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https://github.com/huggingface/text-generation-inference.git
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Merge f147f10ed4
into 0627983c17
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commit
97bbd136de
@ -45,7 +45,7 @@ RUN cargo build --profile release-opt --frozen
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# Text Generation Inference base image for Intel
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FROM intel/oneapi-basekit:2025.0.1-0-devel-ubuntu22.04 AS xpu
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FROM intel/oneapi-basekit:2025.1.3-0-devel-ubuntu22.04 AS xpu
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USER root
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@ -99,7 +99,8 @@ ENV HF_HOME=/data \
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WORKDIR /usr/src
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RUN pip install torch==2.7.0 torchvision==0.22.0 --index-url https://download.pytorch.org/whl/xpu
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#RUN pip install torch==2.7.0 torchvision==0.22.0 --index-url https://download.pytorch.org/whl/xpu
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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
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# Install server
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COPY proto proto
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@ -117,8 +118,7 @@ ENV TORCH_LLM_ALLREDUCE=1
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ENV CCL_TOPO_FABRIC_VERTEX_CONNECTION_CHECK=0
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ENV TORCH_DEVICE_BACKEND_AUTOLOAD=0
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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
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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
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#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
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# Install benchmarker
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COPY --from=builder /usr/src/target/release-opt/text-generation-benchmark /usr/local/bin/text-generation-benchmark
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# Install router
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@ -90,7 +90,7 @@ class TensorParallelHead(SuperLayer):
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local_out = gather_input.T
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torch.mm(input, self.linear.weight.T, out=local_out)
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if SYSTEM == "ipex":
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if SYSTEM == "ipex" and gather_input.device.type == "cpu":
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ipex.distributed.all_gather_into_tensor(
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world_out, gather_input, group=self.process_group
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)
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@ -107,7 +107,7 @@ class TensorParallelHead(SuperLayer):
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world_output = [
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torch.empty_like(output) for _ in range(self.process_group.size())
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]
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if SYSTEM == "ipex":
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if SYSTEM == "ipex" and output.device.type == "cpu":
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ipex.distributed.all_gather(world_output, output, group=self.process_group)
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else:
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torch.distributed.all_gather(world_output, output, group=self.process_group)
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@ -202,7 +202,7 @@ class TensorParallelRowLinear(SuperLayer):
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def forward(self, input: torch.Tensor, reduce: bool = True) -> torch.Tensor:
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out = super().forward(input)
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if self.process_group.size() > 1 and reduce:
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if SYSTEM == "ipex":
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if SYSTEM == "ipex" and out.device.type == "cpu":
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ipex.distributed.all_reduce(out, group=self.process_group)
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else:
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torch.distributed.all_reduce(out, group=self.process_group)
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@ -242,7 +242,7 @@ class TensorParallelEmbedding(torch.nn.Module):
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)
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out = torch.nn.functional.embedding(input, self.weight)
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if self.reduce and self.process_group.size() > 1:
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if SYSTEM == "ipex":
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if SYSTEM == "ipex" and out.device.type == "cpu":
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ipex.distributed.all_reduce(out, group=self.process_group)
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else:
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torch.distributed.all_reduce(out, group=self.process_group)
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@ -79,7 +79,16 @@ def initialize_torch_distributed():
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), "Each process is one xpu"
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device = RANK % torch.xpu.device_count()
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torch.xpu.set_device(device)
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device_id = torch.device(f"xpu:{RANK}")
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torch.distributed.init_process_group(
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backend="xccl",
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world_size=WORLD_SIZE,
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rank=RANK,
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timeout=timedelta(seconds=120),
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pg_options=options,
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device_id=device_id,
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)
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else:
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ipex.distributed.init_process_group(
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backend="ccl",
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world_size=WORLD_SIZE,
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