我跟着tensorflow-gpu installation tutorial，根据tensorflow网站上的示例，似乎安装得很好。但是我得到了一个
Check failed: stream->parent()->GetConvolveAlgorithms( conv_parameters.ShouldIncludeWinogradNonfusedAlgo<T>(), &algorithms)
错误。我看到一个solution通过更新gpu驱动程序并重新启动它而对其他人有相同的错误，但是我似乎没有工作。
这是完整的错误：
$py cnn_train.py
C:\Program Files\Python36\lib\site-packages\h5py\__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
from ._conv import register_converters as _register_converters
Using TensorFlow backend.
cnn_train.py:21: UserWarning: Update your `Conv2D` call to the Keras 2 API: `Conv2D(32, (3, 3), input_shape=(200, 200,..., activation="relu")`
model.add(Convolution2D(32, 3, 3, input_shape=(200, 200, 1), activation='relu'))
cnn_train.py:24: UserWarning: Update your `Conv2D` call to the Keras 2 API: `Conv2D(32, (3, 3), input_shape=(200, 200,..., activation="relu")`
model.add(Convolution2D(32, 3, 3, input_shape=(200, 200, 1), activation='relu'))
cnn_train.py:33: UserWarning: Update your `Dense` call to the Keras 2 API: `Dense(activation="relu", kernel_regularizer=<keras.reg..., units=150)`
kernel_regularizer=regularizers.l2(0.01)))
cnn_train.py:38: UserWarning: Update your `Dense` call to the Keras 2 API: `Dense(activation="relu", kernel_regularizer=<keras.reg..., units=150)`
kernel_regularizer=regularizers.l2(0.01)))
cnn_train.py:44: UserWarning: Update your `Dense` call to the Keras 2 API: `Dense(activation="relu", kernel_regularizer=<keras.reg..., units=150)`
kernel_regularizer=regularizers.l2(0.01)))
cnn_train.py:47: UserWarning: Update your `Dense` call to the Keras 2 API: `Dense(activation="sigmoid", units=4)`
model.add(Dense(output_dim=4, activation='sigmoid'))
Found 42 images belonging to 4 classes.
Found 12 images belonging to 4 classes.
cnn_train.py:83: UserWarning: The semantics of the Keras 2 argument `steps_per_epoch` is not the same as the Keras 1 argument `samples_per_epoch`. `steps_per_epoch` is the number of batches to draw from the generator at each epoch. Basically steps_per_epoch = samples_per_epoch/batch_size. Similarly `nb_val_samples`->`validation_steps` and `val_samples`->`steps` arguments have changed. Update your method calls accordingly.
nb_val_samples=320)
cnn_train.py:83: UserWarning: Update your `fit_generator` call to the Keras 2 API: `fit_generator(<keras.pre..., validation_data=<keras.pre..., steps_per_epoch=195, epochs=10, validation_steps=320)`
nb_val_samples=320)
Epoch 1/10
2018-03-14 21:24:47.253618: I C:\tf_jenkins\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\platform\cpu_feature_guard.cc:137] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2
2018-03-14 21:24:47.757122: I C:\tf_jenkins\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\common_runtime\gpu\gpu_device.cc:1105] Found device 0 with properties:
name: GeForce GTX 1050 major: 6 minor: 1 memoryClockRate(GHz): 1.493
pciBusID: 0000:01:00.0
totalMemory: 4.00GiB freeMemory: 3.31GiB
2018-03-14 21:24:47.761770: I C:\tf_jenkins\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\common_runtime\gpu\gpu_device.cc:1195] Creating TensorFlow device (/device:GPU:0) -> (device: 0, name: GeForce GTX 1050, pci bus id: 0000:01:00.0, compute capability: 6.1)
2018-03-14 21:24:50.602239: E C:\tf_jenkins\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\stream_executor\cuda\cuda_dnn.cc:378] Loaded runtime CuDNN library: 7101 (compatibility version 7100) but source was compiled with 7003 (compatibility version 7000). If using a binary install, upgrade your CuDNN library to match. If building from sources, make sure the library loaded at runtime matches a compatible version specified during compile configuration.
2018-03-14 21:24:50.612332: F C:\tf_jenkins\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\kernels\conv_ops.cc:717] Check failed: stream->parent()->GetConvolveAlgorithms( conv_parameters.ShouldIncludeWinogradNonfusedAlgo<T>(), &algorithms)
任何帮助将不胜感激！ 感谢