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Fix ZeroGPU compat: torch 2.6.0 -> 2.8.0, update causal_conv1d wheel
Browse files- Dockerfile +9 -8
Dockerfile
CHANGED
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@@ -3,8 +3,9 @@
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# Mirrors the HF Space (ZeroGPU) stack so we can validate the inference path
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# locally without the host's CUDA-13/Python-3.12 incompatibilities:
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# - Ubuntu 22.04 ships Python 3.10 (= Space's Python)
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# - cu12.
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# - causal_conv1d wheel for cu12torch2.
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#
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# Build:
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# docker build -t qwen3.5-ocr-jp-2b-local spaces/Qwen3.5-ocr-jp-2b/
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@@ -15,7 +16,7 @@
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# qwen3.5-ocr-jp-2b-local
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# Open http://localhost:7860
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FROM nvidia/cuda:12.
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# `devel` (not `runtime`) is required: triton JIT-compiles its CUDA driver
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# bindings (`backends/nvidia/driver.c` → `cuda_utils.so`) at first invocation,
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@@ -39,18 +40,18 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
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WORKDIR /app
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# Pin torch+vision from the cu12.
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RUN pip install --no-cache-dir \
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--extra-index-url https://download.pytorch.org/whl/
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torch==2.
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COPY requirements.txt .
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RUN pip install --no-cache-dir -r requirements.txt
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# Pre-install causal_conv1d for fla fast path (Python 3.10 / cu12 / torch 2.
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# app.py also tries to install at runtime; this pre-install just makes startup faster.
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RUN pip install --no-cache-dir --no-deps \
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https://github.com/Dao-AILab/causal-conv1d/releases/download/v1.
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COPY app.py .
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# Mirrors the HF Space (ZeroGPU) stack so we can validate the inference path
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# locally without the host's CUDA-13/Python-3.12 incompatibilities:
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# - Ubuntu 22.04 ships Python 3.10 (= Space's Python)
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# - cu12.8 runtime libs (pre-built torch 2.8.0 cu12 wheels target this)
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# - causal_conv1d wheel for cu12torch2.8 / cp310 / cxx11abi=TRUE
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# (torch >=2.8 ships with cxx11abi=TRUE by default)
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#
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# Build:
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# docker build -t qwen3.5-ocr-jp-2b-local spaces/Qwen3.5-ocr-jp-2b/
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# qwen3.5-ocr-jp-2b-local
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# Open http://localhost:7860
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FROM nvidia/cuda:12.8.1-devel-ubuntu22.04
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# `devel` (not `runtime`) is required: triton JIT-compiles its CUDA driver
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# bindings (`backends/nvidia/driver.c` → `cuda_utils.so`) at first invocation,
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WORKDIR /app
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# Pin torch+vision from the cu12.8 index so the wheel ABI matches our cuda image.
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RUN pip install --no-cache-dir \
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--extra-index-url https://download.pytorch.org/whl/cu128 \
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torch==2.8.0 torchvision==0.23.0
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COPY requirements.txt .
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RUN pip install --no-cache-dir -r requirements.txt
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# Pre-install causal_conv1d for fla fast path (Python 3.10 / cu12 / torch 2.8 / cxx11abi=TRUE).
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# app.py also tries to install at runtime; this pre-install just makes startup faster.
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RUN pip install --no-cache-dir --no-deps \
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https://github.com/Dao-AILab/causal-conv1d/releases/download/v1.6.2.post1/causal_conv1d-1.6.2.post1+cu12torch2.8cxx11abiTRUE-cp310-cp310-linux_x86_64.whl
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COPY app.py .
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