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wip: implement grad wrt logits

justheuristic %!s(int64=5) %!d(string=hai) anos
pai
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c005da2089
Modificáronse 1 ficheiros con 1 adicións e 1 borrados
  1. 1 1
      tesseract/client/moe.py

+ 1 - 1
tesseract/client/moe.py

@@ -201,7 +201,7 @@ class _RemoteMoECall(torch.autograd.Function):
         stacked_alive_outputs = tuple(map(torch.stack, alive_outputs))
         flat_average_outputs = tuple(dot_along_first_axis(alive_expert_probs, stacked_out)
                                      for stacked_out in stacked_alive_outputs)
-        print(flat_average_outputs)
+        print('!!!!', flat_average_outputs, flush=True)
 
         # 3. save individual outputs for backward pass
         ctx.save_for_backward(expert_logits, alive_ix, alive_expert_probs, *stacked_alive_outputs)