couple of issues to support opencl

[rayset]

as you know theano works on opencl, but it's in beta.

first issue: this program forces cpu mode if not on cuda.

python make_image_analogy.py images/arch-A.jpg images/arch-Ap.jpg images/arch-B.jpg /nothing
Using Theano backend.
Mapped name None to device opencl0:0: Tahiti
/home/deep/.local/lib/python2.7/site-packages/theano/tensor/signal/downsample.py:5: UserWarning: downsample module has been moved to the pool module.
warnings.warn("downsample module has been moved to the pool module.")
Theano CPU mode detected. Forcing a-scale-mode to "match"
Using PatchMatch model

I think this is because of the _on_gpu() method of keras/backend/theano_backend.py that seems to assume opencl (and gpuarray) support don't exist.

second problem: this is the error I get running the code

Precomputing static features...
ERROR (theano.gof.opt): Optimization failure due to: local_error_convop
ERROR (theano.gof.opt): node: ConvOp{('imshp', (256, 16, 12)),('kshp', (3, 3)),('nkern', 512),('bsize', None),('dx', 1),('dy', 1),('out_mode', 'valid'),('unroll_batch', None),('unroll_kern', None),('unroll_patch', True),('imshp_logical', (256, 16, 12)),('kshp_logical', (3, 3)),('kshp_logical_top_aligned', True)}(IncSubtensor{Set;::, ::, int64:int64:, int64:int64:}.0, HostFromGpu(gpuarray).0)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/home/deep/.local/lib/python2.7/site-packages/theano/gof/opt.py", line 1772, in process_node
replacements = lopt.transform(node)
File "/home/deep/.local/lib/python2.7/site-packages/theano/sandbox/gpuarray/opt.py", line 141, in local_opt
new_op = maker(node, context_name)
File "/home/deep/.local/lib/python2.7/site-packages/theano/sandbox/gpuarray/opt.py", line 839, in local_error_convop
"""
AssertionError:
ConvOp does not work with the gpuarray backend.

Use the new convolution interface to have GPU convolution working:
theano.tensor.nnet.conv2d()

Traceback (most recent call last):
File "make_image_analogy.py", line 27, in
image_analogy.main.main(args, model_class)
File "/home/deep/.local/lib/python2.7/site-packages/image_analogy/main.py", line 69, in main
model.build(a_image, ap_image, b_image, (1, img_num_channels, img_height, img_width))
File "/home/deep/.local/lib/python2.7/site-packages/image_analogy/models/nnf.py", line 16, in build
loss = self.build_loss(a_image, ap_image, b_image)
File "/home/deep/.local/lib/python2.7/site-packages/image_analogy/models/nnf.py", line 54, in build_loss
all_a_features, all_ap_image_features, all_b_features = self.precompute_static_features(a_image, ap_image, b_image)
File "/home/deep/.local/lib/python2.7/site-packages/image_analogy/models/base.py", line 51, in precompute_static_features
all_a_features = self.get_features(a_image, a_layers)
File "/home/deep/.local/lib/python2.7/site-packages/image_analogy/models/base.py", line 59, in get_features
f = K.function([self.net_input], [self.get_layer_output(layer_name) for layer_name in layers])
File "/home/deep/.local/lib/python2.7/site-packages/keras/backend/theano_backend.py", line 388, in function
return Function(inputs, outputs, updates=updates)
File "/home/deep/.local/lib/python2.7/site-packages/keras/backend/theano_backend.py", line 380, in init
allow_input_downcast=True, *_kwargs)
File "/home/deep/.local/lib/python2.7/site-packages/theano/compile/function.py", line 320, in function
output_keys=output_keys)
File "/home/deep/.local/lib/python2.7/site-packages/theano/compile/pfunc.py", line 479, in pfunc
output_keys=output_keys)
File "/home/deep/.local/lib/python2.7/site-packages/theano/compile/function_module.py", line 1776, in orig_function
output_keys=output_keys).create(
File "/home/deep/.local/lib/python2.7/site-packages/theano/compile/function_module.py", line 1456, in init
optimizer_profile = optimizer(fgraph)
File "/home/deep/.local/lib/python2.7/site-packages/theano/gof/opt.py", line 101, in call
return self.optimize(fgraph)
File "/home/deep/.local/lib/python2.7/site-packages/theano/gof/opt.py", line 89, in optimize
ret = self.apply(fgraph, *args, *_kwargs)
File "/home/deep/.local/lib/python2.7/site-packages/theano/gof/opt.py", line 230, in apply
sub_prof = optimizer.optimize(fgraph)
File "/home/deep/.local/lib/python2.7/site-packages/theano/gof/opt.py", line 89, in optimize
ret = self.apply(fgraph, _args, *_kwargs)
File "/home/deep/.local/lib/python2.7/site-packages/theano/gof/opt.py", line 230, in apply
sub_prof = optimizer.optimize(fgraph)
File "/home/deep/.local/lib/python2.7/site-packages/theano/gof/opt.py", line 89, in optimize
ret = self.apply(fgraph, _args, *_kwargs)
File "/home/deep/.local/lib/python2.7/site-packages/theano/gof/opt.py", line 2196, in apply
lopt_change = self.process_node(fgraph, node, lopt)
File "/home/deep/.local/lib/python2.7/site-packages/theano/gof/opt.py", line 1777, in process_node
lopt, node)
File "/home/deep/.local/lib/python2.7/site-packages/theano/gof/opt.py", line 1673, in warn_inplace
return NavigatorOptimizer.warn(exc, nav, repl_pairs, local_opt, node)
File "/home/deep/.local/lib/python2.7/site-packages/theano/gof/opt.py", line 1659, in warn
raise exc
AssertionError:
ConvOp does not work with the gpuarray backend.

Use the new convolution interface to have GPU convolution working:
theano.tensor.nnet.conv2d()

I think using conv2d instead of ConvOp could fix it, but I really have no idea of how much of a work is it. if you'll ever decide to make it work on opencl I will happly make a readme here or on reddit on how to set it up. for now I'll try to figure out how to run with tensorflow!

[awentzonline]

Thanks for giving it a shot with opencl! I think both of those issues need to be solved in keras. I'll have a look at what it would take.

[rayset]

if you'll ever need some opencl testing feel free contact me,
sadly I'm not able to help you more than that.

I read that the developers of neural doodle are looking into opencl too (they also have a theano backend),I'm myself going to test it too tomorrow, if I read something interesting over there I will link it here.