parameters: (filename, num_images)
docstring: Extract the images into a 4D tensor [image index, y, x, channels].
  
    Values are rescaled from [0, 255] down to [-0.5, 0.5].
docstring_summary: Extract the images into a 4D tensor [image index, y, x, channels].
docstring_tokens: Extract the images into a 4D tensor [ image index y x channels ] .
function: def extract_data(filename, num_images):
    """Extract the images into a 4D tensor [image index, y, x, channels].
  
    Values are rescaled from [0, 255] down to [-0.5, 0.5].
    """
    print('Extracting', filename)
    with gzip.open(filename) as bytestream:
      bytestream.read(16)
      buf = bytestream.read(IMAGE_SIZE * IMAGE_SIZE * num_images * NUM_CHANNELS)
      data = numpy.frombuffer(buf, dtype=numpy.uint8).astype(numpy.float32)
      data = (data - (PIXEL_DEPTH / 2.0)) / PIXEL_DEPTH
      data = data.reshape(num_images, IMAGE_SIZE, IMAGE_SIZE, NUM_CHANNELS)
      return data
function_tokens: def extract_data ( filename , num_images ) : print ( 'Extracting' , filename ) with gzip . open ( filename ) as bytestream : bytestream . read ( 16 ) buf = bytestream . read ( IMAGE_SIZE * IMAGE_SIZE * num_images * NUM_CHANNELS ) data = numpy . frombuffer ( buf , dtype = numpy . uint8 ) . astype ( numpy . float32 ) data = ( data - ( PIXEL_DEPTH / 2.0 ) ) / PIXEL_DEPTH data = data . reshape ( num_images , IMAGE_SIZE , IMAGE_SIZE , NUM_CHANNELS ) return data