Skip to content

[https://nvbugs/5449155][fix] Fix DeepSeek R1 weight loading for TP16 #6913

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
litaotju merged 1 commit into from
Aug 19, 2025
Merged

[https://nvbugs/5449155][fix] Fix DeepSeek R1 weight loading for TP16 #6913

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
40 changes: 30 additions & 10 deletions tensorrt_llm/_torch/modules/linear.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -604,9 +604,12 @@ def load_weights_vanilla(self, module: Linear, weights: List[Dict]) -> None:
load_weights_vanilla_helper(module, weights)

scale_name = self._get_scale_name(weights)
weight_scale = load_weight_shard(weights[0][scale_name], module.tp_size,
module.tp_rank,
module.tp_mode).squeeze()
full_weight_scale = weights[0][scale_name]
# modelopt fp8_pb_wo can have 2 extra singleton dimensions
if full_weight_scale.dim() == 4:
full_weight_scale = full_weight_scale.squeeze(1).squeeze(-1)
weight_scale = load_weight_shard(full_weight_scale, module.tp_size,
module.tp_rank, module.tp_mode)
copy_weight(module.weight_scale, weight_scale)
if "input_scale" in weights[0]:
copy_weight(module.input_scale, weights[0]["input_scale"])
Expand All @@ -619,13 +622,23 @@ def load_weights_fused_qkv_linear(self, module: Linear,
fused_weight = torch.cat((q_weight, k_weight, v_weight))

scale_name = self._get_scale_name(weights)
q_scale = load_weight_shard(weights[0][scale_name], module.tp_size,
full_q_scale = weights[0][scale_name]
full_k_scale = weights[1][scale_name]
full_v_scale = weights[2][scale_name]
# modelopt fp8_pb_wo can have 2 extra singleton dimensions
if full_q_scale.dim() == 4:
full_q_scale = full_q_scale.squeeze(1).squeeze(-1)
if full_k_scale.dim() == 4:
full_k_scale = full_k_scale.squeeze(1).squeeze(-1)
if full_v_scale.dim() == 4:
full_v_scale = full_v_scale.squeeze(1).squeeze(-1)
q_scale = load_weight_shard(full_q_scale, module.tp_size,
module.tp_rank, module.tp_mode)
k_scale = load_weight_shard(weights[1][scale_name], module.tp_size,
k_scale = load_weight_shard(full_k_scale, module.tp_size,
module.tp_rank, module.tp_mode)
v_scale = load_weight_shard(weights[2][scale_name], module.tp_size,
v_scale = load_weight_shard(full_v_scale, module.tp_size,
module.tp_rank, module.tp_mode)
fused_fp8_block_scale = torch.cat((q_scale, k_scale, v_scale)).squeeze()
fused_fp8_block_scale = torch.cat((q_scale, k_scale, v_scale))

copy_weight(module.weight, fused_weight)
copy_weight(module.weight_scale, fused_fp8_block_scale)
Expand All @@ -637,11 +650,18 @@ def load_weights_fused_gate_up_linear(self, module: Linear,
fused_weight = torch.cat((gate_weight, up_weight))

scale_name = self._get_scale_name(weights)
left_scale = load_weight_shard(weights[0][scale_name], module.tp_size,
full_left_scale = weights[0][scale_name]
full_right_scale = weights[1][scale_name]
# modelopt fp8_pb_wo can have 2 extra singleton dimensions
if full_left_scale.dim() == 4:
full_left_scale = full_left_scale.squeeze(1).squeeze(-1)
if full_right_scale.dim() == 4:
full_right_scale = full_right_scale.squeeze(1).squeeze(-1)
left_scale = load_weight_shard(full_left_scale, module.tp_size,
module.tp_rank, module.tp_mode)
right_scale = load_weight_shard(weights[1][scale_name], module.tp_size,
right_scale = load_weight_shard(full_right_scale, module.tp_size,
module.tp_rank, module.tp_mode)
fused_scale = torch.cat([left_scale, right_scale], dim=0).squeeze()
fused_scale = torch.cat([left_scale, right_scale], dim=0)
copy_weight(module.weight, fused_weight)
copy_weight(module.weight_scale, fused_scale)

Expand Down