code: def convolution_batch(
      x,
      kernel,
      rank,
      strides,
      padding,
      data_format=None,
      dilations=None,
      name=None,
  ):
      """Like `tf.nn.conv2d` except applies batch of kernels to batch of `x`."""
      if rank != 2:
          raise NotImplementedError(
              "Argument `rank` currently only supports `2`; "
              'saw "{}".'.format(rank)
          )
      if data_format is not None and data_format.upper() == "NHWBC":
          return _convolution_batch_nhwbc(
              x, kernel, rank, strides, padding, dilations, name
          )
      if data_format is not None and data_format.upper() == "NBHWC":
          return _convolution_batch_nbhwc(
              x, kernel, rank, strides, padding, dilations, name
          )
      raise ValueError(
          'Argument `data_format` currently only supports "NHWBC" and '
          '"NBHWC"; saw "{}".'.format(data_format)
      )
  
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 5 for calling a global function with example usage: convolution_batch(x, kernel, rank, strides, padding, data_format, dilations, name) and returns: _convolution_batch_nhwbc, _convolution_batch_nbhwc