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
>>>
>>
--
---
You received this message because you are subscribed to the Google Groups
"theano-users" group.
To unsubscribe from this group and stop receiving emails from it, send an email
to theano-users+unsubscr...@googlegroups.com.
For more options, visit https://groups.google.com/d/optout.
