message: Improve batch_group_count documentation in XLA operation semantics
diff: @@ -636,11 +636,15 @@ details, see `tf.nn.depthwise_conv2d`.
  The `batch_group_count` (default value 1) argument can be used for depthwise
  filters during backpropagation. `batch_group_count` needs to be a divisor of the
  -size of the `lhs` batch dimension. If `batch_group_count` is greater than 1, it
  -means that conceptually the output batch dimension is split evenely in
  -`batch_group_count` groups, such that each group consists of a consecutive
  -subsequence of batches. Each output batch element is the reduced value of the
  -batch group size.
  +size of the `lhs` (input) batch dimension. If `batch_group_count` is greater
  +than 1, it means that the output batch dimension should be of size
  +`batch_group_size` where `batch_group_size = input batch / batch_group_count`.
  +For convolutions with `batch_group_count` greater than 1, the input batch size
  +must evenly divide into batch_group_size and output feature size, which implies
  +that the output feature size must be equal to batch_group_count. Conceptually,
  +this can be achieved by performing the usual convolution, and then scraping
  +`batch_group_size` number of elements on the diagonal of the matrix formed by
  +output batch and output feature.
  The output shape has these dimensions, in this order:
  