huggingface/text-generation-inference
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Merge f147f10ed4 into 0627983c17

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Wang, Yi 2025-06-18 06:50:46 +08:00 committed by GitHub
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3 changed files with 25 additions and 16 deletions
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8
Dockerfile_intel
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@ -45,7 +45,7 @@ RUN cargo build --profile release-opt --frozen
# Text Generation Inference base image for Intel # Text Generation Inference base image for Intel
FROM intel/oneapi-basekit:2025.0.1-0-devel-ubuntu22.04 AS xpu FROM intel/oneapi-basekit:2025.1.3-0-devel-ubuntu22.04 AS xpu
USER root USER root
@ -99,7 +99,8 @@ ENV HF_HOME=/data \
WORKDIR /usr/src WORKDIR /usr/src
RUN pip install torch==2.7.0 torchvision==0.22.0 --index-url https://download.pytorch.org/whl/xpu #RUN pip install torch==2.7.0 torchvision==0.22.0 --index-url https://download.pytorch.org/whl/xpu
RUN pip install --pre torch==2.8.0.dev20250526+xpu torchvision==0.22.0.dev20250526+xpu --index-url https://download.pytorch.org/whl/nightly/xpu
# Install server # Install server
COPY proto proto COPY proto proto
@ -117,8 +118,7 @@ ENV TORCH_LLM_ALLREDUCE=1
ENV CCL_TOPO_FABRIC_VERTEX_CONNECTION_CHECK=0 ENV CCL_TOPO_FABRIC_VERTEX_CONNECTION_CHECK=0
ENV TORCH_DEVICE_BACKEND_AUTOLOAD=0 ENV TORCH_DEVICE_BACKEND_AUTOLOAD=0
RUN pip install https://intel-extension-for-pytorch.s3.amazonaws.com/ipex_stable/xpu/oneccl_bind_pt-2.7.0%2Bxpu-cp311-cp311-linux_x86_64.whl #RUN pip install https://intel-extension-for-pytorch.s3.amazonaws.com/ipex_stable/xpu/intel_extension_for_pytorch-2.7.10%2Bxpu-cp311-cp311-linux_x86_64.whl
RUN pip install https://intel-extension-for-pytorch.s3.amazonaws.com/ipex_stable/xpu/intel_extension_for_pytorch-2.7.10%2Bxpu-cp311-cp311-linux_x86_64.whl
# Install benchmarker # Install benchmarker
COPY --from=builder /usr/src/target/release-opt/text-generation-benchmark /usr/local/bin/text-generation-benchmark COPY --from=builder /usr/src/target/release-opt/text-generation-benchmark /usr/local/bin/text-generation-benchmark
# Install router # Install router

8
server/text_generation_server/layers/tensor_parallel.py
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@ -90,7 +90,7 @@ class TensorParallelHead(SuperLayer):
local_out = gather_input.T local_out = gather_input.T
torch.mm(input, self.linear.weight.T, out=local_out) torch.mm(input, self.linear.weight.T, out=local_out)
if SYSTEM == "ipex": if SYSTEM == "ipex" and gather_input.device.type == "cpu":
ipex.distributed.all_gather_into_tensor( ipex.distributed.all_gather_into_tensor(
world_out, gather_input, group=self.process_group world_out, gather_input, group=self.process_group
) )
@ -107,7 +107,7 @@ class TensorParallelHead(SuperLayer):
world_output = [ world_output = [
torch.empty_like(output) for _ in range(self.process_group.size()) torch.empty_like(output) for _ in range(self.process_group.size())
] ]
if SYSTEM == "ipex": if SYSTEM == "ipex" and output.device.type == "cpu":
ipex.distributed.all_gather(world_output, output, group=self.process_group) ipex.distributed.all_gather(world_output, output, group=self.process_group)
else: else:
torch.distributed.all_gather(world_output, output, group=self.process_group) torch.distributed.all_gather(world_output, output, group=self.process_group)
@ -202,7 +202,7 @@ class TensorParallelRowLinear(SuperLayer):
def forward(self, input: torch.Tensor, reduce: bool = True) -> torch.Tensor: def forward(self, input: torch.Tensor, reduce: bool = True) -> torch.Tensor:
out = super().forward(input) out = super().forward(input)
if self.process_group.size() > 1 and reduce: if self.process_group.size() > 1 and reduce:
if SYSTEM == "ipex": if SYSTEM == "ipex" and out.device.type == "cpu":
ipex.distributed.all_reduce(out, group=self.process_group) ipex.distributed.all_reduce(out, group=self.process_group)
else: else:
torch.distributed.all_reduce(out, group=self.process_group) torch.distributed.all_reduce(out, group=self.process_group)
@ -242,7 +242,7 @@ class TensorParallelEmbedding(torch.nn.Module):
) )
out = torch.nn.functional.embedding(input, self.weight) out = torch.nn.functional.embedding(input, self.weight)
if self.reduce and self.process_group.size() > 1: if self.reduce and self.process_group.size() > 1:
if SYSTEM == "ipex": if SYSTEM == "ipex" and out.device.type == "cpu":
ipex.distributed.all_reduce(out, group=self.process_group) ipex.distributed.all_reduce(out, group=self.process_group)
else: else:
torch.distributed.all_reduce(out, group=self.process_group) torch.distributed.all_reduce(out, group=self.process_group)

25
server/text_generation_server/utils/dist.py
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@ -79,14 +79,23 @@ def initialize_torch_distributed():
), "Each process is one xpu" ), "Each process is one xpu"
device = RANK % torch.xpu.device_count() device = RANK % torch.xpu.device_count()
torch.xpu.set_device(device) torch.xpu.set_device(device)
device_id = torch.device(f"xpu:{RANK}")
ipex.distributed.init_process_group( torch.distributed.init_process_group(
backend="ccl", backend="xccl",
world_size=WORLD_SIZE, world_size=WORLD_SIZE,
rank=RANK, rank=RANK,
timeout=timedelta(seconds=120), timeout=timedelta(seconds=120),
pg_options=options, pg_options=options,
) device_id=device_id,
)
else:
ipex.distributed.init_process_group(
backend="ccl",
world_size=WORLD_SIZE,
rank=RANK,
timeout=timedelta(seconds=120),
pg_options=options,
)
else: else:
device = torch.device(f"cuda:{RANK}") device = torch.device(f"cuda:{RANK}")
torch.distributed.init_process_group( torch.distributed.init_process_group(