code: def randint(shape, minval, maxval, dtype="int32", seed=None):
      intemediate_dtype = dtype
      if standardize_dtype(dtype) not in ["int32", "int64"]:
          intemediate_dtype = "int64"
      seed = tf_draw_seed(seed)
      output = tf.random.stateless_uniform(
          shape=shape,
          minval=minval,
          maxval=maxval,
          dtype=intemediate_dtype,
          seed=seed,
      )
      return tf.cast(output, dtype)
  
file_path: keras/keras/backend/tensorflow/random.py
imports: import tensorflow
  from tensorflow.experimental import numpy
  from keras.backend.common import standardize_dtype
  from keras.backend.config import floatx
  from keras.random.seed_generator import SeedGenerator
  from keras.random.seed_generator import draw_seed
  from keras.random.seed_generator import make_default_seed
label_desc: Use image node_id 5 for calling a global function with example usage: randint(shape, minval, maxval, dtype, seed) and returns: tf