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I am trying to reproduce the code on a V100 instance and I ran into the following issues when I ran python NPE.py
Do you have any recommendations on how we can reproduce your experimental setup in the form of a Dockerfile?
/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/matplotlib/__init__.py:1067: UserWarning: Duplicate key in file "/home/ubuntu/.config/matplotlib/matplotlibrc", line #2
(fname, cnt))
/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/matplotlib/__init__.py:1067: UserWarning: Duplicate key in file "/home/ubuntu/.config/matplotlib/matplotlibrc", line #3
(fname, cnt))
Loading weights
Compiling Theano Functions
ERROR (theano.gof.opt): Optimization failure due to: LocalOptGroup(local_abstractconv_gemm,local_abstractconv_gradweight_gemm,local_abstractconv_gradinputs_gemm,local_abstractconv3d_gemm,local_abstractconv3d_gradweight_gemm,local_abstractconv3d_gradinputs_gemm,local_conv2d_cpu,local_conv2d_gradweight_cpu,local_conv2d_gradinputs_cpu)
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode=(2, 2), subsample=(2, 2), filter_flip=False, imshp=(None, 3, 64, 64), kshp=(128, 3, 5, 5), filter_dilation=(1, 1), num_groups=1, unshared=False}(X, enc_conv1.W)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/theano/gof/opt.py", line 2074, in process_node
remove=remove)
File "/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/theano/gof/toolbox.py", line 569, in replace_all_validate_remove
chk = fgraph.replace_all_validate(replacements, reason)
File "/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/theano/gof/toolbox.py", line 518, in replace_all_validate
fgraph.replace(r, new_r, reason=reason, verbose=False)
File "/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/theano/gof/fg.py", line 486, in replace
". The type of the replacement must be the same.", old, new)
BadOptimization: BadOptimization Error
Variable: id 139714617198864 CorrMM{((2, 2), (2, 2)), (2, 2), (1, 1), 1 False}.0
Op CorrMM{((2, 2), (2, 2)), (2, 2), (1, 1), 1 False}(Elemwise{Cast{float64}}.0, enc_conv1.W)
Value Type: <type 'NoneType'>
Old Value: None
New Value: None
Reason: LocalOptGroup(local_abstractconv_gemm,local_abstractconv_gradweight_gemm,local_abstractconv_gradinputs_gemm,local_abstractconv3d_gemm,local_abstractconv3d_gradweight_gemm,local_abstractconv3d_gradinputs_gemm,local_conv2d_cpu,local_conv2d_gradweight_cpu,local_conv2d_gradinputs_cpu). The type of the replacement must be the same.
Old Graph:
AbstractConv2d{convdim=2, border_mode=(2, 2), subsample=(2, 2), filter_flip=False, imshp=(None, 3, 64, 64), kshp=(128, 3, 5, 5), filter_dilation=(1, 1), num_groups=1, unshared=False} [id A] <TensorType(float32, 4D)> ''
|X [id B] <TensorType(float32, 4D)>
|enc_conv1.W [id C] <TensorType(float64, 4D)>
New Graph:
CorrMM{((2, 2), (2, 2)), (2, 2), (1, 1), 1 False} [id D] <TensorType(float64, 4D)> ''
|Elemwise{Cast{float64}} [id E] <TensorType(float64, 4D)> ''
| |X [id B] <TensorType(float32, 4D)>
|enc_conv1.W [id C] <TensorType(float64, 4D)>
Hint: relax the tolerance by setting tensor.cmp_sloppy=1
or even tensor.cmp_sloppy=2 for less-strict comparison
ERROR (theano.gof.opt): Optimization failure due to: LocalOptGroup(local_abstractconv_gemm,local_abstractconv_gradweight_gemm,local_abstractconv_gradinputs_gemm,local_abstractconv3d_gemm,local_abstractconv3d_gradweight_gemm,local_abstractconv3d_gradinputs_gemm,local_conv2d_cpu,local_conv2d_gradweight_cpu,local_conv2d_gradinputs_cpu)
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode=(2, 2), subsample=(2, 2), filter_flip=False, imshp=(None, 3, 64, 64), kshp=(128, 3, 5, 5), filter_dilation=(1, 1), num_groups=1, unshared=False}(X, enc_conv1.W)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/theano/gof/opt.py", line 2074, in process_node
remove=remove)
File "/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/theano/gof/toolbox.py", line 569, in replace_all_validate_remove
chk = fgraph.replace_all_validate(replacements, reason)
File "/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/theano/gof/toolbox.py", line 518, in replace_all_validate
fgraph.replace(r, new_r, reason=reason, verbose=False)
File "/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/theano/gof/fg.py", line 486, in replace
". The type of the replacement must be the same.", old, new)
BadOptimization: BadOptimization Error
Variable: id 139714617838416 CorrMM{((2, 2), (2, 2)), (2, 2), (1, 1), 1 False}.0
Op CorrMM{((2, 2), (2, 2)), (2, 2), (1, 1), 1 False}(Elemwise{Cast{float64}}.0, enc_conv1.W)
Value Type: <type 'NoneType'>
Old Value: None
New Value: None
Reason: LocalOptGroup(local_abstractconv_gemm,local_abstractconv_gradweight_gemm,local_abstractconv_gradinputs_gemm,local_abstractconv3d_gemm,local_abstractconv3d_gradweight_gemm,local_abstractconv3d_gradinputs_gemm,local_conv2d_cpu,local_conv2d_gradweight_cpu,local_conv2d_gradinputs_cpu). The type of the replacement must be the same.
Old Graph:
AbstractConv2d{convdim=2, border_mode=(2, 2), subsample=(2, 2), filter_flip=False, imshp=(None, 3, 64, 64), kshp=(128, 3, 5, 5), filter_dilation=(1, 1), num_groups=1, unshared=False} [id A] <TensorType(float32, 4D)> ''
|X [id B] <TensorType(float32, 4D)>
|enc_conv1.W [id C] <TensorType(float64, 4D)>
New Graph:
CorrMM{((2, 2), (2, 2)), (2, 2), (1, 1), 1 False} [id D] <TensorType(float64, 4D)> ''
|Elemwise{Cast{float64}} [id E] <TensorType(float64, 4D)> ''
| |X [id B] <TensorType(float32, 4D)>
|enc_conv1.W [id C] <TensorType(float64, 4D)>
Hint: relax the tolerance by setting tensor.cmp_sloppy=1
or even tensor.cmp_sloppy=2 for less-strict comparison
ERROR (theano.gof.opt): Optimization failure due to: LocalOptGroup(local_abstractconv_gemm,local_abstractconv_gradweight_gemm,local_abstractconv_gradinputs_gemm,local_abstractconv3d_gemm,local_abstractconv3d_gradweight_gemm,local_abstractconv3d_gradinputs_gemm,local_conv2d_cpu,local_conv2d_gradweight_cpu,local_conv2d_gradinputs_cpu)
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode=(2, 2), subsample=(2, 2), filter_flip=False, imshp=(None, 3, 64, 64), kshp=(128, 3, 5, 5), filter_dilation=(1, 1), num_groups=1, unshared=False}(X, enc_conv1.W)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/theano/gof/opt.py", line 2074, in process_node
remove=remove)
File "/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/theano/gof/toolbox.py", line 569, in replace_all_validate_remove
chk = fgraph.replace_all_validate(replacements, reason)
File "/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/theano/gof/toolbox.py", line 518, in replace_all_validate
fgraph.replace(r, new_r, reason=reason, verbose=False)
File "/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/theano/gof/fg.py", line 486, in replace
". The type of the replacement must be the same.", old, new)
BadOptimization: BadOptimization Error
Variable: id 139714617837136 CorrMM{((2, 2), (2, 2)), (2, 2), (1, 1), 1 False}.0
Op CorrMM{((2, 2), (2, 2)), (2, 2), (1, 1), 1 False}(Elemwise{Cast{float64}}.0, enc_conv1.W)
Value Type: <type 'NoneType'>
Old Value: None
New Value: None
Reason: LocalOptGroup(local_abstractconv_gemm,local_abstractconv_gradweight_gemm,local_abstractconv_gradinputs_gemm,local_abstractconv3d_gemm,local_abstractconv3d_gradweight_gemm,local_abstractconv3d_gradinputs_gemm,local_conv2d_cpu,local_conv2d_gradweight_cpu,local_conv2d_gradinputs_cpu). The type of the replacement must be the same.
Old Graph:
AbstractConv2d{convdim=2, border_mode=(2, 2), subsample=(2, 2), filter_flip=False, imshp=(None, 3, 64, 64), kshp=(128, 3, 5, 5), filter_dilation=(1, 1), num_groups=1, unshared=False} [id A] <TensorType(float32, 4D)> ''
|X [id B] <TensorType(float32, 4D)>
|enc_conv1.W [id C] <TensorType(float64, 4D)>
New Graph:
CorrMM{((2, 2), (2, 2)), (2, 2), (1, 1), 1 False} [id D] <TensorType(float64, 4D)> ''
|Elemwise{Cast{float64}} [id E] <TensorType(float64, 4D)> ''
| |X [id B] <TensorType(float32, 4D)>
|enc_conv1.W [id C] <TensorType(float64, 4D)>
Hint: relax the tolerance by setting tensor.cmp_sloppy=1
or even tensor.cmp_sloppy=2 for less-strict comparison
ERROR (theano.gof.opt): Optimization failure due to: LocalOptGroup(local_abstractconv_gemm,local_abstractconv_gradweight_gemm,local_abstractconv_gradinputs_gemm,local_abstractconv3d_gemm,local_abstractconv3d_gradweight_gemm,local_abstractconv3d_gradinputs_gemm,local_conv2d_cpu,local_conv2d_gradweight_cpu,local_conv2d_gradinputs_cpu)
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode=(2, 2), subsample=(2, 2), filter_flip=False, imshp=(None, 3, 64, 64), kshp=(128, 3, 5, 5), filter_dilation=(1, 1), num_groups=1, unshared=False}(X, enc_conv1.W)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/theano/gof/opt.py", line 2074, in process_node
remove=remove)
File "/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/theano/gof/toolbox.py", line 569, in replace_all_validate_remove
chk = fgraph.replace_all_validate(replacements, reason)
File "/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/theano/gof/toolbox.py", line 518, in replace_all_validate
fgraph.replace(r, new_r, reason=reason, verbose=False)
File "/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/theano/gof/fg.py", line 486, in replace
". The type of the replacement must be the same.", old, new)
BadOptimization: BadOptimization Error
Variable: id 139714617737296 CorrMM{((2, 2), (2, 2)), (2, 2), (1, 1), 1 False}.0
Op CorrMM{((2, 2), (2, 2)), (2, 2), (1, 1), 1 False}(Elemwise{Cast{float64}}.0, enc_conv1.W)
Value Type: <type 'NoneType'>
Old Value: None
New Value: None
Reason: LocalOptGroup(local_abstractconv_gemm,local_abstractconv_gradweight_gemm,local_abstractconv_gradinputs_gemm,local_abstractconv3d_gemm,local_abstractconv3d_gradweight_gemm,local_abstractconv3d_gradinputs_gemm,local_conv2d_cpu,local_conv2d_gradweight_cpu,local_conv2d_gradinputs_cpu). The type of the replacement must be the same.
Old Graph:
AbstractConv2d{convdim=2, border_mode=(2, 2), subsample=(2, 2), filter_flip=False, imshp=(None, 3, 64, 64), kshp=(128, 3, 5, 5), filter_dilation=(1, 1), num_groups=1, unshared=False} [id A] <TensorType(float32, 4D)> ''
|X [id B] <TensorType(float32, 4D)>
|enc_conv1.W [id C] <TensorType(float64, 4D)>
New Graph:
CorrMM{((2, 2), (2, 2)), (2, 2), (1, 1), 1 False} [id D] <TensorType(float64, 4D)> ''
|Elemwise{Cast{float64}} [id E] <TensorType(float64, 4D)> ''
| |X [id B] <TensorType(float32, 4D)>
|enc_conv1.W [id C] <TensorType(float64, 4D)>
Hint: relax the tolerance by setting tensor.cmp_sloppy=1
or even tensor.cmp_sloppy=2 for less-strict comparison
ERROR (theano.gof.opt): Optimization failure due to: local_abstractconv_check
ERROR (theano.gof.opt): node: AbstractConv2d{convdim=2, border_mode=(2, 2), subsample=(2, 2), filter_flip=False, imshp=(None, 3, 64, 64), kshp=(128, 3, 5, 5), filter_dilation=(1, 1), num_groups=1, unshared=False}(X, enc_conv1.W)
ERROR (theano.gof.opt): TRACEBACK:
ERROR (theano.gof.opt): Traceback (most recent call last):
File "/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/theano/gof/opt.py", line 2034, in process_node
replacements = lopt.transform(node)
File "/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/theano/tensor/nnet/opt.py", line 500, in local_abstractconv_check
node.op.__class__.__name__)
LocalMetaOptimizerSkipAssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
Traceback (most recent call last):
File "NPE.py", line 19, in <module>
model = IAN(config_path = 'IAN_simple.py', dnn = False)
File "/home/ubuntu/Neural-Photo-Editor/API.py", line 51, in __init__
self.Z_hat_fn = theano.function([self.X],self.Z_hat)
File "/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/theano/compile/function.py", line 317, in function
output_keys=output_keys)
File "/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/theano/compile/pfunc.py", line 486, in pfunc
output_keys=output_keys)
File "/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/theano/compile/function_module.py", line 1839, in orig_function
name=name)
File "/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/theano/compile/function_module.py", line 1519, in __init__
optimizer_profile = optimizer(fgraph)
File "/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/theano/gof/opt.py", line 108, in __call__
return self.optimize(fgraph)
File "/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/theano/gof/opt.py", line 97, in optimize
ret = self.apply(fgraph, *args, **kwargs)
File "/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/theano/gof/opt.py", line 251, in apply
sub_prof = optimizer.optimize(fgraph)
File "/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/theano/gof/opt.py", line 97, in optimize
ret = self.apply(fgraph, *args, **kwargs)
File "/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/theano/gof/opt.py", line 2143, in apply
nb += self.process_node(fgraph, node)
File "/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/theano/gof/opt.py", line 2039, in process_node
lopt, node)
File "/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/theano/gof/opt.py", line 1933, in warn_inplace
return NavigatorOptimizer.warn(exc, nav, repl_pairs, local_opt, node)
File "/home/ubuntu/anaconda3/envs/python2/lib/python2.7/site-packages/theano/gof/opt.py", line 1919, in warn
raise exc
theano.gof.opt.LocalMetaOptimizerSkipAssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against? On the CPU we do not support float16.
The text was updated successfully, but these errors were encountered:
I've not used Docker at all (well, I've not successfully used Docker at all), but I can try to point you in the right direction. I was running this with python 2.7.12, Theano 0.7 or 0.8, and Lasagne 0.2 back in 2016, on GTX 980s and my laptop GPU for inference (GT730m).
At the end of the day though, I'm not sure you'll be able to run it on the V100s, what with Theano being deprecated and this code being 2+ years old at this point.
If you just want to use the interface, it should be trivial to plug in a PyTorch/Chainer/TF pre-trained GAN, just implement the appropriate methods in API.py.
Hi,
I am trying to reproduce the code on a V100 instance and I ran into the following issues when I ran
python NPE.py
Do you have any recommendations on how we can reproduce your experimental setup in the form of a Dockerfile?
The text was updated successfully, but these errors were encountered: