-
Notifications
You must be signed in to change notification settings - Fork 112
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
load LandscapesBig mode error #5
Comments
I have this issue too. Note that 1536 is 16 * 96. Could this be an issue with BATCH_SIZE? |
Same problem here. Changing the batch size to 1 helped solving this issue. |
I ran the section of code to generateTruncated using one of preexisting
models, LandscapeBig.zip. This is model 28. I commented out the section to
evaluate and train and then amended the model.load parameter to 28.
I'm not sure how necessary it is to have your own data in place in the data
subfolder as these are for training I believe, but I had used 256 by 256
images.
The problem was when I tried to train the code crashes eventually with a
GPU (unfortunately it;s only a 1050 Ti) - possibly some sort of GPU memory
issue, and it would take an extremely long time with a CPU, which I tried
but it looked like it was going to take many days.
so here's my snippet of code
if __name__ == "__main__":
model = StyleGAN(lr = 0.0001, silent = False)
#model.evaluate(0)
#while model.GAN.steps < 1000001:
# model.train()
model.load(28)
n1 = noiseList(64)
n2 = nImage(64)
for i in range(50):
print(i, end = '\r')
model.generateTruncated(n1, noi = n2, trunc = i / 50, outImage =
True, num = i)
…On Sat, 8 Feb 2020 at 14:03, derveit ***@***.***> wrote:
tensorflow.python.framework.errors_impl.InvalidArgumentError: input and
filter must have the same depth: 1536 vs 96
Same problem here. Changing the batch size to 1 helped solving this issue.
Unfortunately there is no output image created. @pyrator
<https://github.com/pyrator> : What dimensions and format do your images
have? Thanks.
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
<#5?email_source=notifications&email_token=AAUZPLGD32NE5KOHEEJWKBLRB23R3A5CNFSM4KL4GW3KYY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOELFSPPA#issuecomment-583739324>,
or unsubscribe
<https://github.com/notifications/unsubscribe-auth/AAUZPLFXGWCNUINBN7MYMB3RB23R3ANCNFSM4KL4GW3A>
.
|
Same problem. If you set the batch size to |
model.load(28)
error
2020-01-27 14:14:23.735268: W tensorflow/core/common_runtime/base_collective_executor.cc:216] BaseCollectiveExecutor::StartAbort Invalid argument: input and filter must have the same depth: 1536 vs 96
[[{{node conv2d_mod_23/Conv2D}}]]
Traceback (most recent call last):
File "/Users/pig/PycharmProjects/StyleGAN2-Tensorflow-2.0/stylegan_two.py", line 646, in
model.generateTruncated(n1, noi = n2, trunc = i / 50, outImage = True, num = i)
File "/Users/pig/PycharmProjects/StyleGAN2-Tensorflow-2.0/stylegan_two.py", line 567, in generateTruncated
generated_images = self.GAN.GE.predict(w_space + [noi], batch_size = BATCH_SIZE)
File "/Users/pig/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training.py", line 909, in predict
use_multiprocessing=use_multiprocessing)
File "/Users/pig/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training_arrays.py", line 722, in predict
callbacks=callbacks)
File "/Users/pig/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training_arrays.py", line 393, in model_iteration
batch_outs = f(ins_batch)
File "/Users/pig/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow_core/python/keras/backend.py", line 3740, in call
outputs = self._graph_fn(*converted_inputs)
File "/Users/pig/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow_core/python/eager/function.py", line 1081, in call
return self._call_impl(args, kwargs)
File "/Users/pig/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow_core/python/eager/function.py", line 1121, in _call_impl
return self._call_flat(args, self.captured_inputs, cancellation_manager)
File "/Users/pig/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow_core/python/eager/function.py", line 1224, in _call_flat
ctx, args, cancellation_manager=cancellation_manager)
File "/Users/pig/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow_core/python/eager/function.py", line 511, in call
ctx=ctx)
File "/Users/pig/anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow_core/python/eager/execute.py", line 67, in quick_execute
six.raise_from(core._status_to_exception(e.code, message), None)
File "", line 3, in raise_from
tensorflow.python.framework.errors_impl.InvalidArgumentError: input and filter must have the same depth: 1536 vs 96
[[node conv2d_mod_23/Conv2D (defined at /anaconda3/envs/tf2/lib/python3.6/site-packages/tensorflow_core/python/framework/ops.py:1751) ]] [Op:__inference_keras_scratch_graph_20999]
Function call stack:
keras_scratch_graph
The text was updated successfully, but these errors were encountered: