During chunked prefill, seqlen_k was set to len(seq) (the full sequence
length), causing the attention kernel to access uninitialized KV slots
for tokens not yet scheduled in the current chunk.
Fix: reorder so that end = start + seqlen_q is computed first, then
set seqlen_k = end — limiting attention to the current chunk boundary.
Fixes#212
When RowParallelLinear has bias=True, the weight_loader crashes with an
IndexError because it calls param_data.size(tp_dim) where tp_dim=1, but
the bias tensor is 1D and only has dimension 0.
The bias in RowParallelLinear is not sharded (all ranks hold the full
bias, only rank 0 applies it), so skip the sharding logic for 1D params.
FixesGeeeekExplorer/nano-vllm#125
Tai An