Use a smaller value like 0.9 or 0.8.
Le 2 déc. 2016 18:19, "Sandipan Haldar" <[email protected]> a écrit :
> I have a total dedicated memory of 1948MB. And used dedicated memory of
> 233MB. I gave lib.cnmem=1. No the error is shown when lib.cnmem=0..But it
> shows
>
> "Using gpu device 0: GeForce 820M (CNMeM is disabled, cuDNN not available)"
>
> On Friday, December 2, 2016 at 2:01:58 AM UTC+5:30, Pascal Lamblin wrote:
>>
>> The error message mentions being out of memory for cnmem.
>> How much memory do you have on your GPU? How much free memory?
>> What is the value you gave to lib.cnmem?
>> Does it still happen if you set lib.cnmem to 0?
>>
>> On Thu, Dec 01, 2016, Sandipan Haldar wrote:
>> > *Can somebody help me with this error?*
>> >
>> >
>> >
>> > >>> import theano
>> > ERROR (theano.sandbox.cuda): ERROR: Not using GPU. Initialisation of
>> device
>> > gpu failed:
>> > initCnmem: cnmemInit call failed! Reason=CNMEM_STATUS_OUT_OF_MEMORY.
>> > numdev=1
>> >
>> > Traceback (most recent call last):
>> > File
>> > "/home/sandipan/.local/lib/python3.5/site-packages/theano/compile/function_module.py",
>>
>> > line 859, in __call__
>> > outputs = self.fn()
>> > RuntimeError: Cuda error:
>> > kernel_reduce_ccontig_node_meb404c8cd39208f6884dd773b584b7d7_0: out of
>> > memory. (grid: 1 x 1; block: 256 x 1 x 1)
>> >
>> >
>> > During handling of the above exception, another exception occurred:
>> >
>> > Traceback (most recent call last):
>> > File "<stdin>", line 1, in <module>
>> > File
>> > "/home/sandipan/.local/lib/python3.5/site-packages/theano/__init__.py",
>>
>> > line 111, in <module>
>> > theano.sandbox.cuda.tests.test_driver.test_nvidia_driver1()
>> > File
>> > "/home/sandipan/.local/lib/python3.5/site-packages/theano/
>> sandbox/cuda/tests/test_driver.py",
>> > line 38, in test_nvidia_driver1
>> > if not numpy.allclose(f(), a.sum()):
>> > File
>> > "/home/sandipan/.local/lib/python3.5/site-packages/theano/compile/function_module.py",
>>
>> > line 871, in __call__
>> > storage_map=getattr(self.fn, 'storage_map', None))
>> > File
>> > "/home/sandipan/.local/lib/python3.5/site-packages/theano/gof/link.py",
>>
>> > line 314, in raise_with_op
>> > reraise(exc_type, exc_value, exc_trace)
>> > File "/home/sandipan/.local/lib/python3.5/site-packages/six.py",
>> line
>> > 685, in reraise
>> > raise value.with_traceback(tb)
>> > File
>> > "/home/sandipan/.local/lib/python3.5/site-packages/theano/compile/function_module.py",
>>
>> > line 859, in __call__
>> > outputs = self.fn()
>> > RuntimeError: Cuda error:
>> > kernel_reduce_ccontig_node_meb404c8cd39208f6884dd773b584b7d7_0: out of
>> > memory. (grid: 1 x 1; block: 256 x 1 x 1)
>> >
>> > Apply node that caused the error:
>> > GpuCAReduce{add}{1}(<CudaNdarrayType(float32, vector)>)
>> > Toposort index: 0
>> > Inputs types: [CudaNdarrayType(float32, vector)]
>> > Inputs shapes: [(10000,)]
>> > Inputs strides: [(1,)]
>> > Inputs values: ['not shown']
>> > Outputs clients: [[HostFromGpu(GpuCAReduce{add}{1}.0)]]
>> >
>> > HINT: Re-running with most Theano optimization disabled could give you
>> a
>> > back-trace of when this node was created. This can be done with by
>> setting
>> > the Theano flag 'optimizer=fast_compile'. If that does not work, Theano
>> > optimizations can be disabled with 'optimizer=None'.
>> > HINT: Use the Theano flag 'exception_verbosity=high' for a debugprint
>> and
>> > storage map footprint of this apply node.
>> > >>>
>> >
>> > --
>> >
>> > ---
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>>
>>
>> --
>> Pascal
>>
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