Loading VGG16/19 with pooling=None still has pooling about keras-applications HOT 2 CLOSED

Thank you for reporting the issue, @weiji14. There is no problem in the current implementations, but the docstrings need to be revised, as you pointed out. The include_top=False, pooling=None arguments should return the last convolutional "block" rather than "layer". The "block" means generally a set of layers, and the "convolutional block" in the ImageNet models typically consists of several convolutional layers followed by (or following) a 2x down-sampling layer.

Thus, it is true that the last output in VGG(include_top=False, pooling=None) is MaxPooling2D (block5_pool). I will revise the docstrings. Thank you!

from keras-applications.

Thanks for the quick fix. I'll close the issue now 😄

from keras-applications.