ValueError: padding must be zero for average_exc_pad
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Mnd Daniel
Aug 8, 2019, 3:57:19 AM8/8/19
to theano-users
Im trying to fine tune InceptionV3 to binary classification. I have follow the code at keras.io but got this error instead. I'm using theano backend with python 3.5, keras=2.2.4. Also I do not understand the hint at the end of error code.
HINT: Use the Theano flag 'exception_verbosity=high' for a debugprint and storage map footprint of this apply node.
Coding
inceptionV3_model=keras.applications.inception_v3.InceptionV3(weights='imagenet', include_top=False)
x = inceptionV3_model.output
x = GlobalAveragePooling2D()(x)
x = Dense(1024, activation='relu')(x)
predictions = Dense(2, activation='softmax')(x)
model = Model(inputs=inceptionV3_model.input, outputs=predictions)
for layer in inceptionV3_model.layers:
layer.trainable = False
model.compile(Adam(lr=.0001), loss='categorical_crossentropy',
metrics=['accuracy'])
history=model.fit_generator(train_batches, steps_per_epoch=10,
validation_data=valid_batches,
validation_steps=10, epochs=10, verbose=2)
for layer in model.layers[:249]:
layer.trainable = False
for layer in model.layers[249:]:
layer.trainable = True
model.compile(Adam(lr=.0001), loss='categorical_crossentropy',
metrics=['accuracy'])
history=model.fit_generator(train_batches, steps_per_epoch=10,
validation_data=valid_batches,
validation_steps=10, epochs=150, verbose=2)
Error
ValueError Traceback (most recent call last) ~\AppData\Roaming\Python\Python37\site-packages\theano\compile\function_module.py in __call__(self, *args, **kwargs) 902 outputs =\ --> 903 self.fn() if output_subset is None else\ 904 self.fn(output_subset=output_subset) ValueError: padding must be zero for average_exc_pad During handling of the above exception, another exception occurred: ValueError Traceback (most recent call last) <ipython-input-42-347232762e6a> in <module> 1 history=model.fit_generator(train_batches, steps_per_epoch=10, 2 validation_data=valid_batches, ----> 3 validation_steps=10, epochs=150, verbose=2) C:\ProgramData\Anaconda3\lib\site-packages\keras\legacy\interfaces.py in wrapper(*args, **kwargs) 89 warnings.warn('Update your `' + object_name + '` call to the ' + 90 'Keras 2 API: ' + signature, stacklevel=2) ---> 91 return func(*args, **kwargs) 92 wrapper._original_function = func 93 return wrapper C:\ProgramData\Anaconda3\lib\site-packages\keras\engine\training.py in fit_generator(self, generator, steps_per_epoch, epochs, verbose, callbacks, validation_data, validation_steps, class_weight, max_queue_size, workers, use_multiprocessing, shuffle, initial_epoch) 1416 use_multiprocessing=use_multiprocessing, 1417 shuffle=shuffle, -> 1418 initial_epoch=initial_epoch) 1419 1420 @interfaces.legacy_generator_methods_support C:\ProgramData\Anaconda3\lib\site-packages\keras\engine\training_generator.py in fit_generator(model, generator, steps_per_epoch, epochs, verbose, callbacks, validation_data, validation_steps, class_weight, max_queue_size, workers, use_multiprocessing, shuffle, initial_epoch) 215 outs = model.train_on_batch(x, y, 216 sample_weight=sample_weight, --> 217 class_weight=class_weight) 218 219 outs = to_list(outs) C:\ProgramData\Anaconda3\lib\site-packages\keras\engine\training.py in train_on_batch(self, x, y, sample_weight, class_weight) 1215 ins = x + y + sample_weights 1216 self._make_train_function() -> 1217 outputs = self.train_function(ins) 1218 return unpack_singleton(outputs) 1219 C:\ProgramData\Anaconda3\lib\site-packages\keras\backend\theano_backend.py in __call__(self, inputs) 1386 def __call__(self, inputs): 1387 assert isinstance(inputs, (list, tuple)) -> 1388 return self.function(*inputs) 1389 1390 ~\AppData\Roaming\Python\Python37\site-packages\theano\compile\function_module.py in __call__(self, *args, **kwargs) 915 node=self.fn.nodes[self.fn.position_of_error], 916 thunk=thunk, --> 917 storage_map=getattr(self.fn, 'storage_map', None)) 918 else: 919 # old-style linkers raise their own exceptions ~\AppData\Roaming\Python\Python37\site-packages\theano\gof\link.py in raise_with_op(node, thunk, exc_info, storage_map) 323 # extra long error message in that case. 324 pass --> 325 reraise(exc_type, exc_value, exc_trace) 326 327 ~\AppData\Roaming\Python\Python37\site-packages\six.py in reraise(tp, value, tb) 690 value = tp() 691 if value.__traceback__ is not tb: --> 692 raise value.with_traceback(tb) 693 raise value 694 finally: ~\AppData\Roaming\Python\Python37\site-packages\theano\compile\function_module.py in __call__(self, *args, **kwargs) 901 try: 902 outputs =\ --> 903 self.fn() if output_subset is None else\ 904 self.fn(output_subset=output_subset) 905 except Exception: ValueError: padding must be zero for average_exc_pad Apply node that caused the error: AveragePoolGrad{ignore_border=True, mode='average_exc_pad', ndim=2}(Join.0, IncSubtensor{InplaceInc;::, ::, :int64:, :int64:}.0, TensorConstant{(2,) of 3}, TensorConstant{(2,) of 1}, TensorConstant{(2,) of 1}) Toposort index: 4151 Inputs types: [TensorType(float32, 4D), TensorType(float32, 4D), TensorType(int32, vector), TensorType(int32, vector), TensorType(int32, vector)] Inputs shapes: [(10, 2048, 5, 5), (10, 2048, 5, 5), (2,), (2,), (2,)] Inputs strides: [(204800, 100, 20, 4), (204800, 100, 20, 4), (4,), (4,), (4,)] Inputs values: ['not shown', 'not shown', array([3, 3]), array([1, 1]), array([1, 1])] Outputs clients: [[Elemwise{add,no_inplace}(CorrMM_gradInputs{half, (1, 1), (1, 1), 1 False}.0, CorrMM_gradInputs{half, (1, 1), (1, 1), 1 False}.0, CorrMM_gradInputs{half, (1, 1), (1, 1), 1 False}.0, AveragePoolGrad{ignore_border=True, mode='average_exc_pad', ndim=2}.0)]] Backtrace when the node is created(use Theano flag traceback.limit=N to make it longer): File "C:\Users\User\AppData\Roaming\Python\Python37\site-packages\theano\gradient.py", line 1326, in access_grad_cache term = access_term_cache(node)[idx] File "C:\Users\User\AppData\Roaming\Python\Python37\site-packages\theano\gradient.py", line 1021, in access_term_cache output_grads = [access_grad_cache(var) for var in node.outputs] File "C:\Users\User\AppData\Roaming\Python\Python37\site-packages\theano\gradient.py", line 1021, in <listcomp> output_grads = [access_grad_cache(var) for var in node.outputs] File "C:\Users\User\AppData\Roaming\Python\Python37\site-packages\theano\gradient.py", line 1326, in access_grad_cache term = access_term_cache(node)[idx] File "C:\Users\User\AppData\Roaming\Python\Python37\site-packages\theano\gradient.py", line 1021, in access_term_cache output_grads = [access_grad_cache(var) for var in node.outputs] File "C:\Users\User\AppData\Roaming\Python\Python37\site-packages\theano\gradient.py", line 1021, in <listcomp> output_grads = [access_grad_cache(var) for var in node.outputs] File "C:\Users\User\AppData\Roaming\Python\Python37\site-packages\theano\gradient.py", line 1326, in access_grad_cache term = access_term_cache(node)[idx] File "C:\Users\User\AppData\Roaming\Python\Python37\site-packages\theano\gradient.py", line 1162, in access_term_cache new_output_grads) HINT: Use the Theano flag 'exception_verbosity=high' for a debugprint and storage map footprint of this apply node.
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