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Calling K.get_session() using Keras 2.0.9 (backend TF 1.4) leads to following exception:
$ python
Python 2.7.6 (default, Oct 26 2016, 20:30:19)
[GCC 4.8.4] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> from keras import backend as K
Using TensorFlow backend.
2017-11-03 13:44:40.499249: I tensorflow/core/platform/cpu_feature_guard.cc:137] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA
2017-11-03 13:44:40.725248: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1030] Found device 0 with properties:
name: Quadro K2200 major: 5 minor: 0 memoryClockRate(GHz): 1.124
pciBusID: 0000:03:00.0
totalMemory: 3.95GiB freeMemory: 3.32GiB
2017-11-03 13:44:40.908348: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1030] Found device 1 with properties:
name: Quadro K2200 major: 5 minor: 0 memoryClockRate(GHz): 1.124
pciBusID: 0000:81:00.0
totalMemory: 3.95GiB freeMemory: 3.91GiB
2017-11-03 13:44:40.908450: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1045] Device peer to peer matrix
2017-11-03 13:44:40.908500: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1051] DMA: 0 1
2017-11-03 13:44:40.908525: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1061] 0: Y N
2017-11-03 13:44:40.908536: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1061] 1: N Y
2017-11-03 13:44:40.908560: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1120] Creating TensorFlow device (/device:GPU:0) -> (device: 0, name: Quadro K2200, pci bus id: 0000:03:00.0, compute capability: 5.0)
2017-11-03 13:44:40.908574: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1120] Creating TensorFlow device (/device:GPU:1) -> (device: 1, name: Quadro K2200, pci bus id: 0000:81:00.0, compute capability: 5.0)
>>> K.get_session()
2017-11-03 13:44:46.409150: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1120] Creating TensorFlow device (/device:GPU:0) -> (device: 0, name: Quadro K2200, pci bus id: 0000:03:00.0, compute capability: 5.0)
2017-11-03 13:44:46.409197: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1120] Creating TensorFlow device (/device:GPU:1) -> (device: 1, name: Quadro K2200, pci bus id: 0000:81:00.0, compute capability: 5.0)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/usr/local/lib/python2.7/dist-packages/keras/backend/tensorflow_backend.py", line 180, in get_session
[tf.is_variable_initialized(v) for v in candidate_vars])
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 889, in run
run_metadata_ptr)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 1049, in _run
raise RuntimeError('The Session graph is empty. Add operations to the '
RuntimeError: The Session graph is empty. Add operations to the graph before calling run().
On Keras 2.0.8 there is no problem:
$ python
Python 2.7.6 (default, Oct 26 2016, 20:30:19)
[GCC 4.8.4] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> from keras import backend as K
Using TensorFlow backend.
>>> K.get_session()
2017-11-03 13:43:41.642325: I tensorflow/core/platform/cpu_feature_guard.cc:137] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA
2017-11-03 13:43:41.878929: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1030] Found device 0 with properties:
name: Quadro K2200 major: 5 minor: 0 memoryClockRate(GHz): 1.124
pciBusID: 0000:03:00.0
totalMemory: 3.95GiB freeMemory: 3.32GiB
2017-11-03 13:43:42.073808: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1030] Found device 1 with properties:
name: Quadro K2200 major: 5 minor: 0 memoryClockRate(GHz): 1.124
pciBusID: 0000:81:00.0
totalMemory: 3.95GiB freeMemory: 3.91GiB
2017-11-03 13:43:42.073906: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1045] Device peer to peer matrix
2017-11-03 13:43:42.073954: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1051] DMA: 0 1
2017-11-03 13:43:42.073977: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1061] 0: Y N
2017-11-03 13:43:42.073988: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1061] 1: N Y
2017-11-03 13:43:42.074011: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1120] Creating TensorFlow device (/device:GPU:0) -> (device: 0, name: Quadro K2200, pci bus id: 0000:03:00.0, compute capability: 5.0)
2017-11-03 13:43:42.074024: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1120] Creating TensorFlow device (/device:GPU:1) -> (device: 1, name: Quadro K2200, pci bus id: 0000:81:00.0, compute capability: 5.0)
<tensorflow.python.client.session.Session object at 0x7f583528d9d0>
>>>
Check that you are up-to-date with the master branch of Keras. You can update with:
pip install git+git://github.com/fchollet/keras.git --upgrade --no-deps
If running on TensorFlow, check that you are up-to-date with the latest version. The installation instructions can be found here.
If running on Theano, check that you are up-to-date with the master branch of Theano. You can update with:
pip install git+git://github.com/Theano/Theano.git --upgrade --no-deps
Provide a link to a GitHub Gist of a Python script that can reproduce your issue (or just copy the script here if it is short).
The text was updated successfully, but these errors were encountered:
Calling K.get_session() using Keras 2.0.9 (backend TF 1.4) leads to following exception:
On Keras 2.0.8 there is no problem:
@fchollet It seems to be caused by this refactoring: 9166733
Check that you are up-to-date with the master branch of Keras. You can update with:
pip install git+git://github.com/fchollet/keras.git --upgrade --no-deps
If running on TensorFlow, check that you are up-to-date with the latest version. The installation instructions can be found here.
If running on Theano, check that you are up-to-date with the master branch of Theano. You can update with:
pip install git+git://github.com/Theano/Theano.git --upgrade --no-deps
Provide a link to a GitHub Gist of a Python script that can reproduce your issue (or just copy the script here if it is short).
The text was updated successfully, but these errors were encountered: