Sure, in the following model, i need to convert conv1 layer to numpy :
input = Input(shape=(48, 48, 1))
conv1 = Conv2D(32, kernel_size=5, padding='same')(input)
# here i need to convert conv1 to numpy #

Conv1 is a KerasTensor of shape ([None, 48, 48, 32]) i need to convert it to numpy  to iterate over the 32 feature maps and manipulate them individually, then wrap them all into single list and convert it to KerasTensor to be fed it to the next layer in the model
Note:  print(conv1)  results :
KerasTensor(type_spec=TensorSpec(shape=(None, 48, 48, 32), dtype=tf.float32, name=None), name=‘conv2d/BiasAdd:0’, description=“created by layer ‘conv2d’”)
and, conv1.shape results :
(None, 48, 48, 32)
Thanks alot for your patience and help