// make it to the return array.
      auto segment_sizes = getOperation()->getAttrOfType<DenseI32ArrayAttr>(getOperandSegmentSizeAttr());
      return OperandRangeRange(getOperands(), segment_sizes).join();
    }
  }];
}

def TF_BatchMatMulOp : TF_Op<"BatchMatMul", [Pure, TF_SameOperandsAndResultElementTypeResolveRef]> {
  let summary = "Multiplies slices of two tensors in batches.";

				strings.Join(missing.List(), "\n"))
		}
		if len(unexpected) > 0 {
			t.Errorf("the following fields were in the result, but unexpected. "+
				"If the field is new, please add it to the osNeutralFields set "+
				"or add it to the osSpecificFields set, as appropriate:\n%s",
				strings.Join(unexpected.List(), "\n"))
		}
	}
}

        `tf.quantization.fake_quant_with_min_max_vars_per_channel`,
        `tf.quantization.fake_quant_with_min_max_vars_per_channel_gradient`.
    *   New endpoints in tf.strings namespace: `tf.strings.join` (corresponds to
        `tf.string_join`), `tf.strings.regex_replace`, `tf.strings.to_number`
        (corresponds to `tf.string_to_number`), `tf.strings.strip` (corresponds