Tensorflow崩潰CUBLAS_STATUS_ALLOC_FAILED

我使用一個簡單的MINST神經網絡程序在Windows 10上運行tensorflow-gpu。當它試圖運行時，它遇到一個CUBLAS_STATUS_ALLOC_FAILED錯誤。谷歌搜索沒有任何東西。Tensorflow崩潰CUBLAS_STATUS_ALLOC_FAILED

I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\gpu\gpu_device.cc:885] Found device 0 with properties: 
name: GeForce GTX 970 
major: 5 minor: 2 memoryClockRate (GHz) 1.253 
pciBusID 0000:0f:00.0 
Total memory: 4.00GiB 
Free memory: 3.31GiB 
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\gpu\gpu_device.cc:906] DMA: 0 
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\gpu\gpu_device.cc:916] 0: Y 
I c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\core\common_runtime\gpu\gpu_device.cc:975] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 970, pci bus id: 0000:0f:00.0) 
E c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\cuda\cuda_blas.cc:372] failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED 
W c:\tf_jenkins\home\workspace\release-win\device\gpu\os\windows\tensorflow\stream_executor\stream.cc:1390] attempting to perform BLAS operation using StreamExecutor without BLAS support 
Traceback (most recent call last): 
    File "C:\Users\Anonymous\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\client\session.py", line 1021, in _do_call 
    return fn(*args) 
    File "C:\Users\Anonymous\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\client\session.py", line 1003, in _run_fn 
    status, run_metadata) 
    File "C:\Users\Anonymous\AppData\Local\Programs\Python\Python35\lib\contextlib.py", line 66, in __exit__ 
    next(self.gen) 
    File "C:\Users\Anonymous\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\framework\errors_impl.py", line 469, in raise_exception_on_not_ok_status 
    pywrap_tensorflow.TF_GetCode(status)) 
tensorflow.python.framework.errors_impl.InternalError: Blas SGEMM launch failed : a.shape=(100, 784), b.shape=(784, 256), m=100, n=256, k=784 
     [[Node: MatMul = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/job:localhost/replica:0/task:0/gpu:0"](_recv_Placeholder_0/_7, Variable/read)]] 
     [[Node: Mean/_15 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_35_Mean", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]

來源

2016-12-13 Axiverse

的位置會話配置的「allow_growth」屬性現在似乎有所不同。它在這裏解釋：https://www.tensorflow.org/tutorials/using_gpu

所以目前你必須設定這樣的：

config = tf.ConfigProto() 
config.gpu_options.allow_growth = True 
session = tf.Session(config=config, ...)

來源

2017-03-20 01:33:57

在Windows上，目前tensorflow並不像它在文檔中表示，通過允許動態內存增長如下分配所有可用內存，而不是你可以解決此錯誤：

tf.Session(config=tf.ConfigProto(allow_growth=True))

來源

2016-12-30 00:44:47 Axiverse

'ConfiProto'似乎缺少這個參數，從而產生一個錯誤'ValueError異常：協議消息ConfigProto沒有「 allow_growth「字段」 –

Tensorflow崩潰CUBLAS_STATUS_ALLOC_FAILED

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