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Fix wrong inputs/model placement when using a single core #725

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Nov 15, 2024
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Fix wrong inputs/model placement when using a single core #725

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9 changes: 7 additions & 2 deletions optimum/neuron/modeling_traced.py
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Original file line number Diff line number Diff line change
Expand Up @@ -53,6 +53,7 @@
NEURON_COMPILER_VERSION = get_neuroncc_version()

if is_neuronx_available():
import torch_neuronx
from torch_neuronx import move_trace_to_device

NEURON_COMPILER_TYPE = "neuronx-cc"
Expand Down Expand Up @@ -127,8 +128,12 @@ def load_model(
if path.is_file():
model = torch.jit.load(path)
# For non-inlined models, send the module manually to device. This is important for weights/neff non-inlined module since when loading the module, the neff is automatically moved to Neuron but not the weights. We need to move the weights to Neuron as well manually to avoid great host to device IO penalty.
if is_neuronx_available() and to_neuron:
move_trace_to_device(model, device_id)
if is_neuronx_available():
torch_neuronx.experimental.set_neuron_cores(
model, start_nc=0, nc_count=1
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What happens if the model has tp_degree > 1 ?

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There is no tp support right now for SD models, only one neuron device is supported, and we want both cores to be used, we apply ddp with the entire model loaded on both cores.

) # The inputs are allocated to nc:0 by default, this line ensures both input tensors and the model are on the same core.
if to_neuron:
move_trace_to_device(model, device_id)
return model

def replace_weights(self, weights: Optional[Union[Dict[str, torch.Tensor], torch.nn.Module]] = None):
Expand Down
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