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[Excutor] Experiment Feature-Support Prefill in cudagraph (#3459)

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* Support prefill in Cudagraph

* Refactor GetBlockShapeAndSplitKVBlock Kernel V2

* Refactor GetBlockShapeAndSplitKVBlock Kernel V2.1

* Refactor GetBlockShapeAndSplitKVBlock Kernel V2.2

* Refactor GetBlockShapeAndSplitKVBlock Kernel V2.3

* Refactor GetBlockShapeAndSplitKVBlock Kernel V2.4

* Refactor GetBlockShapeAndSplitKVBlock Kernel V2.5

* Solve problem about encoder_num_blocks_x_cpu

* Add early-exit mechanism for attention kernel

* fix test case about append-attention

* Update testcode, Add annotations to related tensors

* move get_input_length_list

* solve test_code

* Add annotations about early-exit for attention kernel

* Add annotations about early-exit for attention kernel2

* solve comment

* solve mtp

---------

Co-authored-by: RAM <gstian5555@outlook.com>
This commit is contained in:
Jundong Liu
2025-09-08 13:12:24 +08:00
committed by GitHub
parent 472402bf4e
commit 3d0aaa5923
21 changed files with 528 additions and 260 deletions
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38
tests/layers/test_append_attention_with_output.py
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@@ -382,6 +382,13 @@ class TestAppendGroupQueryAttnWithRope(unittest.TestCase):
self.decoder_tile_ids_per_batch = paddle.full([self.batch_size], 0, dtype="int32")
self.decoder_num_blocks_cpu = paddle.full([1], 0, dtype="int32").pin_memory()
self.max_len_tensor_cpu = paddle.full([8], 0, dtype="int32").cpu()
self.encoder_batch_ids = paddle.full([self.batch_size], 0, dtype="int32")
self.encoder_tile_ids_per_batch = paddle.full([self.batch_size], 0, dtype="int32")
self.encoder_num_blocks_x_cpu = paddle.full([1], 0, dtype="int32").cpu()
self.kv_batch_ids = paddle.full([self.batch_size], 0, dtype="int32")
self.kv_tile_ids_per_batch = paddle.full([self.batch_size], 0, dtype="int32")
self.kv_num_blocks_x_cpu = paddle.full([1], 0, dtype="int32").cpu()
self.max_len_kv_cpu = paddle.full([1], 0, dtype="int32").cpu()
self.cache_shape = (
self.max_block_num,
@@ -450,15 +457,7 @@ class TestAppendGroupQueryAttnWithRope(unittest.TestCase):
get_block_shape_and_split_kv_block,
)
(
encoder_batch_ids,
encoder_tile_ids_per_batch,
encoder_num_blocks,
kv_batch_ids,
kv_tile_ids_per_batch,
kv_num_blocks,
max_len_kv,
) = get_block_shape_and_split_kv_block(
get_block_shape_and_split_kv_block(
self.seq_lens_encoder,
self.seq_lens_decoder,
self.seq_lens_this_time,
@@ -466,6 +465,13 @@ class TestAppendGroupQueryAttnWithRope(unittest.TestCase):
self.decoder_tile_ids_per_batch,
self.decoder_num_blocks_cpu,
self.max_len_tensor_cpu,
self.encoder_batch_ids,
self.encoder_tile_ids_per_batch,
self.encoder_num_blocks_x_cpu,
self.kv_batch_ids,
self.kv_tile_ids_per_batch,
self.kv_num_blocks_x_cpu,
self.max_len_kv_cpu,
64,
12,
(self.q_num_head + 2 * self.kv_num_head) // self.kv_num_head,
@@ -491,17 +497,17 @@ class TestAppendGroupQueryAttnWithRope(unittest.TestCase):
self.padding_offset,
self.cum_offset,
self.block_tables,
encoder_batch_ids,
encoder_tile_ids_per_batch,
encoder_num_blocks,
kv_batch_ids,
kv_tile_ids_per_batch,
kv_num_blocks,
self.encoder_batch_ids,
self.encoder_tile_ids_per_batch,
self.encoder_num_blocks_x_cpu,
self.kv_batch_ids,
self.kv_tile_ids_per_batch,
self.kv_num_blocks_x_cpu,
self.decoder_batch_ids,
self.decoder_tile_ids_per_batch,
self.decoder_num_blocks_cpu,
self.max_len_tensor_cpu,
max_len_kv,
self.max_len_kv_cpu,
out,
self.rope_emb, # rope_emb
None, # attn_mask