which you have. I'm curious what you might see as a benefit to the alternative syntax, or if that's driven by some device choices or something. Both are fine probably because you tend to subscribe to commands vs state topics separately anyway in most cases I guess, just a thought.
Connected status is a good idea, I'm gonna adopt that.
There are some opinions around about promoting topics with spaces in them (i.e., "knxgateway1/status/Kitchen/Lights/Front Left". I think its more "we've seen this cause problems even though its allowed, best to avoid" thing: https://www.hivemq.com/blog/mqtt-essentials-part-5-mqtt-topics-best-practices

Oh also, I have a series of bridges that I wrote and use for stuff. Including a Google Home bridge that might be useful to a lot of people here. All Dockerized for your protection. Look for "HomeAutio" on Dockerhub.
They will follow my MQTT topic format as above though, and its not configurable right now... but it might expose some possibilities that aren't there for people right now looking to do this.


Remove unused sink/wait.rs

This was added in https://github.com/rust-lang-nursery/futures-rs/pull/406, but is currently disabled and Stream::wait is also removed at the stage of version 0.2.

Yeah, that was replaced with executor::block_on_stream. executor::block_on_sink seems like perhaps a reasonable thing to have as well, but in the meantime this seems fine to remove.


make_method call flexibility

The following example work:
import Dolang
eqs = [
    :(a*x + b*y)
]
variables = [(:a,0), (:b,0)]
parameters = [:x, :y]
Dolang.make_method(eqs, variables, parameters)

Now, two variants of this call don't work yet:

define group arguments:
variables = [ [(:a,0), (:b,0)] ]
parameters = [:x, :y]
Dolang.make_method(eqs, variables, parameters)

allow arbitrary symbols:
eqs = [
    :(a(0)*x + b*y(1))
]
variables = [ (:a,0), :b ]
parameters = [:x, (:y,1)]
Dolang.make_method(eqs, variables, parameters)

Ideally, the make_method would work with any list of symbols which have a normalized string representation. So as soon as we define (:a,:b,0) to represent \frac{\partial a}{\partial b}_t, we can build and differentiate equations containing derivatives. Same thing for indexed variables.
@sglyon : what do you think prevent us from making these improvements ? For the first issue, we should be fine if we all compound symbols are immutable (i.e. made of tuples). If there is a serious type stability issue, we might want to add a compound symbol object, but I doubt it is required, as they are all normalized as a string symbol anyway. As for the second issue, only reason I can think of is the way we currently deal with definitions.

So for the first case we currently accept things of the form:
variables = Dict(X => [(:a, 0), (:b, 0)])

I guess because the actual names of the grouped variables (X in my example) are mostly used internally, we could automatically generate them if we are given a vector of symbol groups instead of a dict.
For the second case, I thought we wanted to be very strict about timing, which your example violates in two ways:

For variables, we always require and explicit time
For parameters we only accept time 0, so we can take either :x or (:x, 0)

Ah, I know understand the misunderstanding in the second case. That's my fault: I was giving two different meanings to variables/parameters
I was thinking we could have a make_method(symbols_to_be_differentiated, constant_symbols) method, where symbols_to_be_differentiated would be a list of arbitrary compound symbols (or a list of list) and constant_symbols a list of compound symbols to be treated as constants.
Btw, I noticed, that normalize(:x) is currently the same as normalize((:x,0)), but that shouldn't be the case.

We don't have any support for make_method(symbols_to_be_differentiated, constant_symbols)
What do you expect each of normalize(:x) and normalize((:x, 0)) to return?

1/ So let's keep the issue open, as this is a much-needed feature. Way I
thought it was working was by normalizing all input arguments (symbols and
equations), so it seemed to me like a relatively simple extension.
2/ since normalize( (:a,1) ) produces _a__1_, maybe (:a,0) ->
`a__0' would make sense ?
On Tue, Mar 28, 2017 at 1:23 PM Spencer Lyon<EMAIL_ADDRESS>wrote:

We don't have any support for make_method(symbols_to_be_differentiated,
constant_symbols)
What do you expect each of normalize(:x) and normalize((:x, 0)) to return?
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I'm circling back around to this now.
To be totally honest I  don't see the need for make_method(symbols_to_be_differentiated, constant_symbols). Can help me understand why we need it?
Also I'd be happy to have normalize((:x, 0)) lower to _x__0_. Does that mean the functionality we want is
normalize(:x) ==> :_x_
normalize((:x, 0)) ==> :_x__0_

?

Yes for the second part. One shall add the case normalize(:fun)=>:fun when fun is a recognized function.
As for the make_method, I need to to be able to make the following calls:
make_method([:(a(0)*p+b(0))], [(:a,0),(:b,0)], [:p])
or
make_method([:(a(0)*p+b(0))], [(:a,0)] ,[(:b,0),:p]) # if I don't need to diff w.r.t. (:b,0)
or
make_method([:(Delta(a,0) + a(0)*p+b(0))], [(:Delta,:a,0), (:a,0)] ,[(:b,0),:p]) # `Delta(a,0) ~ \Delta a_t
or
make_method([ :( v(0)[0]+ v(0)[1] + v(0)[2] ) ], [(:v,0,0),(:v,0,1),(:v,0,2)] ,[]) # \sum v_{t,i}

This was the plan all along (see README file) and these extensions are required by at least three projects outside of dolo (bttt, heterogenous agents, time-consistent modeling).
The only thing that should be required for this to work, is to define the normalized form of the extended symbol (like Delta(a,0) represented by (:Delta,:a,0). ) and ensure the normalize routine correctly recognizes these type of symbol. make_method itself, would just have to normalize the equations, the arguments, and then operate on simple symbols.
One serious complication to deal with is how to deal with the definitions option. Ideally, this should be done outside of the make_method method. There would then be an argument prepend or smthg, where one could give the resolved definitions.


Selection in Vi mode disapears

Contour Terminal version
master
Installer source
Github: source code cloned
Operating System
Fedora 36
Architecture
x86-64
Other Software
No response
Steps to reproduce

Run tree in home
Switch to Vi mode
Start selecting text with V
keep selecting text upwards until selection doesn't disappear.

Expected Behavior
Selection should be visible at all times
Actual Behavior
Selection disapears
Additional notes
If I try to yank the selection after it disappears, I get a segfault and this assertion failure
contour: contour/src/terminal/ViCommands.cpp:185: void terminal::ViCommands::executeYank(terminal::ViMotion, unsigned int): Assertion terminal.selector()' failed.
`

Ugh I recently realized that, too. Thanks for creating the ticket. I may be able to look at it at some evening soon (unless you are faster) :).

I think before going into the why-yank-cranks part would be to figure why the selection drops, even though it's simply just extended. hmm...

ea21ebf30ada066b3f7eb0c6486849778ef3e0c8 this is the commit where it first appears.

~ea21ebf~ 1788dd1 this is the commit where it first appears.

Earlier linked wrong commit by mistake :(


Adjust xref query tags and remove unused docsets

Add correct xref query tags to fix uid not resolve issue
Remove unused docset config from configuration file

Docs Build status updates of commit 3762eb5:
:white_check_mark: Validation status: passed

File
Status
Preview URL
Details

.openpublishing.publish.config.json
:white_check_mark:Succeeded

For more details, please refer to the build report.
Note: If you changed an existing file name or deleted a file, broken links in other files to the deleted or renamed file are listed only in the full build report.

Fixed in #525


Use fetch and remove request [5.x]

Type: Refactor
The following has been addressed in the PR:

There is a related issue #1807
Unit or Functional tests are included in the PR

Description:

Another option with retry https://www.npmjs.com/package/make-fetch-happen

@ayusharma you might want to have some inspiration here https://github.com/verdaccio/monorepo/pull/367

Thanks @juanpicado 😀

Closing this, master is completely different  now.


Assign residents to an event

Initial implementation of assigning command.
Command format is as follows:
assign RESIDENT_INDEX EVENT_INDEX
E.g. assign 1 1
assign the 1st resident on the resident list to the 1st event on the event list

Codecov Report

Merging #109 into master will decrease coverage by 4.43%.
The diff coverage is 19.86%.

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[YUNIKORN-1580] Upgrade github.com/looplab/fsm to stable version

What is this PR for?
Upgrading github.com/looplab/fsm from v0.1.0 to v1.0.1.
Related fsm documetations: fsm in go package and fsm github .
The difference between v0.1.0 and v1.0.1 is following:

parameters of callback function are different. v0.1.0 def v.s. v1.0.1
parameters of fsm.Event are different. v0.1.0 def v.s. v1.0.1

What type of PR is it?

[ ] - Bug Fix
[ ] - Improvement
[ ] - Feature
[ ] - Documentation
[ ] - Hot Fix
[ ] - Refactoring
[x] - Task

What is the Jira issue?
https://issues.apache.org/jira/browse/YUNIKORN-1580
How should this be tested?
If the YUNIKORN-1580 in core side is not be merged, you need to clone the YUNIKORN-1580 in core.

modifying the go.mod require and redirect the core dependency to local core rep.
make test
If the YUNIKORN-1580 in core side is merged, only one thing is to try the command make test

Screenshots (if appropriate)
Questions:

[ ] - The licenses files need update.
[ ] - There is breaking changes for older versions.
[ ] - It needs documentation.

Expected failure is because the modification in core side is not merged.

YUNIKOR-1580 in core side was merged and the fsm version problem in core side does not exist.
I restart the Pre-commit check and the unit test step will pass.

Hi @wilfred-s , how do change the core version to the  latest version of core?
I successfully ran the UT in k8shim with the latest core which I cloned from the apache/yunikorn-core:master.

Updating the package dependency.
Core version is latest.


"Authorization Failed" for BROKER users created via API having rights for "ALL" tables

In Pinot 1.2.0, user creation via REST API seems broken when "ZkBasicAuthAccessControlFactory" is activated.
How to reproduce:

start pinot 1.2.0 (i.e. using docker-compose) and with "ZkBasicAuthAccessControlFactory" enabled.
create a schema and a table (can be empty in terms of: no data required)
create a "BROKER" User via the API:curl -X 'POST' \
 'http://localhost:9000/users' \
 -H 'accept: application/json' \
 -H 'Authorization: YWRtaW46YWRtaW4=' \
 -H 'Content-Type: application/json' \
 -d '{
 "username": "test",
 "password": "test",
 "component": "BROKER",
 "role": "USER",
 "permissions": [
   "READ"
 ],
 "tables": [
   "ALL"
 ]
}
'

you can check the "User Console" in the Controller UI now if you want. It looks like the user has been created correctly. "READ" Rights have been assigned for "ALL" tables for this broker user.
try to make a query using this user via the API:export AUTH_HEADER=`echo -n 'test:test' | base64`
curl -H "Content-Type: application/json" -H "Authorization: $AUTH_HEADER" -X POST \
 -d '{"sql":"select * from offline_table_example_OFFLINE limit 10"}' \
 http://localhost:8099/query/sql
 {"code":403,"error":"Permission denied.Reason: Authorization Failed for tables: [offline_table_example_OFFLINE]"}%

That looks already wrong, as the user should have access to "ALL" tabes.
Now buckle up, as we're going to fix this: Go to the "User Console" in the Controller UI, "edit" the user. In the "tables" section, remove the activated checkbox for "ALL" - and check it again. Submit your changes. (There weren't really any changes, but still.)
Now try the exact same "curl" again:curl -H "Content-Type: application/json" -H "Authorization: $AUTH_HEADER" -X POST \
 -d '{"sql":"select * from offline_table_example_OFFLINE limit 10"}' \
 http://localhost:8099/query/sql
{"numRowsResultSet":0,"partialResult":false,"exceptions":[],"numGroupsLimitReached":false,"timeUsedMs":1,"requestId":"1429030164000000006","brokerId":"Broker_67d510247f83_8099","numDocsScanned":0,"totalDocs":0,"numEntriesScannedInFilter":0,"numEntriesScannedPostFilter":0,"numServersQueried":0,"numServersResponded":0,"numSegmentsQueried":0,"numSegmentsProcessed":0,"numSegmentsMatched":0,"numConsumingSegmentsQueried":0,"numConsumingSegmentsProcessed":0,"numConsumingSegmentsMatched":0,"minConsumingFreshnessTimeMs":0,"numSegmentsPrunedByBroker":0,"numSegmentsPrunedByServer":0,"numSegmentsPrunedInvalid":0,"numSegmentsPrunedByLimit":0,"numSegmentsPrunedByValue":0,"brokerReduceTimeMs":0,"offlineThreadCpuTimeNs":0,"realtimeThreadCpuTimeNs":0,"offlineSystemActivitiesCpuTimeNs":0,"realtimeSystemActivitiesCpuTimeNs":0,"offlineResponseSerializationCpuTimeNs":0,"realtimeResponseSerializationCpuTimeNs":0,"offlineTotalCpuTimeNs":0,"realtimeTotalCpuTimeNs":0,"explainPlanNumEmptyFilterSegments":0,"explainPlanNumMatchAllFilterSegments":0,"traceInfo":{}}%

Now we got a response...

Unfortunately, this breaks our automation for user creation via the API. Can we get a fix?

@johannesploetner if you want the user to have access to all the tables, the list of tables should be omitted rather than setting "tables": ["ALL"] (which actually has the semantic of granting the user access to a single table with the name of ALL).

Thanks a lot! I would still advise to make it more clear in the docs.


Add Chi La Khong Cung Nhau by Tang Phuc x Truong Thao Nhi

Song Name
Chi La Khong Cung Nhau
Artist Name
Tang Phuc x Truong Thao Nhi
Source
Youtube
Youtube Link
https://youtu.be/UqKVL56IJB8?si=j5KV-8deJ_nkaSpt
Direct File Link
No response
Song ID
529148
Start Offset [ms]
11500
Extra
Created from Auto Nong.
Created for level:
Downloaded: Yes

accept


Add and_scalar and or_scalar for boolean

Close https://github.com/jorgecarleitao/arrow2/issues/663

I think that there is an optimization here:

When the scalar is true, A & true = A and A | true = A.
When the scalar is false, A & false = false and A | false =  A

i.e. we do not need to compute this item by item; we just need to clone and/or initialize all items as false / unset accordingly. This should be orders of magnitude faster since it is not O(N).
What do you think?

Yes. That should be great. I will update the code. Thanks.

Merged. Thanks a lot, @silathdiir!


API 32 update

Updates for the API upgrade were taken from https://github.com/e-mission/e-mission-phone/compare/master...maint_upgrade_2023
These changes require the project to be built with java 11. Be sure to install Java 11 and set it to be used with
sudo update-alternatives --config java and in JAVA_HOME
You will also need to install "command line tools" from Android Studio and add the appropriate android SDK folders to your path. That should look something like this:
$ANDROID_SDK/platform-tools:$ANDROID_SDK/emulator:$ANDROID_SDK/cmdline-tools/latest/bin
You may need to do a git clean -dfx on the project and fully rebuild for the changes to apply properly.
No changes were made to the setup/setup_shared_native.sh file but the EXPECTED_COUNT will probably need to be adjusted (24 in the upstream branch).
The minimum API was raised to 23 as in the upstream branch. This is unlikely to be an issue but it could be if a significant amount of the user base for the app is running API 22 devices.
Gradle was updated to 7.6. Other tools / frameworks in setup/export_shared_dep_versions.sh were not changed but could maybe use an update.
Several changes were brought to various permissions in Android from API 28 to API 32. Everything seems to have been updated properly in the libraries which depend on the changed permissions, but the app is still crashing due to missing permissions. Here is a log of the crash log.txt. The permission causing the crash here is ACTIVITY_RECOGNITION which is for physical activity tracking. It originates from the service here. I think this service will need to be prevented from running until the permission is granted.
The app does seem to work fine once the permissions are granted from the Android settings though. That said, many changes were made in accordance to the upstream changes and I don't know what impact they may have so everything should be checked to see that nothing broke.

I fixed the crash by adding a screen to verify the permissions before continuing. I also fixed some minor stuff. Only the splash screen does not display the right logo :/


Threading fix

Time to pull in changes

This needs to get backported to 3.x

I'd love to see it backported to 3.x soon.

I will see if I find the time to backport this evening.


Remove dnx reference

There's a reference to Microsoft.Extensions.CompilationAbstractions which is a dnx component. It should be removed
https://github.com/aspnet/dotnet-watch/blob/release/src/Microsoft.DotNet.Watcher.Core/project.json#L14

Fixed


fix: minor fix

Description
hmiserver was not able to use currentUserService in this file as it was not set up (was just null)

@dgauldie or @YohannParis can you force merge this?


Web Interface for the Project

Web Interface for the Project
A simple web based interface for the created intents.

As in the project landing page? Please go ahead.


Align hardware map generated file with twister1

Do not store every hardware-map parameter.
Fix loading empty hardware-map file.
Fix taking proper platform from loaded hardware-map file, if platform is missed in CLI.

Codecov Report

Merging #147 (cb80117) into main (325ebc9) will increase coverage by 0.14%.
The diff coverage is 100.00%.

:mega: This organization is not using Codecov’s GitHub App Integration. We recommend you install it so Codecov can continue to function properly for your repositories. Learn more
@@            Coverage Diff             @@
##             main     #147      +/-   ##
==========================================
+ Coverage   81.36%   81.51%   +0.14%
==========================================
  Files          54       54
  Lines        3365     3370       +5
==========================================
+ Hits         2738     2747       +9
+ Misses        627      623       -4

Impacted Files
Coverage Δ

src/twister2/device/hardware_map.py
100.00% <100.00%> (ø)

src/twister2/scripts/hardware_map.py
91.25% <100.00%> (+5.35%)
:arrow_up:

src/twister2/twister_config.py
96.26% <100.00%> (ø)

:mega: We’re building smart automated test selection to slash your CI/CD build times. Learn more


Add dry run option for PR validation

Is your feature request related to a problem? Please describe.
The check only option exists to error when information is out of sync. A dry run option as a simple validation that assemble is completed successful without changing the branch would be useful for change validation during the PR process.
Describe the solution you'd like
Remove the check_only flag and add a dry run option.
There should be a way for a user to understand if there were changes or not through output and logged messages. Then the user could determine whether to fail for changes or not.
Acceptance Criteria

[x] Remove check_only flag
[x] Add a more precise flag for dry run. Possibly (push=false)
[x] Add a logged message with dry run to show what would have been updated.
[ ] Stretch Goal: Possibly on another issue - Comment on the PR if triggered through that process

Describe alternatives you've considered
The TrestleBot class has a dry-run option. This could simply be exposed, but that could be confusing when here is already a check_only flag and the option does not have output that would be helpful to a user.
Additional context
This will be a breaking change so that release notes should have upgrade information. Documentation will need to updated to show how to fail a pipeline when changed are found and that is unexpected.

@beatrizmcouto Currently testing some work around this feature and suggest we move the commenting feature to a new issue since it is slightly more complex. WDYT?

Let's discuss in the daily later today


Slot templates inside logic templates fail to render

Version
3.2.33
Reproduction link
sfc.vuejs.org/
Steps to reproduce
Put one or more templates with a named slot inside a template with logic like v-if.
What is expected?
For the slots to conditionally render
What is actually happening?
Compiled with problems:

...

Module build failed (from ./node_modules/vue-loader/dist/templateLoader.js):
Error: Codegen node is missing for element/if/for node. Apply appropriate transforms first.
    at assert (.../@vue/compiler-core/dist/compiler-core.cjs.js:508:15)

Working through the compatibility build to migrate from vue2 ran into this failure.

all templates should be top level
from :
 <BaseLayout>
    <template #header>

Here might be a page title {{myProp}}

    </template>

    <template v-if="myProp">
      <template #default>

A paragraph for the main content.

And another one.

      </template>

      <template #footer>

Here's some contact info butts

      </template>
    </template>
  </BaseLayout>

To:
  <BaseLayout>
    <template #header>

Here might be a page title {{myProp}}

    </template>

    <template #default v-if="myProp">

A paragraph for the main content.

And another one.

    </template>

    <template #footer v-if="myProp">

Here's some contact info butts

    </template>
  </BaseLayout>

For simple logic that seems fine but I have at least a few use-cases where consolidating the logic is a big help for readability.
Something like:
 <BaseLayout>
    <template #header>

Title That Persists

    </template>

    <template v-if="certainCondition">
      <template #default>

Initial content

      </template>

      <template #footer>
        <button>Control for this chunk</button>
      </template>
    </template>

    <template v-else>
      <template #default>

Secondary content

      </template>

      <template #footer>
        <button>Another action</button>
      </template>
    </template>
  </BaseLayout>

That would have been nice, but it's not a supported syntax.
    <BaseLayout>
      <template #header>

Title That Persists

      </template>

      <template #default v-if="certainCondition">

Initial content

      </template>

      <template #footer v-if="certainCondition">
        <button>Control for this chunk</button>
      </template>

      <template #default v-if="!certainCondition">

Secondary content

      </template>

      <template #footer  v-if="!certainCondition">
        <button>Another action</button>
      </template>

    </BaseLayout>

As @lidlanca pointed out, you should write the v-if multiple times for this to work. Using multiple templates like that creates ambiguity for the default slot and therefore cannot be supported.