(output, labels)
| 114 | |
| 115 | |
| 116 | def CrossEntropy(output, labels): |
| 117 | labels, loss_mask = labels[0], labels[1] |
| 118 | |
| 119 | args = get_args() |
| 120 | |
| 121 | losses = mpu.vocab_parallel_cross_entropy(output.contiguous().float(), labels) |
| 122 | loss_mask = loss_mask.view(-1) |
| 123 | loss = torch.sum(losses.view(-1) * loss_mask) / loss_mask.sum() |
| 124 | return loss |
| 125 | |
| 126 | |
| 127 | class CodeGeeXModelPipe(PipelineModule, MegatronModule): |
nothing calls this directly
no test coverage detected