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Output of powershell after command python train_image.py --example_config golden_horse.yaml:
Traceback (most recent call last):
File "C:\Users\CodeSame\miniconda3\text2live\train_image.py", line 129, in <module>
train_model(config)
File "C:\Users\CodeSame\miniconda3\text2live\train_image.py", line 24, in train_model
seed = np.random.randint(2 ** 32)
File "mtrand.pyx", line 763, in numpy.random.mtrand.RandomState.randint
File "_bounded_integers.pyx", line 1336, in numpy.random._bounded_integers._rand_int32
ValueError: high is out of bounds for int32
On my own, I was able to run this neural network by replacing in the 24th line of the file train_image.py the value from seed = np.random.randint(2** 32) to seed = np.random.randint(2** 31). BUT now all the other errors remain in the output. You can specify specific software versions and PC system requirements, if any.
The text was updated successfully, but these errors were encountered:
I have the same. I handled with 32bit issue but now it just show me some CUDA error, I sync up my torch with CUDA Toolkit but still same situation. Probably, 32gb Tesla isn't fun recommendation, it is in must need :D
I have the same. I handled with 32bit issue but now it just show me some CUDA error, I sync up my torch with CUDA Toolkit but still same situation. Probably, 32gb Tesla isn't fun recommendation, it is in must need :D
Output of powershell after command python train_image.py --example_config golden_horse.yaml:
On my own, I was able to run this neural network by replacing in the 24th line of the file train_image.py the value from seed = np.random.randint(2** 32) to seed = np.random.randint(2** 31). BUT now all the other errors remain in the output. You can specify specific software versions and PC system requirements, if any.
The text was updated successfully, but these errors were encountered: