code: def make_pixel_mask(
      image: np.ndarray,
      output_size: Tuple[int, int],
      input_data_format: Optional[Union[str, ChannelDimension]] = None,
  ) -> np.ndarray:
      """
      Make a pixel mask for the image, where 1 indicates a valid pixel and 0 indicates padding.
  
      Args:
          image (`np.ndarray`):
              Image to make the pixel mask for.
          output_size (`Tuple[int, int]`):
              Output size of the mask.
      """
      input_height, input_width = get_image_size(
          image, channel_dim=input_data_format
      )
      mask = np.zeros(output_size, dtype=np.int64)
      mask[:input_height, :input_width] = 1
      return mask
  
imports: import io
  import pathlib
  from collections import defaultdict
  from typing import Any, Callable, Dict, Iterable, List, Optional, Set, Tuple, Union
  import numpy
  from ...feature_extraction_utils import BatchFeature
  from ...image_processing_utils import BaseImageProcessor, get_size_dict
  from ...image_transforms import PaddingMode, center_to_corners_format, corners_to_center_format, id_to_rgb, pad, rescale, resize, rgb_to_id, to_channel_dimension_format
  from ...image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD, AnnotationFormat, AnnotationType, ChannelDimension, ImageInput, PILImageResampling, get_image_size, infer_channel_dimension_format, is_scaled_image, make_list_of_images, to_numpy_array, valid_images, validate_annotations
  from ...utils import TensorType, is_flax_available, is_jax_tensor, is_scipy_available, is_tf_available, is_tf_tensor, is_torch_available, is_torch_tensor, is_vision_available, logging
label_desc: Use image node_id 8 for calling a global function with example usage: make_pixel_mask(image, output_size, input_data_format) and returns: mask