[long_seq] remove long_seq env (#4660)
### What this PR does / why we need it? remove env VLLM_ASCEND_ENABLE_CONTEXT_PARALLEL - vLLM version: v0.12.0 --------- Signed-off-by: LookAround <lixushi@huawei.com> Signed-off-by: ZhangMingWei716 <2894054457@qq.com> Co-authored-by: ZhangMingWei716 <2894054457@qq.com> Co-authored-by: wangxiyuan <wangxiyuan1007@gmail.com>
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@@ -26,10 +26,13 @@ import torch.nn as nn
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import torch_npu
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from vllm.attention.backends.abstract import (AttentionBackend, AttentionImpl,
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AttentionLayer, AttentionType)
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from vllm.attention.backends.registry import (AttentionBackendEnum,
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register_backend)
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from vllm.config import VllmConfig
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from vllm.distributed import (get_dcp_group,
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get_decode_context_model_parallel_rank,
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get_decode_context_model_parallel_world_size)
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get_decode_context_model_parallel_world_size,
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get_pcp_group)
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from vllm.forward_context import ForwardContext, get_forward_context
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from vllm.utils.math_utils import cdiv
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from vllm.v1.attention.backends.utils import AttentionCGSupport
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@@ -41,19 +44,7 @@ from vllm_ascend.attention.utils import (AscendCommonAttentionMetadata,
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split_decodes_and_prefills)
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from vllm_ascend.compilation.acl_graph import (get_graph_params,
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update_graph_params_workspaces)
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from vllm_ascend.utils import prefill_context_parallel_enable, weak_ref_tensors
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# isort: off
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if prefill_context_parallel_enable():
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from vllm.distributed import (get_pcp_group,
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get_prefill_context_model_parallel_rank,
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get_prefill_context_model_parallel_world_size
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)
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# isort: on
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from vllm.attention.backends.registry import (AttentionBackendEnum,
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register_backend)
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from vllm_ascend.utils import weak_ref_tensors
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@register_backend(AttentionBackendEnum.CUSTOM, "ASCEND")
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@@ -255,10 +246,9 @@ class AscendAttentionMetadataBuilder:
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vllm_config.scheduler_config.max_num_batched_tokens,
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dtype=torch.uint8,
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device=device)
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self.pcp_size = get_prefill_context_model_parallel_world_size(
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) if prefill_context_parallel_enable() else 1
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self.pcp_rank = get_prefill_context_model_parallel_rank(
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) if self.pcp_size > 1 else 0
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self.pcp_size = get_pcp_group().world_size
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self.pcp_rank = get_pcp_group(
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).rank_in_group if self.pcp_size > 1 else 0
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self.dcp_size = get_decode_context_model_parallel_world_size()
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self.dcp_rank = get_decode_context_model_parallel_rank(
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) if self.dcp_size > 1 else 0
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@@ -350,8 +340,7 @@ class AscendAttentionMetadataBuilder:
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context_lens_cpu = num_computed_tokens_cpu[
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num_decodes:num_reqs]
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max_context_len_cpu = context_lens_cpu.max().item()
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pcp_size = get_prefill_context_model_parallel_world_size(
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) if prefill_context_parallel_enable() else 1
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pcp_size = get_pcp_group().world_size
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if self.chunked_prefill_enabled and max_context_len_cpu > 0:
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local_context_lens_allranks = torch.tensor(
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num_computed_tokens_of_pcp_dcp
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@@ -539,10 +528,9 @@ class AscendAttentionBackendImpl(AttentionImpl):
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self.num_queries_per_kv = self.num_heads // self.num_kv_heads
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self.key_cache = None
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self.value_cache = None
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self.pcp_size = get_prefill_context_model_parallel_world_size(
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) if prefill_context_parallel_enable() else 1
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self.pcp_rank = get_prefill_context_model_parallel_rank(
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) if self.pcp_size > 1 else 0
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self.pcp_size = get_pcp_group().world_size
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self.pcp_rank = get_pcp_group(
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).rank_in_group if self.pcp_size > 1 else 0
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self.pcp_group = get_pcp_group(
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).device_group if self.pcp_size > 1 else None
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