(obj, file_name='output')
Convert and save an output tensor from BigGAN in a list of saved images.
        Params:
            obj: tensor or numpy array of shape (batch_size, channels, height, width)
            file_name: path and beggingin of filename to save.
                Images will be saved as `file_name_{image_number}.png`
Convert and save an output tensor from BigGAN in a list of saved images.
        Params:
            obj: tensor or numpy array of shape (batch_size, channels, height, width)
            file_name: path and beggingin of filename to save.
                Images will be saved as `file_name_{image_number}.png`
Convert and save an output tensor from BigGAN in a list of saved images . Params : obj : tensor or numpy array of shape ( batch_size channels height width ) file_name : path and beggingin of filename to save . Images will be saved as file_name_ { image_number } . png
def save_as_images(obj, file_name='output'):
    """ Convert and save an output tensor from BigGAN in a list of saved images.
        Params:
            obj: tensor or numpy array of shape (batch_size, channels, height, width)
            file_name: path and beggingin of filename to save.
                Images will be saved as `file_name_{image_number}.png`
    """
    img = convert_to_images(obj)

    for i, out in enumerate(img):
        current_file_name = file_name + '_%d.png' % i
        logger.info("Saving image to {}".format(current_file_name))
        out.save(current_file_name, 'png')
def save_as_images ( obj , file_name = 'output' ) : img = convert_to_images ( obj ) for i , out in enumerate ( img ) : current_file_name = file_name + '_%d.png' % i logger . info ( "Saving image to {}" . format ( current_file_name ) ) out . save ( current_file_name , 'png' )