code: def _convolution_batch_nbhwc(
      x, kernel, rank, strides, padding, dilations, name
  ):
      """Specialization of batch conv to NBHWC data format."""
      result = _convolution_batch_nhwbc(
          tf.transpose(x, [0, 2, 3, 1, 4]),
          kernel,
          rank,
          strides,
          padding,
          dilations,
          name,
      )
      return tf.transpose(result, [0, 3, 1, 2, 4])
  
imports: import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import distribution
  from tensorflow_probability.python.experimental.nn import layers
  from tensorflow_probability.python.experimental.nn import variational_base
  from tensorflow_probability.python.experimental.nn.util import convolution_util
  from tensorflow_probability.python.experimental.nn.util import kernel_bias
  from tensorflow_probability.python.experimental.nn.util import utils
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import prefer_static
label_desc: Use image node_id 3 for calling a global function with example usage: _convolution_batch_nbhwc(x, kernel, rank, strides, padding, dilations, name) and returns: tf