docstr: 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
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code: def kaiming(self, shape, dtype):
      """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.random.truncated_normal(shape, dtype=dtype) * tf.sqrt(
          2 / float(shape[0])
      )
  
imports: import numpy
  import tensorflow
  from tensorlayer.layers import Layer, Dropout, Dense, Input, BatchNorm, Reshape, Elementwise
  from tensorlayer.models import Model
  from tensorlayer import logging
  from .common import mask_weight, neighbour_matrix
label_desc: Use image node_id 4 for calling the Base_layer obj's underlying member method code with example usage: obj.kaiming(shape, dtype) and returns: unknown