class_docstr: Initializer which concats other intializers.
class_docstr_tok: ["Initializer","which","concats","other","intializers","."]
docstr: Creates the `BlockwiseInitializer`.
  
  Args:
    initializers: `list` of Keras initializers, e.g., `"glorot_uniform"` or
      `tf_keras.initializers.Constant(0.5413)`.
    sizes: `list` of `int` scalars representing the number of elements
      associated with each initializer in `initializers`.
    validate_args: Python `bool` indicating we should do (possibly expensive)
      graph-time assertions, if necessary.
docstr_tok: ["Creates","the","`","BlockwiseInitializer","`",".","Args",":","initializers",":","`","list","`","of","Keras","initializers",",","e.g.",",","`","``","glorot_uniform","''","`","or","`","tf_keras.initializers.Constant","(","0.5413",")","`",".","sizes",":","`","list","`","of","`","int","`","scalars","representing","the","number","of","elements","associated","with","each","initializer","in","`","initializers","`",".","validate_args",":","Python","`","bool","`","indicating","we","should","do","(","possibly","expensive",")","graph-time","assertions",",","if","necessary","."]
code: def __init__(self, initializers, sizes, validate_args=False):
      """Creates the `BlockwiseInitializer`.
  
      Args:
        initializers: `list` of Keras initializers, e.g., `"glorot_uniform"` or
          `tf_keras.initializers.Constant(0.5413)`.
        sizes: `list` of `int` scalars representing the number of elements
          associated with each initializer in `initializers`.
        validate_args: Python `bool` indicating we should do (possibly expensive)
          graph-time assertions, if necessary.
      """
      self._initializers = initializers
      self._sizes = sizes
      self._validate_args = validate_args
  
file_path: probability/tensorflow_probability/python/layers/initializers.py
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import tf_keras
label_desc: Use image node_id 1 to create a new BlockwiseInitializer object from inherited base classes: tf_keras.initializers with example: obj = BlockwiseInitializer(initializers, sizes, validate_args)