c272747d13
### What this PR does / why we need it?
adapt vllm-ascend main branch with vllm releases/v0.11.1
fix `forward context not set` in test_vlm.py caused by:
https://github.com/vllm-project/vllm/pull/23207
fix import `cdiv round` failed caused by:
https://github.com/vllm-project/vllm/pull/27188
fix import `init_cached_hf_modules` failed caused by:
https://github.com/vllm-project/vllm/pull/27567
adapt triton kernel `fused_recurrent_gated_delta_rule_fwd_kernel` caused
by: https://github.com/vllm-project/vllm/pull/27654
- remove unused code in sigmoid_gating.py
- `class FusedRecurrentFunction` , `fused_recurrent_gated_delta_rule`,
`fused_recurrent_gated_delta_rule_fwd`
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
CI
- vLLM version: v0.11.0
- vLLM main:
83f478bb19
Signed-off-by: 22dimensions <waitingwind@foxmail.com>
111 lines
3.9 KiB
Python
111 lines
3.9 KiB
Python
# mypy: ignore-errors
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import vllm.model_executor.models.config
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from vllm.logger import init_logger
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from vllm.model_executor.models import ModelRegistry
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from vllm.model_executor.models.config import MambaModelConfig
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from vllm_ascend.utils import vllm_version_is
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if vllm_version_is("0.11.0"):
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from vllm.utils import cdiv
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else:
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from vllm.utils.math_utils import cdiv
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from vllm.v1.kv_cache_interface import FullAttentionSpec, MambaSpec
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from vllm_ascend.utils import vllm_version_is
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if vllm_version_is("0.11.0"):
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from vllm.utils import STR_DTYPE_TO_TORCH_DTYPE
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else:
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from vllm.utils.torch_utils import STR_DTYPE_TO_TORCH_DTYPE
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@classmethod
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def verify_and_update_config(cls, vllm_config) -> None:
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"""
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Ensure that page size of attention layers is greater than or
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equal to the mamba layers. If not, automatically set the attention
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block size to ensure that it is. If the attention page size is
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strictly greater than the mamba page size, we pad the mamba page size
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to make them equal.
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Args:
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vllm_config: vLLM Config
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"""
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logger = init_logger(__name__)
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# Enable FULL_AND_PIECEWISE by default
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MambaModelConfig.verify_and_update_config(vllm_config)
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cache_config = vllm_config.cache_config
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model_config = vllm_config.model_config
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parallel_config = vllm_config.parallel_config
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if cache_config.cache_dtype == "auto":
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kv_cache_dtype = model_config.dtype
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else:
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kv_cache_dtype = STR_DTYPE_TO_TORCH_DTYPE[cache_config.cache_dtype]
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# get attention page size (for 1 token)
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attn_page_size_1_token = FullAttentionSpec(
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block_size=1,
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num_kv_heads=model_config.get_num_kv_heads(parallel_config),
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head_size=model_config.get_head_size(),
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dtype=kv_cache_dtype).page_size_bytes
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model_cls, _ = ModelRegistry.resolve_model_cls(
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model_config.architecture,
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model_config=model_config,
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)
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# get mamba page size
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mamba_page_size = MambaSpec(
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shapes=model_cls.get_mamba_state_shape_from_config(vllm_config),
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dtypes=model_cls.get_mamba_state_dtype_from_config(vllm_config),
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block_size=model_config.max_model_len,
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).page_size_bytes
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block_alignment_bytes = 128
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# some attention backends (e.g. FA) only support setting
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# block size to multiple of 16, so let's suggest a value
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# that would work (note: FA is currently not compatible
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# with mamba layers, use FlashInfer instead).
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attn_block_size = block_alignment_bytes * cdiv(
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mamba_page_size, block_alignment_bytes * attn_page_size_1_token)
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# override attention block size if either (a) the
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# user has not set it or (b) the user has set it
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# too small.
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if (cache_config.block_size is None
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or cache_config.block_size < attn_block_size):
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cache_config.block_size = attn_block_size
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logger.info(
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"Setting attention block size to %d tokens "
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"to ensure that attention page size is >= mamba page size.",
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attn_block_size)
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# compute new attention page size
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attn_page_size = \
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cache_config.block_size * attn_page_size_1_token
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assert attn_page_size >= mamba_page_size
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if attn_page_size == mamba_page_size:
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# don't need to pad mamba page size
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return
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# pad mamba page size to exactly match attention
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if (cache_config.mamba_page_size_padded is None
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or cache_config.mamba_page_size_padded != attn_page_size):
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cache_config.mamba_page_size_padded = (attn_page_size)
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mamba_padding_pct = 100 * (attn_page_size -
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mamba_page_size) / mamba_page_size
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logger.info(
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"Padding mamba page size by %.2f%% to ensure "
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"that mamba page size and attention page size are "
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"exactly equal.", mamba_padding_pct)
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vllm.model_executor.models.config.HybridAttentionMambaModelConfig.verify_and_update_config = verify_and_update_config
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