code: def beta(shape, alpha, beta, dtype=None, seed=None):
      dtype = dtype or floatx()
      seed = draw_seed(seed)
      rng = np.random.default_rng(seed)
      sample = rng.beta(a=alpha, b=beta, size=shape).astype(dtype)
      return sample
  
file_path: keras/keras/backend/numpy/random.py
imports: import numpy
  from keras.backend.config import floatx
  from keras.backend.numpy.nn import softmax
  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 10 for calling a global function with example usage: beta(shape, alpha, beta, dtype, seed) and returns: sample