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[pipeline] hotfix backward for multiple outputs #6090

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Merged
ver217 merged 2 commits into from
Oct 16, 2024
Merged

[pipeline] hotfix backward for multiple outputs #6090

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4382fc5
[pipeline] hotfix backward for multiple outputs
ver217 Oct 15, 2024
e52ac38
[pipeline] hotfix backward for multiple outputs
ver217 Oct 16, 2024
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17 changes: 9 additions & 8 deletions colossalai/pipeline/schedule/interleaved_pp.py
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Original file line number Diff line number Diff line change
Expand Up @@ -351,15 +351,16 @@ def backward_step(
if output_obj_grad is None:
optimizer.backward(output_obj)
else:
if "backward_tensor_keys" not in output_obj:
for k, grad in output_obj_grad.items():
optimizer.backward_by_grad(output_obj[k], grad)
keys = output_obj.get("backward_tensor_keys", output_obj_grad.keys())
tensors_to_backward = []
grads_to_backward = []
for k in keys:
tensors_to_backward.append(output_obj[k])
grads_to_backward.append(output_obj_grad[k])
if len(tensors_to_backward) == 1:
optimizer.backward_by_grad(tensors_to_backward[0], grads_to_backward[0])
else:
for k, grad in output_obj_grad.items():
output_obj[k].grad = grad
for k in output_obj["backward_tensor_keys"]:
tensor_to_backward = output_obj[k]
optimizer.backward_by_grad(tensor_to_backward, tensor_to_backward.grad)
optimizer.backward_by_grad(tensors_to_backward, grads_to_backward)

# Collect the grad of the input_obj.
input_obj_grad = None
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17 changes: 9 additions & 8 deletions colossalai/pipeline/schedule/one_f_one_b.py
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Original file line number Diff line number Diff line change
Expand Up @@ -305,15 +305,16 @@ def backward_step(
if output_obj_grad is None:
optimizer.backward(output_obj)
else:
if "backward_tensor_keys" not in output_obj:
for k, grad in output_obj_grad.items():
optimizer.backward_by_grad(output_obj[k], grad)
keys = output_obj.get("backward_tensor_keys", output_obj_grad.keys())
tensors_to_backward = []
grads_to_backward = []
for k in keys:
tensors_to_backward.append(output_obj[k])
grads_to_backward.append(output_obj_grad[k])
if len(tensors_to_backward) == 1:
optimizer.backward_by_grad(tensors_to_backward[0], grads_to_backward[0])
else:
for k, grad in output_obj_grad.items():
output_obj[k].grad = grad
for k in output_obj["backward_tensor_keys"]:
tensor_to_backward = output_obj[k]
optimizer.backward_by_grad(tensor_to_backward, tensor_to_backward.grad)
optimizer.backward_by_grad(tensors_to_backward, grads_to_backward)

# Collect the grad of the input_obj.
input_obj_grad = None
Expand Down