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[NPUW] Fix LLMInferRequest to work with the input prompt of len 1 #32267

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Merged
merged 2 commits into from
Oct 10, 2025
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[NPUW] Fix LLMInferRequest to work with the input prompt of len 1 #32267

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97563ee
Fix LLMInferRequest to work with the input prompt of len 1
AsyaPronina Oct 1, 2025
74744ef
Fixed review comments
AsyaPronina Oct 9, 2025
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7 changes: 5 additions & 2 deletions src/plugins/intel_npu/src/plugin/npuw/llm_compiled_model.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -629,13 +629,16 @@ void slice_out_embeds(std::shared_ptr<ov::Model> model,

if (embed_result) {
auto shape = embed_result->input(0).get_shape();
// If shape.size() is 3, then last axis should be the Vocab size.
// If shape.size() is 3, then last axis should contain the rank of embedding dimension.
// But 1st and 2nd axes can mean different things.
// 1st axis can represent the batch size, while 2nd - the number of embeddings,
// or vice-versa (in chatglm)
if (shape.size() == 3) {
OPENVINO_ASSERT(batch_dim <= 1, "Unexpected value of batch_dim: ", batch_dim, ", expected 0 or 1!");
uint32_t num_embeds_dim = 1 - batch_dim;
if (shape[num_embeds_dim] > max_generation_token_len) {
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somehow I overlooked it in the past but what is batch_dim? can this 1 - x underflow to some hugely positive value here?

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No, because batch dim is either 0 or 1 (for chat-glm), but great catch!! Let me add assert!

OPENVINO_ASSERT(shape[num_embeds_dim] >= max_generation_token_len,
"Number of output embeddings should be greater or equal to the slicing range!");
if (shape[num_embeds_dim] != max_generation_token_len) {
std::vector<int32_t> start_pos{
static_cast<int32_t>(batch_dim * (shape[num_embeds_dim] - max_generation_token_len)),
static_cast<int32_t>(num_embeds_dim * (shape[num_embeds_dim] - max_generation_token_len)),
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4 changes: 3 additions & 1 deletion src/plugins/intel_npu/src/plugin/npuw/llm_infer_request.cpp
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Expand Up @@ -858,7 +858,9 @@ void ov::npuw::LLMInferRequest::infer_generate(ov::SoPtr<ov::ITensor> input_ids,

if (!m_generate_initialized) {
LOG_DEBUG("Copy kv-cache from prefill to generate model.");
copy_kvcache();
if (kvcache_desc.num_stored_tokens > 0) {
copy_kvcache();
}

LOG_DEBUG("Prepare inputs.");
namespace uu = ov::npuw::util;
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