Learning | AFO

from keras.applications.vgg16 import VGG16
from keras.applications.vgg16 import preprocess_input
import keras.backend as K
import numpy as np
import json
import shap

# load pre-trained model and choose two images to explain
model = VGG16(weights='im  

# ...include code from https://github.com/keras-team/keras/blob/master/examples/mnist_cnn.py

import shap
import numpy as np

# select a set of background examples to take an expectation over
background = x_train[np.random.choice(x_train.shape[0], 10  

def deprecated_internal_learning_phase_scope(value):
  """An internal-only version of `learning_phase_scope`.

  Unlike the public method, this method does not raise a deprecation warning.
  This is needed because saved model saving needs to set lear  

def set_learning_phase(value):
  """Sets the learning phase to a fixed value.

  The backend learning phase affects any code that calls
  `backend.learning_phase()`
  In particular, all Keras built-in layers use the learning phase as the default
  fo  

def eager_learning_phase_scope(value):
  """Internal scope that sets the learning phase in eager / tf.function only.

  Args:
      value: Learning phase value, either 0 or 1 (integers).
             0 = test, 1 = train

  Yields:
    None.

  Raises