mkocaoglu / causalgan Goto Github PK
View Code? Open in Web Editor NEWLicense: MIT License
License: MIT License
Hello Murat,
I tried to run the code using 0 GPUs, and it gave me errors on both BEGAN and DCGAN. I am not able to test on the default 1 GPU because I don't have any. Do you know what might be causing this?
The command I entered was the following:
python main.py --causal_model big_causal_graph --is_pretrain True --model_type dcgan --is_train True --num_gpu 0
And I got the following output:
C:\Users\kayan\anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\framework\dtypes.py:455: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint8 = np.dtype([("qint8", np.int8, 1)])
C:\Users\kayan\anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\framework\dtypes.py:456: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_quint8 = np.dtype([("quint8", np.uint8, 1)])
C:\Users\kayan\anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\framework\dtypes.py:457: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint16 = np.dtype([("qint16", np.int16, 1)])
C:\Users\kayan\anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\framework\dtypes.py:458: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_quint16 = np.dtype([("quint16", np.uint16, 1)])
C:\Users\kayan\anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\framework\dtypes.py:459: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint32 = np.dtype([("qint32", np.int32, 1)])
C:\Users\kayan\anaconda3\envs\tensorflow\lib\site-packages\tensorflow\python\framework\dtypes.py:462: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
np_resource = np.dtype([("resource", np.ubyte, 1)])
tf: resetting default graph!
Loaded ./config.py
Loaded ./causal_controller/config.py
Loaded ./causal_dcgan/config.py
Loaded ./causal_began/config.py
saving config because load path not given
[] MODEL dir: logs\celebA_0728_103822
[] PARAM path: logs\celebA_0728_103822\params.json
[] PARAM path: logs\celebA_0728_103822\cc_params.json
[] PARAM path: logs\celebA_0728_103822\dcgan_params.json
[*] PARAM path: logs\celebA_0728_103822\began_params.json
setting up CausalController
causal graph size: 9
setting up data
setup pretrain
setting up pretrain: CausalController
causalcontroller has 58 summaries
WARNING:CausalGAN.rec_loss_coff= 0.0
Filling queue with 202 Celeb images before starting to train. I don't know how long this will take
2021-07-28 10:38:32.942722: W c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE instructions, but these are available on your machine and could speed up CPU computations.
2021-07-28 10:38:32.942937: W c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE2 instructions, but these are available on your machine and could speed up CPU computations.
2021-07-28 10:38:32.943087: W c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE3 instructions, but these are available on your machine and could speed up CPU computations.
2021-07-28 10:38:32.943198: W c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
2021-07-28 10:38:32.943308: W c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2021-07-28 10:38:32.943489: W c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2021-07-28 10:38:32.944325: W c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2021-07-28 10:38:32.945032: W c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
Traceback (most recent call last):
File "main.py", line 87, in
trainer=get_trainer()
File "main.py", line 74, in get_trainer
trainer=Trainer(config,cc_config,model_config)
File "C:\Users\kayan\OneDrive\Desktop\CausalGAN\trainer.py", line 95, in init
self.model.build_train_op()
File "C:\Users\kayan\OneDrive\Desktop\CausalGAN\causal_dcgan\CausalGAN.py", line 287, in build_train_op
.minimize(self.g_loss, var_list=self.g_vars)
AttributeError: 'CausalGAN' object has no attribute 'g_loss'
For the BEGAN, I ran:
python main.py --causal_model big_causal_graph --is_pretrain True --model_type began --is_train True --num_gpu 0
and got the following error:
C:\Users\kayan\anaconda3\envs\tf2\lib\site-packages\tensorflow\python\framework\dtypes.py:458: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint8 = np.dtype([("qint8", np.int8, 1)])
C:\Users\kayan\anaconda3\envs\tf2\lib\site-packages\tensorflow\python\framework\dtypes.py:459: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_quint8 = np.dtype([("quint8", np.uint8, 1)])
C:\Users\kayan\anaconda3\envs\tf2\lib\site-packages\tensorflow\python\framework\dtypes.py:460: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint16 = np.dtype([("qint16", np.int16, 1)])
C:\Users\kayan\anaconda3\envs\tf2\lib\site-packages\tensorflow\python\framework\dtypes.py:461: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_quint16 = np.dtype([("quint16", np.uint16, 1)])
C:\Users\kayan\anaconda3\envs\tf2\lib\site-packages\tensorflow\python\framework\dtypes.py:462: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint32 = np.dtype([("qint32", np.int32, 1)])
C:\Users\kayan\anaconda3\envs\tf2\lib\site-packages\tensorflow\python\framework\dtypes.py:465: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
np_resource = np.dtype([("resource", np.ubyte, 1)])
tf: resetting default graph!
Loaded ./config.py
Loaded ./causal_controller/config.py
Loaded ./causal_dcgan/config.py
Loaded ./causal_began/config.py
saving config because load path not given
[] MODEL dir: logs\celebA_0728_100704
[] PARAM path: logs\celebA_0728_100704\params.json
[] PARAM path: logs\celebA_0728_100704\cc_params.json
[] PARAM path: logs\celebA_0728_100704\dcgan_params.json
[*] PARAM path: logs\celebA_0728_100704\began_params.json
setting up CausalController
causal graph size: 9
setting up data
setup pretrain
setting up pretrain: CausalController
causalcontroller has 58 summaries
Filling queue with 202 Celeb images before starting to train. I don't know how long this will take
2021-07-28 10:07:14.554201: W c:\tf_jenkins\home\workspace\release-win\m\windows\py\36\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE instructions, but these are available on your machine and could speed up CPU computations.
2021-07-28 10:07:14.554405: W c:\tf_jenkins\home\workspace\release-win\m\windows\py\36\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE2 instructions, but these are available on your machine and could speed up CPU computations.
2021-07-28 10:07:14.554999: W c:\tf_jenkins\home\workspace\release-win\m\windows\py\36\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE3 instructions, but these are available on your machine and could speed up CPU computations.
2021-07-28 10:07:14.555208: W c:\tf_jenkins\home\workspace\release-win\m\windows\py\36\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
2021-07-28 10:07:14.555410: W c:\tf_jenkins\home\workspace\release-win\m\windows\py\36\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2021-07-28 10:07:14.555604: W c:\tf_jenkins\home\workspace\release-win\m\windows\py\36\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2021-07-28 10:07:14.555802: W c:\tf_jenkins\home\workspace\release-win\m\windows\py\36\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2021-07-28 10:07:14.556000: W c:\tf_jenkins\home\workspace\release-win\m\windows\py\36\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
Traceback (most recent call last):
File "main.py", line 87, in
trainer=get_trainer()
File "main.py", line 74, in get_trainer
trainer=Trainer(config,cc_config,model_config)
File "C:\Users\kayan\OneDrive\Desktop\CausalGAN\trainer.py", line 95, in init
self.model.build_train_op()
File "C:\Users\kayan\OneDrive\Desktop\CausalGAN\causal_began\CausalBEGAN.py", line 278, in build_train_op
g_optim = self.g_optimizer.apply_gradients(g_grads, global_step=self.step)
File "C:\Users\kayan\anaconda3\envs\tf2\lib\site-packages\tensorflow\python\training\optimizer.py", line 423, in apply_gradients
raise ValueError("No variables provided.")
ValueError: No variables provided.
Undefined names can raise NameError at runtime.
flake8 testing of https://github.com/mkocaoglu/CausalGAN on Python 2.7.13
$ flake8 . --count --select=E901,E999,F821,F822,F823 --show-source --statistics
./causal_dcgan/utils.py:147:16: F821 undefined name 'x'
return x.astype(np.uint8)
^
./causal_dcgan/utils.py:149:18: F821 undefined name 'x'
return ((x+1)/2*255).astype(np.uint8)
^
./figure_scripts/sample.py:157:51: F821 undefined name 'list_labels'
for name, lab, dfl in zip(model.cc.node_names,list_labels,list_d_fake_labels):
^
./figure_scripts/sample.py:157:63: F821 undefined name 'list_d_fake_labels'
for name, lab, dfl in zip(model.cc.node_names,list_labels,list_d_fake_labels):
^
./figure_scripts/sample.py:442:47: F821 undefined name 'nsamples'
outputs[k]=np.vstack(outputs[k])[:nsamples]
^
./figure_scripts/sample.py:507:41: F821 undefined name 'nsamples'
if len(completed_rows)>=nsamples:
^
./figure_scripts/sample.py:585:40: F821 undefined name 'nsamples'
outputs[k]=outputs[k][:nsamples]
^
./figure_scripts/sample.py:592:32: F821 undefined name 'nsamples'
values=outputs[k][:nsamples]
^
The download link of download.py
can not work, could you provide a new download link of your dataset, which is trained by your code.
Hi @mkocaoglu Murat, I try to first train a causal implicit model by using your source code. It ran well if using default one gpu. However, when I set more GPUs, e.g.
python main.py --causal_model big_causal_graph --is_pretrain True --num_gpu 8
I met the error as below. Please help me! Thanks a lot!
setting up pretrain: CausalController
Traceback (most recent call last):
File "main.py", line 89, in
trainer=get_trainer()
File "main.py", line 76, in get_trainer
trainer=Trainer(config,cc_config,model_config)
File "/home/qw/projects/CausalGAN/trainer.py", line 60, in init
self.cc.build_pretrain(label_queue)
File "/home/qw/projects/CausalGAN/causal_controller/CausalController.py", line 179, in build_pretrain
grad_cost,self.dcc_slopes=Grad_Penalty(real_inputs,fake_inputs,self.DCC,self.config)
File "/home/qw/projects/CausalGAN/causal_controller/models.py", line 45, in Grad_Penalty
interpolates = alpha*real_data + ((1-alpha)*fake_data)#Could do more if not fixed batch_size
File "/home/qw/anaconda3/envs/py27/lib/python2.7/site-packages/tensorflow/python/ops/math_ops.py", line 866, in binary_op_wrapper
return func(x, y, name=name)
File "/home/qw/anaconda3/envs/py27/lib/python2.7/site-packages/tensorflow/python/ops/math_ops.py", line 1131, in _mul_dispatch
return gen_math_ops.mul(x, y, name=name)
File "/home/qw/anaconda3/envs/py27/lib/python2.7/site-packages/tensorflow/python/ops/gen_math_ops.py", line 5042, in mul
"Mul", x=x, y=y, name=name)
File "/home/qw/anaconda3/envs/py27/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/home/qw/anaconda3/envs/py27/lib/python2.7/site-packages/tensorflow/python/util/deprecation.py", line 488, in new_func
return func(*args, **kwargs)
File "/home/qw/anaconda3/envs/py27/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 3274, in create_op
op_def=op_def)
File "/home/qw/anaconda3/envs/py27/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1792, in init
control_input_ops)
File "/home/qw/anaconda3/envs/py27/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1631, in _create_c_op
raise ValueError(str(e))
ValueError: Dimensions must be equal, but are 16 and 128 for 'mul_1' (op: 'Mul') with input shapes: [16,1], [128,9].
A declarative, efficient, and flexible JavaScript library for building user interfaces.
๐ Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. ๐๐๐
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google โค๏ธ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.