[NPU] Fix NPU CI (#13834)
Co-authored-by: c30031083 <chenxu140@huawei.com>
This commit is contained in:
@@ -112,9 +112,9 @@ class AscendPagedTokenToKVPoolAllocator(PagedTokenToKVPoolAllocator):
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device=self.device,
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device=self.device,
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)
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)
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torch.ops.npu.alloc_extend(
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torch.ops.npu.alloc_extend(
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prefix_lens,
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prefix_lens.to(torch.int64),
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seq_lens,
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seq_lens.to(torch.int64),
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last_loc,
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last_loc.to(torch.int64),
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self.free_pages,
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self.free_pages,
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self.page_size,
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self.page_size,
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out_indices,
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out_indices,
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@@ -329,6 +329,7 @@ class CudaGraphRunner:
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seq_len_fill_value=self.seq_len_fill_value,
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seq_len_fill_value=self.seq_len_fill_value,
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encoder_len_fill_value=self.encoder_len_fill_value,
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encoder_len_fill_value=self.encoder_len_fill_value,
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num_tokens_per_bs=self.num_tokens_per_bs,
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num_tokens_per_bs=self.num_tokens_per_bs,
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cache_loc_dtype=self._cache_loc_dtype(),
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)
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)
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self.tbo_plugin = TboCudaGraphRunnerPlugin()
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self.tbo_plugin = TboCudaGraphRunnerPlugin()
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@@ -43,13 +43,14 @@ class GraphInputBuffers:
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seq_len_fill_value: int,
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seq_len_fill_value: int,
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encoder_len_fill_value: int,
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encoder_len_fill_value: int,
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num_tokens_per_bs: int,
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num_tokens_per_bs: int,
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cache_loc_dtype: torch.dtype,
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) -> "GraphInputBuffers":
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) -> "GraphInputBuffers":
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with torch.device(device):
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with torch.device(device):
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input_ids = torch.zeros((max_num_token,), dtype=torch.int64)
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input_ids = torch.zeros((max_num_token,), dtype=torch.int64)
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input_embeds = torch.zeros((max_num_token, hidden_size), dtype=dtype)
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input_embeds = torch.zeros((max_num_token, hidden_size), dtype=dtype)
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req_pool_indices = torch.zeros((max_bs,), dtype=torch.int32)
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req_pool_indices = torch.zeros((max_bs,), dtype=torch.int32)
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seq_lens = torch.full((max_bs,), seq_len_fill_value, dtype=torch.int32)
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seq_lens = torch.full((max_bs,), seq_len_fill_value, dtype=torch.int32)
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out_cache_loc = torch.zeros((max_num_token,), dtype=torch.int64)
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out_cache_loc = torch.zeros((max_num_token,), dtype=cache_loc_dtype)
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positions = torch.zeros((max_num_token,), dtype=torch.int64)
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positions = torch.zeros((max_num_token,), dtype=torch.int64)
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mrope_positions = torch.zeros((3, max_num_token), dtype=torch.int64)
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mrope_positions = torch.zeros((3, max_num_token), dtype=torch.int64)
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num_token_non_padded = torch.zeros((1,), dtype=torch.int32)
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num_token_non_padded = torch.zeros((1,), dtype=torch.int32)
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@@ -107,8 +107,8 @@ class NPUGraphRunner(CudaGraphRunner):
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self.replay_prepare(forward_batch, pp_proxy_tensors)
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self.replay_prepare(forward_batch, pp_proxy_tensors)
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else:
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else:
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# In speculative decoding, these two fields are still needed.
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# In speculative decoding, these two fields are still needed.
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self.input_ids[: self.raw_num_token].copy_(forward_batch.input_ids)
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self.buffers.input_ids[: self.raw_num_token].copy_(forward_batch.input_ids)
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self.positions[: self.raw_num_token].copy_(forward_batch.positions)
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self.buffers.positions[: self.raw_num_token].copy_(forward_batch.positions)
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# Replay
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# Replay
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if not is_deepseek_nsa(self.model_runner.model_config.hf_config):
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if not is_deepseek_nsa(self.model_runner.model_config.hf_config):
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@@ -133,8 +133,8 @@ def assign_req_to_token_pool_func(
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torch.ops.npu.cache_loc_assign(
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torch.ops.npu.cache_loc_assign(
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req_pool_indices,
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req_pool_indices,
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req_to_token,
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req_to_token,
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start_offset,
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start_offset.to(torch.int64),
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end_offset,
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end_offset.to(torch.int64),
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out_cache_loc,
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out_cache_loc,
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)
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)
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@@ -8,9 +8,7 @@ from sglang.test.test_utils import (
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DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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DEFAULT_URL_FOR_TEST,
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DEFAULT_URL_FOR_TEST,
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CustomTestCase,
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CustomTestCase,
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is_in_ci,
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popen_launch_server,
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popen_launch_server,
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run_bench_offline_throughput,
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)
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)
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TEST_MODEL_MATRIX = {
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TEST_MODEL_MATRIX = {
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@@ -71,26 +69,6 @@ class TestAscendTp1Bf16(CustomTestCase):
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finally:
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finally:
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kill_process_tree(process.pid)
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kill_process_tree(process.pid)
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def test_b_throughput(self):
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for model in self.models:
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with self.subTest(model=model):
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print(f"##=== Testing throughput: {model} ===##")
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output_throughput = run_bench_offline_throughput(
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model,
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[
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*self.common_args,
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],
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)
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print(f"##=== {model} throughput: {output_throughput} ===##")
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if is_in_ci():
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self.assertGreater(
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output_throughput,
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TEST_MODEL_MATRIX[model]["output_throughput"],
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)
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if __name__ == "__main__":
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if __name__ == "__main__":
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unittest.main()
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unittest.main()
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@@ -366,7 +366,7 @@ suite_ascend = {
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],
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],
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"per-commit-16-npu-a3": [
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"per-commit-16-npu-a3": [
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TestFile("ascend/test_ascend_deepep.py", 400),
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TestFile("ascend/test_ascend_deepep.py", 400),
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TestFile("ascend/test_ascend_deepseek_mtp.py", 400),
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# TestFile("ascend/test_ascend_deepseek_mtp.py", 400),
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],
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],
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}
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}
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