Sync docstring of preprocess_input with _preprocess_numpy_input and _preprocess_symbolic_input in imagenet_utils.py
@@ -152,13 +152,16 @@ def preprocess_input(x, data_format=None, mode='caffe'):
# Arguments
x: Input Numpy or symbolic tensor, 3D or 4D.
data_format: Data format of the image tensor/array.
- mode: One of "caffe", "tf".
+ mode: One of "caffe", "tf" or "torch".
- caffe: will convert the images from RGB to BGR,
then will zero-center each color channel with
respect to the ImageNet dataset,
without scaling.
- tf: will scale pixels between -1 and 1,
sample-wise.
+ - torch: will scale pixels between 0 and 1 and then
+ will normalize each channel with respect to the
+ ImageNet dataset.
# Returns
Preprocessed tensor or Numpy array.
