Description
I receive the above error when attempting to train the vanilla_unet. The pipeline works for a unet I wrote that uses "same" padding but was hoping to try the vanilla_unet for it's "valid" padding. I'm not sure what else in my code could have caused this error and would have expected these conditions to have been handled inside the vanilla_unet. Any Recommendations?
initial stack trace below:
Traceback (most recent call last):
File "C:\Users\dpoiesz\Repos\bespin\venv\bespin\lib\site-packages\tensorflow_core\python\framework\tensor_shape.py", line 926, in merge_with
new_dims.append(dim.merge_with(other[i]))
File "C:\Users\dpoiesz\Repos\bespin\venv\bespin\lib\site-packages\tensorflow_core\python\framework\tensor_shape.py", line 309, in merge_with
self.assert_is_compatible_with(other)
File "C:\Users\dpoiesz\Repos\bespin\venv\bespin\lib\site-packages\tensorflow_core\python\framework\tensor_shape.py", line 276, in assert_is_compatible_with
(self, other))
ValueError: Dimensions 256 and 68 are not compatible
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\Users\dpoiesz\Repos\bespin\venv\bespin\lib\site-packages\tensorflow_core\python\ops\nn_impl.py", line 167, in sigmoid_cross_entropy_with_logits
labels.get_shape().merge_with(logits.get_shape())
File "C:\Users\dpoiesz\Repos\bespin\venv\bespin\lib\site-packages\tensorflow_core\python\framework\tensor_shape.py", line 929, in merge_with
raise ValueError("Shapes %s and %s are not compatible" % (self, other))
ValueError: Shapes (None, 256, 256, 1) and (None, 68, 68, 1) are not compatible