Keras 应用、生成器方法的 API 改进。
preprocess_input in all Keras applications compatible with both Numpy arrays and symbolic tensors (previously only supported Numpy arrays).
weights argument in all Keras applications to accept the path to a custom weights file to load (previously only supported the built-in
imagenet weights file).
steps_per_epoch behavior change in generator training/evaluation methods:
If specified, the specified value will be used (previously, in the case of generator of type
Sequence, the specified value was overridden by the
If unspecified and if the generator passed is a
Sequence, we set it to the
workers=0 in generator training/evaluation methods (will run the generator in the main process, in a blocking way).
interpolation argument in
ImageDataGenerator.flow_from_directory, allowing a custom interpolation method for image resizing.
gpus argument in
multi_gpu_model to be a list of specific GPU ids.