akankshakshurai/cuda-error-resolution-analysis huggingface dataset:
Docker ccache rebuild bug

username: veritas
cooked: <p>I am currently building PyTorch from source using a Dockerfile with BuildKit enabled.<br>
I am using CCache to cache my builds.<br>
Although CCache does increase the build speed, I find that the project is rebuilt even when the same branch is checked out. Is this to be expected?<br>
I include a link to my project. This issue does not occur in the same run but between different Docker builds.</p><aside class="onebox githubblob" data-onebox-src="https://github.com/cresset-template/cresset/blob/main/Dockerfile#L239">
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      <a href="https://github.com/cresset-template/cresset/blob/main/Dockerfile#L239" target="_blank" rel="noopener nofollow ugc">github.com</a>
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    <h4><a href="https://github.com/cresset-template/cresset/blob/main/Dockerfile#L239" target="_blank" rel="noopener nofollow ugc">cresset-template/cresset/blob/main/Dockerfile#L239</a></h4>



    <pre class="onebox">      <code class="lang-">
        <ol class="start lines" start="229" style="counter-reset: li-counter 228 ;">
            <li>ARG USE_ROCM</li>
            <li>ARG USE_NNPACK=0</li>
            <li>ARG USE_QNNPACK=0</li>
            <li>ARG BUILD_TEST=0</li>
            <li>ARG BUILD_CAFFE2=0</li>
            <li>ARG USE_PRECOMPILED_HEADERS</li>
            <li>ARG TORCH_CUDA_ARCH_LIST</li>
            <li>ARG CMAKE_PREFIX_PATH=/opt/conda</li>
            <li>ARG TORCH_NVCC_FLAGS="-Xfatbin -compress-all"</li>
            <li># Build wheel for installation in later stages.</li>
            <li class="selected">RUN --mount=type=cache,target=/opt/ccache \</li>
            <li>    python setup.py bdist_wheel -d /tmp/dist</li>
            <li># Install PyTorch for subsidiary libraries.</li>
            <li>RUN --mount=type=cache,target=/opt/ccache \</li>
            <li>    python setup.py install</li>
            <li>
            </li>
<li>###### Additional information for custom builds. ######</li>
            <li>
            </li>
<li># Manually edit conda package versions if older PyTorch versions will not build.</li>
            <li>
            </li>
<li># Use this to build with custom CMake settings.</li>
        </ol>
      </code>
    </pre>



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