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Create the arange tensor on device for enabling CUDA-Graph for Clip Encoder #19503

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Merged
LysandreJik merged 2 commits into from
Oct 12, 2022
Merged

Create the arange tensor on device for enabling CUDA-Graph for Clip Encoder #19503

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create the arange tensor on device for enabling CUDA-Graph at higher-…
Oct 10, 2022
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stas00 Oct 12, 2022
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2 changes: 1 addition & 1 deletion src/transformers/models/clip/modeling_clip.py
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Original file line number Diff line number Diff line change
Expand Up @@ -662,7 +662,7 @@ def forward(
# take features from the eot embedding (eot_token is the highest number in each sequence)
# casting to torch.int for onnx compatibility: argmax doesn't support int64 inputs with opset 14
pooled_output = last_hidden_state[
torch.arange(last_hidden_state.shape[0]), input_ids.to(torch.int).argmax(dim=-1)
torch.arange(last_hidden_state.shape[0], device=input_ids.device), input_ids.to(torch.int).argmax(dim=-1)
]

if not return_dict:
Expand Down
2 changes: 1 addition & 1 deletion src/transformers/models/groupvit/modeling_groupvit.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1134,7 +1134,7 @@ def forward(
# take features from the eot embedding (eot_token is the highest number in each sequence)
# casting to torch.int for onnx compatibility: argmax doesn't support int64 inputs with opset 14
pooled_output = last_hidden_state[
torch.arange(last_hidden_state.shape[0]), input_ids.to(torch.int).argmax(dim=-1)
torch.arange(last_hidden_state.shape[0], device=input_ids.device), input_ids.to(torch.int).argmax(dim=-1)
]

if not return_dict:
Expand Down