How can I apply cache to all layers in a builder with the docker-container driver in docker buildx build ?

[waveofmymind]

Hello,
As the title suggests, after creating a buildx builder with --driver=docker-container, when using local cache, the build time differs from the default builder. (Here, the local cache is not the cache specified by the cache-from/cache-to options with type=local.)

Here is my Dockerfile.

FROM pytorch/pytorch:2.0.1-cuda11.7-cudnn8-devel

WORKDIR /test-dir
ENV PYTHONPATH :/test-dir
ENV PYTHONUNBUFFERED 1
ENV DEBIAN_FRONTEND=noninteractive
ENV TZ=Asia/Seoul

# tini
ENV TINI_VERSION v0.19.0
ADD [https://github.com/krallin/tini/releases/download/${TINI_VERSION}/tini](https://github.com/krallin/tini/releases/download/$%7BTINI_VERSION%7D/tini) /tini
RUN chmod +x /tini

RUN apt update && apt-get install -y software-properties-common
RUN add-apt-repository ppa:deadsnakes/ppa && \
    apt update && \
    apt-get install -y git curl libgl1 libglib2.0-0 libgoogle-perftools-dev && \
    rm -rf /var/lib/apt/lists/*

## Install requirements
COPY requirements.txt .
RUN python -m pip install --no-cache-dir -r requirements.txt

COPY . ./


ENTRYPOINT ["/tini", "--"]
CMD ["python", "src/workers/worker.py"]

I used the aforementioned Dockerfile and employed the default builder.

docker buildx ls

NAME/NODE       DRIVER/ENDPOINT  STATUS  BUILDKIT             PLATFORMS
default *       docker                                        
  default       default          running v0.11.7+d3e6c1360f6e linux/arm64, linux/amd64, linux/amd64/v2, linux/riscv64, linux/ppc64le, linux/s390x, linux/386, linux/mips64le, linux/mips64, linux/arm/v7, linux/arm/v6
desktop-linux   docker                                        
  desktop-linux desktop-linux    running v0.11.7+d3e6c1360f6e linux/arm64, linux/amd64, linux/amd64/v2, linux/riscv64, linux/ppc64le, linux/s390x, linux/386, linux/mips64le, linux/mips64, linux/arm/v7, linux/arm/v6

Additionally, the build command is as follows.

docker buildx build -t waveofmymind/waveofmymind:latest -f src/tasks/concept/Dockerfile .

Using this method, the first build takes 391.8s, and the following log is produced.

docker buildx build -t waveofmymind/waveofmymind:latest -f src/tasks/concept/Dockerfile .
[+] Building 391.8s (16/16) FINISHED                                                                                                  docker:default
 => [internal] load build definition from Dockerfile                                                                                            0.0s
 => => transferring dockerfile: 910B                                                                                                            0.0s
 => [internal] load .dockerignore                                                                                                               0.0s
 => => transferring context: 81B                                                                                                                0.0s
 => [internal] load metadata for docker.io/pytorch/pytorch:2.0.1-cuda11.7-cudnn8-devel                                                          2.4s
 => [auth] pytorch/pytorch:pull token for registry-1.docker.io                                                                                  0.0s
 => [internal] load build context                                                                                                               0.7s
 => => transferring context: 30.78MB                                                                                                            0.7s
 => [1/9] FROM docker.io/pytorch/pytorch:2.0.1-cuda11.7-cudnn8-devel@sha256:4f66166dd757752a6a6a9284686b4078e92337cd9d12d2e14d2d46274dfa9048  175.9s
 => => resolve docker.io/pytorch/pytorch:2.0.1-cuda11.7-cudnn8-devel@sha256:4f66166dd757752a6a6a9284686b4078e92337cd9d12d2e14d2d46274dfa9048    0.0s
 => => sha256:713ab758de5c712ded54bf361bf901cac5d3f6cb6373f7a2ef1db0259a05cc0c 47.88MB / 47.88MB                                                3.1s
 => => sha256:0343fab37dbdcfc79717e0ee8d7dc401f2a7003ce9a318b44225a62c10b2e52a 7.91MB / 7.91MB                                                  1.2s
 => => sha256:42a0e9b621e250719cb14f3d28fd423d795f2d85edaee81b582640ae44e93a09 20.68kB / 20.68kB                                                0.0s
 => => sha256:846c0b181fff0c667d9444f8378e8fcfa13116da8d308bf21673f7e4bea8d580 28.58MB / 28.58MB                                                1.0s
 => => sha256:4f66166dd757752a6a6a9284686b4078e92337cd9d12d2e14d2d46274dfa9048 3.68kB / 3.68kB                                                  0.0s
 => => extracting sha256:846c0b181fff0c667d9444f8378e8fcfa13116da8d308bf21673f7e4bea8d580                                                       1.2s
 => => sha256:34a29b29369c6dd258bd6b95b6020ce0672375c47c9a5788a90f0c2df784a270 187B / 187B                                                      1.3s
 => => sha256:d5b3d7d26c3817886ecf860901a4832c6e35088f57e52fac1f8ad4765ebabb7a 6.43kB / 6.43kB                                                  1.4s
 => => sha256:8d7ddd137efb816d8241a2b238c619500a90f26505cfec4140f11b55ce1157bb 1.09GB / 1.09GB                                                 57.0s
 => => sha256:435f0417c8c03cba392ec7a1714bc69a8175f45a0514d0665b74b28335b14884 62.31kB / 62.31kB                                                1.6s
 => => sha256:e5ded0ebc4016fff4cb9f0c70f0c3ce8a3e68ff5f49936fc62af083e797af294 1.68kB / 1.68kB                                                  1.9s
 => => sha256:8625dee38d858753c0478a95083b4391cf46fbbd7268f00529fdb43b8018d684 1.52kB / 1.52kB                                                  2.2s
 => => sha256:31b4cbf1dca73d4c751a998814c1ce9c8cdd761f274c73782270e6f7fe73cdab 1.42GB / 1.42GB                                                 71.7s
 => => extracting sha256:0343fab37dbdcfc79717e0ee8d7dc401f2a7003ce9a318b44225a62c10b2e52a                                                       0.2s
 => => extracting sha256:713ab758de5c712ded54bf361bf901cac5d3f6cb6373f7a2ef1db0259a05cc0c                                                       0.6s
 => => sha256:f9334d026a1621c2906b9ba8170f3d20a1b5bf527da3e30197d5085e86a7a492 85.31kB / 85.31kB                                                3.5s
 => => sha256:e26e23da3e450407731a7a5802ac87d332f8507880fc8277ee1c319273b120e6 1.15GB / 1.15GB                                                 62.7s
 => => extracting sha256:34a29b29369c6dd258bd6b95b6020ce0672375c47c9a5788a90f0c2df784a270                                                       0.0s
 => => extracting sha256:d5b3d7d26c3817886ecf860901a4832c6e35088f57e52fac1f8ad4765ebabb7a                                                       0.0s
 => => extracting sha256:8d7ddd137efb816d8241a2b238c619500a90f26505cfec4140f11b55ce1157bb                                                      11.2s
 => => sha256:01340e644d393735f7672e41b4fd08eeb0aad003a6b7b2488b31383de03bab39 887.70kB / 887.70kB                                             58.0s
 => => sha256:11b594ba139d13d291d0227243fe068a0e57eed698fa78c7ffeecff933227553 3.11GB / 3.11GB                                                127.2s
 => => sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1 32B / 32B                                                       63.1s
 => => sha256:21f821181543606bb2d93e7dcce09966436d749b63b392fa8e06aacca4fdd3e7 99B / 99B                                                       63.4s
 => => extracting sha256:435f0417c8c03cba392ec7a1714bc69a8175f45a0514d0665b74b28335b14884                                                       0.0s
 => => extracting sha256:e5ded0ebc4016fff4cb9f0c70f0c3ce8a3e68ff5f49936fc62af083e797af294                                                       0.0s
 => => extracting sha256:8625dee38d858753c0478a95083b4391cf46fbbd7268f00529fdb43b8018d684                                                       0.0s
 => => extracting sha256:31b4cbf1dca73d4c751a998814c1ce9c8cdd761f274c73782270e6f7fe73cdab                                                      18.2s
 => => extracting sha256:f9334d026a1621c2906b9ba8170f3d20a1b5bf527da3e30197d5085e86a7a492                                                       0.0s
 => => extracting sha256:e26e23da3e450407731a7a5802ac87d332f8507880fc8277ee1c319273b120e6                                                      17.0s
 => => extracting sha256:01340e644d393735f7672e41b4fd08eeb0aad003a6b7b2488b31383de03bab39                                                       0.1s
 => => extracting sha256:11b594ba139d13d291d0227243fe068a0e57eed698fa78c7ffeecff933227553                                                      47.7s
 => => extracting sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1                                                       0.0s
 => => extracting sha256:21f821181543606bb2d93e7dcce09966436d749b63b392fa8e06aacca4fdd3e7                                                       0.0s
 => https://github.com/krallin/tini/releases/download/v0.19.0/tini                                                                              1.4s
 => [2/9] WORKDIR /test-dir                                                                                                                0.4s
 => [3/9] ADD https://github.com/krallin/tini/releases/download/v0.19.0/tini /tini                                                              0.2s
 => [4/9] RUN chmod +x /tini                                                                                                                    0.5s
 => [5/9] RUN apt update && apt-get install -y software-properties-common                                                                      48.9s
 => [6/9] RUN add-apt-repository ppa:deadsnakes/ppa &&     apt update &&     apt-get install -y git curl libgl1 libglib2.0-0 libgoogle-perfto  38.0s
 => [7/9] COPY requirements.txt .                                                                                                               0.0s
 => [8/9] RUN python -m pip install --no-cache-dir -r requirements.txt                                                                        111.3s
 => [9/9] COPY . ./                                                                                                                             0.2s
 => exporting to image                                                                                                                         13.7s
 => => exporting layers                                                                                                                        13.6s
 => => writing image sha256:78f4ea9a21bede48e57d42c21d141d9eb64217692e267ab57b05fcf326c884fe                                                    0.0s
 => => naming to docker.io/waveofmymind/waveofmymind:latest 

When executing the second build consecutively, cache is applied to all layers, taking only 4s.

[+] Building 4.0s (16/16) FINISHED                                                                                                    docker:default
 => [internal] load build definition from Dockerfile                                                                                            0.0s
 => => transferring dockerfile: 910B                                                                                                            0.0s
 => [internal] load .dockerignore                                                                                                               0.0s
 => => transferring context: 81B                                                                                                                0.0s
 => [internal] load metadata for docker.io/pytorch/pytorch:2.0.1-cuda11.7-cudnn8-devel                                                          2.6s
 => [auth] pytorch/pytorch:pull token for registry-1.docker.io                                                                                  0.0s
 => [internal] load build context                                                                                                               0.1s
 => => transferring context: 19.62kB                                                                                                            0.0s
 => [1/9] FROM docker.io/pytorch/pytorch:2.0.1-cuda11.7-cudnn8-devel@sha256:4f66166dd757752a6a6a9284686b4078e92337cd9d12d2e14d2d46274dfa9048    0.0s
 => https://github.com/krallin/tini/releases/download/v0.19.0/tini                                                                              1.2s
 => CACHED [2/9] WORKDIR /test-dir                                                                                                         0.0s
 => CACHED [3/9] ADD https://github.com/krallin/tini/releases/download/v0.19.0/tini /tini                                                       0.0s
 => CACHED [4/9] RUN chmod +x /tini                                                                                                             0.0s
 => CACHED [5/9] RUN apt update && apt-get install -y software-properties-common                                                                0.0s
 => CACHED [6/9] RUN add-apt-repository ppa:deadsnakes/ppa &&     apt update &&     apt-get install -y git curl libgl1 libglib2.0-0 libgoogle-  0.0s
 => CACHED [7/9] COPY requirements.txt .                                                                                                        0.0s
 => CACHED [8/9] RUN python -m pip install --no-cache-dir -r requirements.txt                                                                   0.0s
 => CACHED [9/9] COPY . ./                                                                                                                      0.0s
 => exporting to image                                                                                                                          0.0s
 => => exporting layers                                                                                                                         0.0s
 => => writing image sha256:78f4ea9a21bede48e57d42c21d141d9eb64217692e267ab57b05fcf326c884fe                                                    0.0s
 => => naming to docker.io/waveofmymind/waveofmymind:latest

For the next case, to delete the previously processed data, I executed docker system prune -a and created a builder.

docker buildx create --name=waveofmymind-builder --driver=docker-container --use --bootstrap
NAME/NODE               DRIVER/ENDPOINT             STATUS  BUILDKIT             PLATFORMS
waveofmymind-builder *  docker-container                                        
  waveofmymind-builder0 unix:///var/run/docker.sock running v0.12.5              linux/arm64, linux/amd64, linux/amd64/v2, linux/riscv64, linux/ppc64le, linux/s390x, linux/386, linux/mips64le, linux/mips64, linux/arm/v7, linux/arm/v6
default                 docker                                                  
  default               default                     running v0.11.7+d3e6c1360f6e linux/arm64, linux/amd64, linux/amd64/v2, linux/riscv64, linux/ppc64le, linux/s390x, linux/386, linux/mips64le, linux/mips64, linux/arm/v7, linux/arm/v6
desktop-linux           docker                                                  
  desktop-linux         desktop-linux               running v0.11.7+d3e6c1360f6e linux/arm64, linux/amd64, linux/amd64/v2, linux/riscv64, linux/ppc64le, linux/s390x, linux/386, linux/mips64le, linux/mips64, linux/arm/v7, linux/arm/v6

And then I proceed with the first build again. It took 391s

[+] Building 391.3s (15/15) FINISHED                                                                                       docker-container:testtest
 => [internal] load build definition from Dockerfile                                                                                            0.0s
 => => transferring dockerfile: 910B                                                                                                            0.0s
 => [internal] load metadata for docker.io/pytorch/pytorch:2.0.1-cuda11.7-cudnn8-devel                                                          2.4s
 => [auth] pytorch/pytorch:pull token for registry-1.docker.io                                                                                  0.0s
 => [internal] load .dockerignore                                                                                                               0.0s
 => => transferring context: 81B                                                                                                                0.0s
 => [1/9] FROM docker.io/pytorch/pytorch:2.0.1-cuda11.7-cudnn8-devel@sha256:4f66166dd757752a6a6a9284686b4078e92337cd9d12d2e14d2d46274dfa9048  181.5s
 => => resolve docker.io/pytorch/pytorch:2.0.1-cuda11.7-cudnn8-devel@sha256:4f66166dd757752a6a6a9284686b4078e92337cd9d12d2e14d2d46274dfa9048    0.0s
 => => sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1 32B / 32B                                                        0.2s
 => => sha256:11b594ba139d13d291d0227243fe068a0e57eed698fa78c7ffeecff933227553 3.11GB / 3.11GB                                                121.1s
 => => sha256:21f821181543606bb2d93e7dcce09966436d749b63b392fa8e06aacca4fdd3e7 99B / 99B                                                        0.7s
 => => sha256:e26e23da3e450407731a7a5802ac87d332f8507880fc8277ee1c319273b120e6 1.15GB / 1.15GB                                                 84.7s
 => => sha256:01340e644d393735f7672e41b4fd08eeb0aad003a6b7b2488b31383de03bab39 887.70kB / 887.70kB                                              0.7s
 => => sha256:f9334d026a1621c2906b9ba8170f3d20a1b5bf527da3e30197d5085e86a7a492 85.31kB / 85.31kB                                                0.3s
 => => sha256:31b4cbf1dca73d4c751a998814c1ce9c8cdd761f274c73782270e6f7fe73cdab 1.42GB / 1.42GB                                                109.9s
 => => sha256:8625dee38d858753c0478a95083b4391cf46fbbd7268f00529fdb43b8018d684 1.52kB / 1.52kB                                                  0.3s
 => => sha256:e5ded0ebc4016fff4cb9f0c70f0c3ce8a3e68ff5f49936fc62af083e797af294 1.68kB / 1.68kB                                                  2.4s
 => => sha256:435f0417c8c03cba392ec7a1714bc69a8175f45a0514d0665b74b28335b14884 62.31kB / 62.31kB                                                0.3s
 => => sha256:8d7ddd137efb816d8241a2b238c619500a90f26505cfec4140f11b55ce1157bb 1.09GB / 1.09GB                                                 85.2s
 => => sha256:d5b3d7d26c3817886ecf860901a4832c6e35088f57e52fac1f8ad4765ebabb7a 6.43kB / 6.43kB                                                  0.7s
 => => sha256:34a29b29369c6dd258bd6b95b6020ce0672375c47c9a5788a90f0c2df784a270 187B / 187B                                                      0.5s
 => => sha256:713ab758de5c712ded54bf361bf901cac5d3f6cb6373f7a2ef1db0259a05cc0c 47.88MB / 47.88MB                                                3.4s
 => => sha256:846c0b181fff0c667d9444f8378e8fcfa13116da8d308bf21673f7e4bea8d580 28.58MB / 28.58MB                                                1.9s
 => => sha256:0343fab37dbdcfc79717e0ee8d7dc401f2a7003ce9a318b44225a62c10b2e52a 7.91MB / 7.91MB                                                  1.4s
 => => extracting sha256:846c0b181fff0c667d9444f8378e8fcfa13116da8d308bf21673f7e4bea8d580                                                       0.5s
 => => extracting sha256:0343fab37dbdcfc79717e0ee8d7dc401f2a7003ce9a318b44225a62c10b2e52a                                                       0.1s
 => => extracting sha256:713ab758de5c712ded54bf361bf901cac5d3f6cb6373f7a2ef1db0259a05cc0c                                                       0.7s
 => => extracting sha256:34a29b29369c6dd258bd6b95b6020ce0672375c47c9a5788a90f0c2df784a270                                                       0.0s
 => => extracting sha256:d5b3d7d26c3817886ecf860901a4832c6e35088f57e52fac1f8ad4765ebabb7a                                                       0.0s
 => => extracting sha256:8d7ddd137efb816d8241a2b238c619500a90f26505cfec4140f11b55ce1157bb                                                      11.6s
 => => extracting sha256:435f0417c8c03cba392ec7a1714bc69a8175f45a0514d0665b74b28335b14884                                                       0.0s
 => => extracting sha256:e5ded0ebc4016fff4cb9f0c70f0c3ce8a3e68ff5f49936fc62af083e797af294                                                       0.0s
 => => extracting sha256:8625dee38d858753c0478a95083b4391cf46fbbd7268f00529fdb43b8018d684                                                       0.0s
 => => extracting sha256:31b4cbf1dca73d4c751a998814c1ce9c8cdd761f274c73782270e6f7fe73cdab                                                      16.1s
 => => extracting sha256:f9334d026a1621c2906b9ba8170f3d20a1b5bf527da3e30197d5085e86a7a492                                                       0.2s
 => => extracting sha256:e26e23da3e450407731a7a5802ac87d332f8507880fc8277ee1c319273b120e6                                                      11.7s
 => => extracting sha256:01340e644d393735f7672e41b4fd08eeb0aad003a6b7b2488b31383de03bab39                                                       0.1s
 => => extracting sha256:11b594ba139d13d291d0227243fe068a0e57eed698fa78c7ffeecff933227553                                                      42.1s
 => => extracting sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1                                                       0.0s
 => => extracting sha256:21f821181543606bb2d93e7dcce09966436d749b63b392fa8e06aacca4fdd3e7                                                       0.0s
 => https://github.com/krallin/tini/releases/download/v0.19.0/tini                                                                              1.2s
 => [internal] load build context                                                                                                               0.5s
 => => transferring context: 30.78MB                                                                                                            0.5s
 => [2/9] WORKDIR /test-dir                                                                                                                 0.1s
 => [3/9] ADD https://github.com/krallin/tini/releases/download/v0.19.0/tini /tini                                                              0.0s
 => [4/9] RUN chmod +x /tini                                                                                                                    0.1s
 => [5/9] RUN apt update && apt-get install -y software-properties-common                                                                      47.5s
 => [6/9] RUN add-apt-repository ppa:deadsnakes/ppa &&     apt update &&     apt-get install -y git curl libgl1 libglib2.0-0 libgoogle-perfto  38.2s
 => [7/9] COPY requirements.txt .                                                                                                               0.0s
 => [8/9] RUN python -m pip install --no-cache-dir -r requirements.txt                                                                        120.5s
 => [9/9] COPY . ./ 

The next build took 381s.

[+] Building 381.3s (15/15) FINISHED                                                                                       docker-container:testtest
 => [internal] load build definition from Dockerfile                                                                                            0.0s
 => => transferring dockerfile: 910B                                                                                                            0.0s
 => [internal] load metadata for docker.io/pytorch/pytorch:2.0.1-cuda11.7-cudnn8-devel                                                          2.1s
 => [auth] pytorch/pytorch:pull token for registry-1.docker.io                                                                                  0.0s
 => [internal] load .dockerignore                                                                                                               0.0s
 => => transferring context: 81B                                                                                                                0.0s
 => [1/9] FROM docker.io/pytorch/pytorch:2.0.1-cuda11.7-cudnn8-devel@sha256:4f66166dd757752a6a6a9284686b4078e92337cd9d12d2e14d2d46274dfa9048  153.9s
 => => resolve docker.io/pytorch/pytorch:2.0.1-cuda11.7-cudnn8-devel@sha256:4f66166dd757752a6a6a9284686b4078e92337cd9d12d2e14d2d46274dfa9048    0.0s
 => => sha256:21f821181543606bb2d93e7dcce09966436d749b63b392fa8e06aacca4fdd3e7 99B / 99B                                                        0.3s
 => => sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1 32B / 32B                                                        0.5s
 => => sha256:11b594ba139d13d291d0227243fe068a0e57eed698fa78c7ffeecff933227553 3.11GB / 3.11GB                                                102.0s
 => => sha256:01340e644d393735f7672e41b4fd08eeb0aad003a6b7b2488b31383de03bab39 887.70kB / 887.70kB                                              0.8s
 => => sha256:e26e23da3e450407731a7a5802ac87d332f8507880fc8277ee1c319273b120e6 1.15GB / 1.15GB                                                 60.0s
 => => sha256:f9334d026a1621c2906b9ba8170f3d20a1b5bf527da3e30197d5085e86a7a492 85.31kB / 85.31kB                                                0.4s
 => => sha256:31b4cbf1dca73d4c751a998814c1ce9c8cdd761f274c73782270e6f7fe73cdab 1.42GB / 1.42GB                                                 83.0s
 => => extracting sha256:31b4cbf1dca73d4c751a998814c1ce9c8cdd761f274c73782270e6f7fe73cdab                                                      17.8s
 => => extracting sha256:f9334d026a1621c2906b9ba8170f3d20a1b5bf527da3e30197d5085e86a7a492                                                       0.0s
 => => extracting sha256:e26e23da3e450407731a7a5802ac87d332f8507880fc8277ee1c319273b120e6                                                      11.6s
 => => extracting sha256:01340e644d393735f7672e41b4fd08eeb0aad003a6b7b2488b31383de03bab39                                                       0.1s
 => => extracting sha256:11b594ba139d13d291d0227243fe068a0e57eed698fa78c7ffeecff933227553                                                      40.5s
 => => extracting sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1                                                       0.0s
 => => extracting sha256:21f821181543606bb2d93e7dcce09966436d749b63b392fa8e06aacca4fdd3e7                                                       0.0s
 => CACHED https://github.com/krallin/tini/releases/download/v0.19.0/tini                                                                       1.2s
 => [internal] load build context                                                                                                               0.5s
 => => transferring context: 30.78MB                                                                                                            0.5s
 => [2/9] WORKDIR /test-dir                                                                                                             0.1s
 => [3/9] ADD https://github.com/krallin/tini/releases/download/v0.19.0/tini /tini                                                              0.0s
 => [4/9] RUN chmod +x /tini                                                                                                                    0.1s
 => [5/9] RUN apt update && apt-get install -y software-properties-common                                                                      70.4s
 => [6/9] RUN add-apt-repository ppa:deadsnakes/ppa &&     apt update &&     apt-get install -y git curl libgl1 libglib2.0-0 libgoogle-perfto  37.2s 
 => [7/9] COPY requirements.txt .                                                                                                               0.0s 
 => [8/9] RUN python -m pip install --no-cache-dir -r requirements.txt                                                                        115.5s 
 => [9/9] COPY . ./

I expected the build time to speed up from the first to the second build, similar to the results with the default builder, where local cache was used for all layers, but this did not happen.

Additionally, I tried using the --cache-from and --cache-to options with type=local to store and retrieve cache data in a local directory, but the build time did not decrease drastically as it did when using the default builder.

Is it impossible to use cache data for all layers like when using the default builder? Is there a need for additional settings?

The reason I want to use this method is because I plan to use the --cache-from/--cache-to options with the type=s3 option in the future.

If cache data exists in the builder volume, I want to use local cache to speed up the build, and if there is no cache data available, I want to apply cache using s3 data.

thank you.

[koush]

@waveofmymind Running into this issue myself with CUDA and buildx builders (on GitHub actions) too. did you ever figure out a solution? Seems created builders effectively have no cache.