reenable xpu for tgi (#1939)
# What does this PR do? <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution. Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change. Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost. --> <!-- Remove if not applicable --> Fixes # (issue) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests), Pull Request section? - [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link to it if that's the case. - [ ] Did you make sure to update the documentation with your changes? Here are the [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation). - [ ] Did you write any new necessary tests? ## Who can review? Anyone in the community is free to review the PR once the tests have passed. Feel free to tag members/contributors who may be interested in your PR. <!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @ @OlivierDehaene OR @Narsil --> Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
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@ -43,6 +43,7 @@ USER root
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RUN wget http://nz2.archive.ubuntu.com/ubuntu/pool/main/o/openssl/libssl1.1_1.1.1f-1ubuntu2_amd64.deb && \
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dpkg -i ./libssl1.1_1.1.1f-1ubuntu2_amd64.deb
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RUN wget -qO - https://repositories.intel.com/gpu/intel-graphics.key | gpg --dearmor | tee /usr/share/keyrings/intel-graphics.gpg > /dev/null
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RUN wget -O- https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB \
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| gpg --dearmor | tee /usr/share/keyrings/oneapi-archive-keyring.gpg > /dev/null && echo "deb [signed-by=/usr/share/keyrings/oneapi-archive-keyring.gpg] https://apt.repos.intel.com/oneapi all main" | tee /etc/apt/sources.list.d/oneAPI.list
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@ -9,6 +9,8 @@ if SYSTEM == "cuda":
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import rotary_emb
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elif SYSTEM == "rocm":
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from vllm._C import ops
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elif SYSTEM == "xpu":
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import intel_extension_for_pytorch as ipex
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def _create_inv_freq(dim, base, device):
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@ -62,7 +62,7 @@ if SYSTEM == "cuda":
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elif SYSTEM == "rocm":
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from vllm._C import ops
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else:
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raise RuntimeError(f"Unsupported system {SYSTEM}")
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dropout_layer_norm = None
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@dataclass
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@ -5,7 +5,9 @@ from loguru import logger
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import math
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from text_generation_server.utils.import_utils import SYSTEM
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from text_generation_server.utils.flash_attn_triton import triton_attention
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if SYSTEM != "xpu":
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from text_generation_server.utils.flash_attn_triton import triton_attention
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if os.getenv("USE_FLASH_ATTENTION", "").lower() == "false":
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raise ImportError("`USE_FLASH_ATTENTION` is false.")
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@ -15,43 +17,6 @@ HAS_FLASH_ATTN_V2_ROCM = False
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ROCM_USE_FLASH_ATTN_V2_CK = False
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ROCM_USE_FLASH_ATTN_V2_TRITON = False
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if SYSTEM == "xpu":
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import intel_extension_for_pytorch as ipex
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def attention(
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q,
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k,
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v,
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out,
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cu_seqlens,
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max_s,
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softmax_scale,
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window_size_left=-1,
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):
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if window_size_left <= 0 and window_size_left != -1:
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raise ValueError("`window_size_left` must be > 0 or -1")
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if window_size_left != -1:
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raise ValueError(
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f"XPU version of Flash Attention does not support window attention (window_size_left != -1, got window_size_left={window_size_left})."
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)
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return ipex.llm.functional.varlen_attention(
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q,
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k,
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v,
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out,
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cu_seqlens,
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cu_seqlens,
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max_s,
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max_s,
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0.0,
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softmax_scale,
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False,
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True,
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False,
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None,
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)
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if SYSTEM in {"cuda", "rocm"}:
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if not torch.cuda.is_available():
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@ -124,8 +89,44 @@ if SYSTEM in {"cuda", "rocm"}:
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logger.warning(f"Unable to use Flash Attention V2: {e}")
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HAS_FLASH_ATTN = True
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if SYSTEM == "xpu":
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import intel_extension_for_pytorch as ipex
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if HAS_FLASH_ATTN_V2_CUDA:
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def attention(
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q,
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k,
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v,
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out,
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cu_seqlens,
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max_s,
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softmax_scale,
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window_size_left=-1,
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):
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if window_size_left <= 0 and window_size_left != -1:
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raise ValueError("`window_size_left` must be > 0 or -1")
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if window_size_left != -1:
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raise ValueError(
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f"XPU version of Flash Attention does not support window attention (window_size_left != -1, got window_size_left={window_size_left})."
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)
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return ipex.llm.functional.varlen_attention(
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q,
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k,
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v,
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out,
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cu_seqlens,
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cu_seqlens,
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max_s,
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max_s,
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0.0,
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softmax_scale,
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False,
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True,
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False,
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None,
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)
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elif HAS_FLASH_ATTN_V2_CUDA:
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def attention(
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q,
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@ -17,7 +17,7 @@ def get_cuda_free_memory(device, memory_fraction):
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return free_memory
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def get_xpu_free_memory(device):
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def get_xpu_free_memory(device, memory_fraction):
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total_gpu_memory = torch.xpu.get_device_properties(device).total_memory
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free_memory = int(total_gpu_memory * 0.5)
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return free_memory
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