(ctx, run_function, length, *args)
| 358 | class CheckpointFunction(torch.autograd.Function): |
| 359 | @staticmethod |
| 360 | def forward(ctx, run_function, length, *args): |
| 361 | ctx.run_function = run_function |
| 362 | ctx.input_tensors = list(args[:length]) |
| 363 | ctx.input_params = list(args[length:]) |
| 364 | ctx.gpu_autocast_kwargs = {"enabled": torch.is_autocast_enabled(), |
| 365 | "dtype": torch.get_autocast_gpu_dtype(), |
| 366 | "cache_enabled": torch.is_autocast_cache_enabled()} |
| 367 | with torch.no_grad(): |
| 368 | output_tensors = ctx.run_function(*ctx.input_tensors) |
| 369 | return output_tensors |
| 370 | |
| 371 | @staticmethod |
| 372 | def backward(ctx, *output_grads): |
nothing calls this directly
no outgoing calls
no test coverage detected