parameters: (shape, dtype, partition_info=None)
return_statement: return(tf.truncated_normal(shape, dtype=dtype)*tf.sqrt(2/float(shape[0])))
docstring: Kaiming initialization as described in https://arxiv.org/pdf/1502.01852.pdf
  
    Args
      shape: dimensions of the tf array to initialize
      dtype: data type of the array
      partition_info: (Optional) info about how the variable is partitioned.
        See https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/ops/init_ops.py#L26
        Needed to be used as an initializer.
    Returns
      Tensorflow array with initial weights
docstring_summary: Kaiming initialization as described in https://arxiv.org/pdf/1502.01852.pdf
docstring_tokens: Kaiming initialization as described in https : // arxiv . org / pdf / 1502 . 01852 . pdf
function: def kaiming(shape, dtype, partition_info=None):
    """Kaiming initialization as described in https://arxiv.org/pdf/1502.01852.pdf
  
    Args
      shape: dimensions of the tf array to initialize
      dtype: data type of the array
      partition_info: (Optional) info about how the variable is partitioned.
        See https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/ops/init_ops.py#L26
        Needed to be used as an initializer.
    Returns
      Tensorflow array with initial weights
    """
    return(tf.truncated_normal(shape, dtype=dtype)*tf.sqrt(2/float(shape[0])))
function_tokens: def kaiming ( shape , dtype , partition_info = None ) : return ( tf . truncated_normal ( shape , dtype = dtype ) * tf . sqrt ( 2 / float ( shape [ 0 ] ) ) )