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docs/ru/docs/deployment/docker.md
@app.get("/items/{item_id}") def read_item(item_id: int, q: Union[str, None] = None): return {"item_id": item_id, "q": q} ``` ### Dockerfile В этой же директории создайте файл `Dockerfile` и заполните его: ```{ .dockerfile .annotate } # (1) FROM python:3.9 # (2) WORKDIR /code # (3) COPY ./requirements.txt /code/requirements.txt # (4)
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.bazelrc
# Another good option is to use our Docker containers to build and test TF: # https://github.com/tensorflow/tensorflow/tree/master/tensorflow/tools/tf_sig_build_dockerfiles. build:unsupported_cpu_linux --config=avx_linux build:unsupported_cpu_linux --crosstool_top="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain"
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