(pfor_input)
| 2164 | # is met. |
| 2165 | @RegisterPFor("BatchMatMul") |
| 2166 | def _convert_batch_mat_mul(pfor_input): |
| 2167 | # TODO(agarwal): There may be a more efficient way to do this instead of |
| 2168 | # stacking the inputs. |
| 2169 | pfor_input.stack_inputs() |
| 2170 | x = pfor_input.stacked_input(0) |
| 2171 | y = pfor_input.stacked_input(1) |
| 2172 | adj_x = pfor_input.get_attr("adj_x") |
| 2173 | adj_y = pfor_input.get_attr("adj_y") |
| 2174 | |
| 2175 | x = _flatten_first_two_dims(x) |
| 2176 | y = _flatten_first_two_dims(y) |
| 2177 | output = math_ops.matmul(x, y, adjoint_a=adj_x, adjoint_b=adj_y) |
| 2178 | output = _unflatten_first_dim(output, pfor_input.pfor.loop_len_vector) |
| 2179 | return wrap(output, True) |
| 2180 | |
| 2181 | |
| 2182 | @RegisterPFor("BatchMatMulV2") |
nothing calls this directly
no test coverage detected