Open lawlite19 opened 6 years ago
When I run: THEANO_FLAGS='device=gpu0, floatX=float32, nvcc.fastmath=True' /usr/bin/python iGAN_main.py --model_name outdoor_64
Using gpu device 0: Tesla P100-PCIE-16GB (CNMeM is enabled with initial size: 50.0% of memory, cuDNN not available)
[n_iters] = 40
[top_k] = 16
[average] = False
[morph_steps] = 16
[model_file] = ./models/outdoor_64.dcgan_theano
[d_weight] = 0.0
[interp] = linear
[batch_size] = 64
[framework] = theano
[model_type] = dcgan_theano
[shadow] = False
[model_name] = outdoor_64
[win_size] = 384
LOADING...
('n_layers=', 3)
load model from ./models/outdoor_64.dcgan_theano
3.81 seconds to load theano models
Traceback (most recent call last):
File "iGAN_main.py", line 41, in <module>
model = model_class.Model(model_name=args.model_name, model_file=args.model_file)
File "/root/iGAN/model_def/dcgan_theano.py", line 27, in __init__
self._gen = self.def_gen(self.gen_params, self.gen_batchnorm, n_layers=self.n_layers, n_f=self.n_f, nc=self.nc)
File "/root/iGAN/model_def/dcgan_theano.py", line 40, in def_gen
gx = gen_test(z, gen_params, gen_pl, n_layers=n_layers, n_f=n_f, nc=nc, use_tanh=False)
File "/root/iGAN/model_def/dcgan_theano.py", line 227, in gen_test
hout = relu(batchnorm(deconv(hin, w, subsample=(2, 2), border_mode=(2, 2)), u=u, s=s, g=g, b=b))
File "/root/iGAN/lib/ops.py", line 95, in deconv
d_img = GpuDnnConvGradI()(kerns, img, out, desc)
File "/usr/local/lib/python2.7/dist-packages/theano/sandbox/cuda/dnn.py", line 838, in __init__
if version() < (4000, 4000):
File "/usr/local/lib/python2.7/dist-packages/theano/sandbox/cuda/__init__.py", line 407, in dnn_version
dnn_available.msg)
Exception: ("We can't determine the cudnn version as it is not available", "Can not compile with cuDNN. We got this error:\nnvcc warning : The 'compute_20', 'sm_20', and 'sm_21' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).\n/usr/bin/ld: cannot find -lcudnn\ncollect2: error: ld returned 1 exit status\n")
The code is only tested with an older Theano version as well as old GPUs and CUDNN. Could you run other Theano demo code such as this one?
mine is similar, I am on windows and i have this problem:
[model_file] = ./models/outdoor_64.dcgan_theano
[shadow] = False
[top_k] = 16
[n_iters] = 40
[framework] = theano
[interp] = linear
[win_size] = 384
[model_type] = dcgan_theano
[morph_steps] = 16
[batch_size] = 64
[model_name] = outdoor_64
[d_weight] = 0.0
[average] = False
LOADING...
n_layers= 3
load model from ./models/outdoor_64.dcgan_theano
3.09 seconds to load theano models
Traceback (most recent call last):
File "iGAN_main.py", line 41, in <module>
model = model_class.Model(model_name=args.model_name, model_file=args.model_file)
File "C:\Users\Alan\Desktop\gits\iGAN\model_def\dcgan_theano.py", line 27, in __init__
self._gen = self.def_gen(self.gen_params, self.gen_batchnorm, n_layers=self.n_layers, n_f=self.n_f, nc=self.nc)
File "C:\Users\Alan\Desktop\gits\iGAN\model_def\dcgan_theano.py", line 40, in def_gen
gx = gen_test(z, gen_params, gen_pl, n_layers=n_layers, n_f=n_f, nc=nc, use_tanh=False)
File "C:\Users\Alan\Desktop\gits\iGAN\model_def\dcgan_theano.py", line 227, in gen_test
hout = relu(batchnorm(deconv(hin, w, subsample=(2, 2), border_mode=(2, 2)), u=u, s=s, g=g, b=b))
File "C:\Users\Alan\Desktop\gits\iGAN\lib\ops.py", line 95, in deconv
d_img = GpuDnnConvGradI()(kerns, img, out, desc)
File "C:\ProgramData\Anaconda3\lib\site-packages\theano\sandbox\cuda\dnn.py", line 859, in __init__
if version() < (5000, 5000):
File "C:\ProgramData\Anaconda3\lib\site-packages\theano\sandbox\cuda\__init__.py", line 424, in dnn_version
dnn_available.msg)
Exception: ("We can't determine the cudnn version as it is not available", 'CUDA not available')
I have installed cuda and cudnn, and I run
THEANO_FLAGS='device=cpu, floatX=float32, nvcc.fastmath=True' /usr/bin/python iGAN_main.py --model_name outdoor_64
, the error message is:Theano (0.8.2) cuda (8.0) cudnn(5.1)
envionment variable:![image](https://user-images.githubusercontent.com/14356062/34663614-9766b9a0-f492-11e7-89f5-bc2f51c496e6.png)
Thank you!