A second thing that is not clear to me in the documentation of Theano is
how you specify a C implementation and GPU implementation of the same own
op. Thank you
On Wednesday, July 12, 2017 at 9:58:34 AM UTC+2, Christopher Bourez wrote:
>
> I've also tried to create an example with theano.gpuarray.nnet.GpuSoftmax but
> after compilation it got replaced another implementation*GpuDnnSoftmax : *
>
>
> *Elemwise{mul,no_inplace} [id A] '' |HostFromGpu(gpuarray) [id B] ''
> | |GpuSoftmax [id C] '' | |GpuFromHost<dev0> [id D] '' | |x
> [id E] |InplaceDimShuffle{x,x} [id F] '' |TensorConstant{2} [id
> G]CompilingHostFromGpu(gpuarray) [id A] '' 5 |GpuElemwise{Mul}[(0,
> 1)]<gpuarray> [id B] '' 4 |GpuArrayConstant{[[ 2.]]} [id C]
> |InplaceGpuDimShuffle{0,1} [id D] '' 3
> |GpuDnnSoftmax{mode='channel', algo='accurate'} [id E] '' 2
> |GpuContiguous [id F] '' 1 |InplaceGpuDimShuffle{0,1,x,x} [id G]
> '' 0 |<GpuArrayType<dev0>(float32, (False, False))> [id H]*I'm
> looking of a good example with a GPU Kernel.
>
> On Wednesday, July 12, 2017 at 9:56:08 AM UTC+2, Christopher Bourez wrote:
>>
>> I don't know what you mean by "not modifying" the source for GpuEye:
>> - In this example, I'm importing a not modifyed GpuEye op from Theano
>> basic ops
>> - If I'm using theano.tensor.eye, then it does not use the GpuEye
>>
>> Also, are you sure this test
>>
>> https://github.com/Theano/Theano/blob/2625464534147fd70da60a3a3ddcb63ed8e5a416/theano/gpuarray/tests/test_basic_ops.py#L401
>> works well ?
>>
>> On Wednesday, July 12, 2017 at 2:48:44 AM UTC+2, Pascal Lamblin wrote:
>>>
>>> Does it work if you do not modify the source for GpuEye at all?
>>> If it does, then maybe sharing your new source would get you more help.
>>>
>>> On Tuesday, July 11, 2017 at 12:12:03 PM UTC-4, Christopher Bourez wrote:
>>>>
>>>> Hi,
>>>>
>>>> I'm trying to implement a simple GPU op but it always gives me a
>>>> Segmentation fault during compilation, without other message.
>>>>
>>>> For example :
>>>> import theano
>>>> from theano.gpuarray.basic_ops import GpuEye
>>>>
>>>> x = theano.tensor.iscalar('x')
>>>> y = theano.tensor.iscalar('y')
>>>> z = GpuEye(dtype='float32', context_name=None)(x,y,
>>>> theano.tensor.constant(0))
>>>>
>>>> theano.printing.debugprint(z)
>>>> print("Compiling")
>>>> f = theano.function( [x,y], z)
>>>> theano.printing.debugprint(f)
>>>> print("Results")
>>>> print(f(3, 3))
>>>>
>>>> I've also tried with the softmax gpu function. Is there something I'm
>>>> missing ?
>>>>
>>>> I copied the file, created a complete new op, and the segmentation
>>>> fault appears when I'm defining a Kernel in gpu_kernels() method of the op.
>>>>
>>>> Thank you a lot for your help
>>>>
>>>
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