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pingpong optimization issue fix

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Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
This commit is contained in:
Wang, Yi A 2025-04-15 21:56:51 -07:00
parent 5ec7f15d0c
commit bf3987e25e
2 changed files with 17 additions and 9 deletions
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22
backends/gaudi/server/text_generation_server/models/flash_causal_lm.py
View File

@ -615,6 +615,12 @@ class FlashCausalLMBatch(Batch):
max_slots = max(max_slots, slot_length) max_slots = max(max_slots, slot_length)
all_input_ids_tensor = self.all_input_ids_tensor[indices] all_input_ids_tensor = self.all_input_ids_tensor[indices]
next_token_logits = self.next_token_logits[indices]
speculative_logits = (
self.speculative_logits[indices]
if self.speculative_logits is not None
else None
)
block_tables_tensor = self.block_tables_tensor[indices] block_tables_tensor = self.block_tables_tensor[indices]
next_token_chooser = self.next_token_chooser.filter(indices) next_token_chooser = self.next_token_chooser.filter(indices)
top_n_tokens_tensor = self.top_n_tokens_tensor[indices] top_n_tokens_tensor = self.top_n_tokens_tensor[indices]
@ -696,8 +702,8 @@ class FlashCausalLMBatch(Batch):
speculative_ids=speculative_ids, speculative_ids=speculative_ids,
adapter_meta=adapter_meta, adapter_meta=adapter_meta,
hpu_attn_meta=None, hpu_attn_meta=None,
next_token_logits=None, next_token_logits=next_token_logits,
speculative_logits=None, speculative_logits=speculative_logits,
) )
@classmethod @classmethod
@ -825,8 +831,11 @@ class FlashCausalLMBatch(Batch):
start_index = cumulative_batch_size start_index = cumulative_batch_size
end_index = cumulative_batch_size + len(batch) end_index = cumulative_batch_size + len(batch)
# Copy tensors (GPU) # Copy tensors (HPU)
top_n_tokens_tensor[start_index:end_index] = batch.top_n_tokens_tensor index = torch.tensor(
list(range(start_index, end_index)), device=batch.input_ids.device
)
top_n_tokens_tensor.index_copy_(0, index, batch.top_n_tokens_tensor)
all_input_ids_tensor[ all_input_ids_tensor[
start_index:end_index, : batch.all_input_ids_tensor.shape[1] start_index:end_index, : batch.all_input_ids_tensor.shape[1]
] = batch.all_input_ids_tensor[:, :max_length] ] = batch.all_input_ids_tensor[:, :max_length]
@ -834,7 +843,7 @@ class FlashCausalLMBatch(Batch):
block_tables_tensor[ block_tables_tensor[
start_index:end_index, : batch.block_tables_tensor.shape[1] start_index:end_index, : batch.block_tables_tensor.shape[1]
] = batch.block_tables_tensor[:, :max_blocks] ] = batch.block_tables_tensor[:, :max_blocks]
prompt_lengths_tensor[start_index:end_index] = batch.prompt_lengths_tensor prompt_lengths_tensor.index_copy_(0, index, batch.prompt_lengths_tensor)
slots_start_index = cumulative_slots slots_start_index = cumulative_slots
slots_end_index = cumulative_slots + len(batch.slots) slots_end_index = cumulative_slots + len(batch.slots)
@ -844,9 +853,6 @@ class FlashCausalLMBatch(Batch):
) )
if not prefilling: if not prefilling:
index = torch.tensor(
list(range(start_index, end_index)), device=batch.input_ids.device
)
input_ids.index_copy_(0, index, batch.input_ids) input_ids.index_copy_(0, index, batch.input_ids)
position_ids.index_copy_(0, index, batch.position_ids) position_ids.index_copy_(0, index, batch.position_ids)
slot_indices.index_copy_( slot_indices.index_copy_(

4
backends/v3/src/block_allocator.rs
View File

@ -177,7 +177,7 @@ impl Allocator for SimpleAllocator {
(required_blocks, repeats) (required_blocks, repeats)
}; };
let tokens = tokens as usize; let mut tokens = tokens as usize;
if required_blocks > self.free_blocks.len() as u32 { if required_blocks > self.free_blocks.len() as u32 {
None None
} else { } else {
@ -189,6 +189,8 @@ impl Allocator for SimpleAllocator {
.split_off(self.free_blocks.len() - required_blocks as usize); .split_off(self.free_blocks.len() - required_blocks as usize);
if self.is_hpu_device { if self.is_hpu_device {
blocks.sort(); blocks.sort();
// need 1 slot for ping-pong optimization
tokens += 1;
} }
let mut slots = let mut slots =
Vec::with_capacity((required_blocks * self.block_size * repeats as u32) as usize); Vec::with_capacity((required_blocks * self.block_size * repeats as u32) as usize);