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Update lightgbm version and fix docker #272

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Update lightgbm version and fix docker #272

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6 changes: 3 additions & 3 deletions .github/workflows/docker_images.yml
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Expand Up @@ -32,8 +32,8 @@ jobs:
- docker/lightgbm-v3.2.1/linux_cuda_build.dockerfile
- docker/lightgbm-v3.2.1/linux_gpu_build.dockerfile
- docker/lightgbm-v3.2.1/linux_gpu_pip.dockerfile
- docker/lightgbm-v3.3.0/linux_cpu_mpi_build.dockerfile
- docker/lightgbm-v3.3.0/linux_cpu_mpi_pip.dockerfile
- docker/lightgbm-v3.3.3/linux_cpu_mpi_build.dockerfile
- docker/lightgbm-v3.3.3/linux_cpu_mpi_pip.dockerfile
- docker/lightgbm-custom/v321_patch_cpu_mpi_build.dockerfile
- src/scripts/training/lightgbm_python/default.dockerfile
- src/scripts/inferencing/lightgbm_python/default.dockerfile
Expand Down Expand Up @@ -73,7 +73,7 @@ jobs:
matrix:
dockerfile:
- docker/lightgbm-v3.2.1/windows_cpu_pip.dockerfile
- docker/lightgbm-v3.3.0/windows_cpu_pip.dockerfile
- docker/lightgbm-v3.3.3/windows_cpu_pip.dockerfile

steps:
- uses: actions/checkout@v2
Expand Down
8 changes: 4 additions & 4 deletions conf/experiments/benchmarks/lightgbm-inferencing.yaml
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Expand Up @@ -71,10 +71,10 @@ lightgbm_inferencing_config:

# list all inferencing frameworks and their builds
variants:
- framework: lightgbm_python # v3.3.0 via pypi
- framework: lightgbm_c_api # v3.3.0 with C API prediction
- framework: lightgbm_c_api # v3.3.0 with C API prediction
build: docker/lightgbm-custom/v330_patch_cpu_mpi_build.dockerfile
- framework: lightgbm_python # v3.3.3 via pypi
- framework: lightgbm_c_api # v3.3.3 with C API prediction
- framework: lightgbm_c_api # v3.3.3 with C API prediction
build: docker/lightgbm-custom/v333_patch_cpu_mpi_build.dockerfile
- framework: lightgbm_c_api # v3.2.1 with C API prediction
build: docker/lightgbm-v3.2.1/linux_cpu_mpi_build.dockerfile
- framework: lightgbm_c_api # v3.2.1 with C API prediction
Expand Down
8 changes: 4 additions & 4 deletions conf/experiments/lightgbm-inferencing.yaml
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Expand Up @@ -27,10 +27,10 @@ lightgbm_inferencing_config:

# list all inferencing frameworks and their builds
variants:
- framework: lightgbm_python # v3.3.0 via pypi
- framework: lightgbm_c_api # v3.3.0 with C API prediction
- framework: lightgbm_c_api # v3.3.0 with C API prediction
build: docker/lightgbm-custom/v330_patch_cpu_mpi_build.dockerfile
- framework: lightgbm_python # v3.3.3 via pypi
- framework: lightgbm_c_api # v3.3.3 with C API prediction
- framework: lightgbm_c_api # v3.3.3 with C API prediction
build: docker/lightgbm-custom/v333_patch_cpu_mpi_build.dockerfile
- framework: lightgbm_c_api # v3.2.1 with C API prediction
build: docker/lightgbm-v3.2.1/linux_cpu_mpi_build.dockerfile
- framework: lightgbm_c_api # v3.2.1 with C API prediction
Expand Down
2 changes: 1 addition & 1 deletion conf/experiments/lightgbm_training/cpu-custom.yaml
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Expand Up @@ -63,7 +63,7 @@ lightgbm_training_config:
#target: null # optional: force target for this training job
nodes: 1
processes: 1
build: "docker/lightgbm-custom/v330_patch_cpu_mpi_build.dockerfile" # relative to lightgbm_python folder
build: "docker/lightgbm-custom/v333_patch_cpu_mpi_build.dockerfile" # relative to lightgbm_python folder

# model registration
# naming convention: "{register_model_prefix}-{task_key}-{num_iterations}trees-{num_leaves}leaves-{register_model_suffix}"
Expand Down
2 changes: 1 addition & 1 deletion conf/experiments/lightgbm_training/gpu.yaml
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Expand Up @@ -63,7 +63,7 @@ lightgbm_training_config:
#target: null # optional: force target for this training job
nodes: 1
processes: 1
build: "docker/lightgbm-v3.3.0/linux_gpu_pip.dockerfile" # relative to lightgbm_python folder
build: "docker/lightgbm-v3.3.3/linux_gpu_pip.dockerfile" # relative to lightgbm_python folder

# model registration
# naming convention: "{register_model_prefix}-{task_key}-{num_iterations}trees-{num_leaves}leaves-{register_model_suffix}"
Expand Down
2 changes: 1 addition & 1 deletion conf/experiments/lightgbm_training/mpi.yaml
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Expand Up @@ -62,7 +62,7 @@ lightgbm_training_config:
# compute parameters
runtime:
#target: null # optional: force target for this training job
build: "docker/lightgbm-v3.3.0/linux_cpu_mpi_pip.dockerfile"
build: "docker/lightgbm-v3.3.3/linux_cpu_mpi_pip.dockerfile"
nodes: 2
processes: 1

Expand Down
22 changes: 11 additions & 11 deletions ...ustom/v330_patch_cpu_mpi_build.dockerfile → ...ustom/v333_patch_cpu_mpi_build.dockerfile
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@@ -1,10 +1,10 @@
FROM mcr.microsoft.com/azureml/openmpi3.1.2-ubuntu18.04:20210615.v1
LABEL lightgbmbenchmark.linux.cpu.mpi.build.version="3.3.0-patch/20211109.1"
LABEL lightgbmbenchmark.linux.cpu.mpi.build.version="3.3.3-patch/20221020.1"

# Those arguments will NOT be used by AzureML
# they are here just to allow for lightgbm-benchmark build to actually check
# dockerfiles in a PR against their actual branch
ARG lightgbm_version="3.3.0"
ARG lightgbm_version="3.3.3"
ARG lightgbm_benchmark_branch=main

RUN apt-get update && \
Expand Down Expand Up @@ -62,15 +62,15 @@ ENV PATH $AZUREML_CONDA_ENVIRONMENT_PATH/bin:$PATH
# Install pip dependencies
RUN HOROVOD_WITH_TENSORFLOW=1 \
pip install 'pandas>=1.1,<1.2' \
'numpy>=1.10,<1.20' \
'matplotlib==3.4.3' \
'scipy~=1.5.0' \
'scikit-learn~=0.24.1' \
'azureml-core==1.35.0' \
'azureml-defaults==1.35.0' \
'azureml-mlflow==1.35.0' \
'azureml-telemetry==1.35.0' \
'mpi4py==3.1.1'
'numpy>=1.10,<1.20' \
'matplotlib==3.4.3' \
'scipy~=1.5.0' \
'scikit-learn~=0.24.1' \
'azureml-core==1.35.0' \
'azureml-defaults==1.35.0' \
'azureml-mlflow==1.35.0' \
'azureml-telemetry==1.35.0' \
'mpi4py==3.1.1'

RUN pip install --upgrade pip setuptools wheel && \
pip install 'cmake==3.21.0'
Expand Down
22 changes: 11 additions & 11 deletions ...gbm-v3.3.0/linux_cpu_mpi_build.dockerfile → ...gbm-v3.3.3/linux_cpu_mpi_build.dockerfile
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@@ -1,10 +1,10 @@
FROM mcr.microsoft.com/azureml/openmpi3.1.2-ubuntu18.04:20211012.v1
LABEL lightgbmbenchmark.linux.cpu.mpi.build.version="3.3.0/20211115.1"
LABEL lightgbmbenchmark.linux.cpu.mpi.build.version="3.3.3/20221020.1"

# Those arguments will NOT be used by AzureML
# they are here just to allow for lightgbm-benchmark build to actually check
# dockerfiles in a PR against their actual branch
ARG lightgbm_version="3.3.0"
ARG lightgbm_version="3.3.3"
ARG lightgbm_benchmark_branch=main

RUN apt-get update && \
Expand Down Expand Up @@ -57,15 +57,15 @@ ENV PATH $AZUREML_CONDA_ENVIRONMENT_PATH/bin:$PATH
# Install pip dependencies
RUN HOROVOD_WITH_TENSORFLOW=1 \
pip install 'pandas>=1.1,<1.2' \
'numpy>=1.10,<1.20' \
'matplotlib==3.4.3' \
'scipy~=1.5.0' \
'scikit-learn~=0.24.1' \
'azureml-core==1.35.0' \
'azureml-defaults==1.35.0' \
'azureml-mlflow==1.35.0' \
'azureml-telemetry==1.35.0' \
'mpi4py==3.1.1'
'numpy>=1.10,<1.20' \
'matplotlib==3.4.3' \
'scipy~=1.5.0' \
'scikit-learn~=0.24.1' \
'azureml-core==1.35.0' \
'azureml-defaults==1.35.0' \
'azureml-mlflow==1.35.0' \
'azureml-telemetry==1.35.0' \
'mpi4py==3.1.1'

RUN pip install --upgrade pip setuptools wheel && \
pip install 'cmake==3.21.0'
Expand Down
22 changes: 11 additions & 11 deletions ...htgbm-v3.3.0/linux_cpu_mpi_pip.dockerfile → ...htgbm-v3.3.3/linux_cpu_mpi_pip.dockerfile
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@@ -1,10 +1,10 @@
FROM mcr.microsoft.com/azureml/openmpi4.1.0-ubuntu20.04:latest
LABEL lightgbmbenchmark.linux.cpu.mpi.pip.version="3.3.0/20220114.1"
LABEL lightgbmbenchmark.linux.cpu.mpi.pip.version="3.3.3/20221020.1"

# Those arguments will NOT be used by AzureML when building the image
# they are here just to allow for lightgbm-benchmark build to actually check
# dockerfiles in a PR against their actual branch
ARG lightgbm_version="3.3.0"
ARG lightgbm_version="3.3.3"

ENV AZUREML_CONDA_ENVIRONMENT_PATH /azureml-envs/lightgbm

Expand All @@ -18,15 +18,15 @@ ENV PATH $AZUREML_CONDA_ENVIRONMENT_PATH/bin:$PATH
# Install pip dependencies
RUN HOROVOD_WITH_TENSORFLOW=1 \
pip install 'pandas>=1.1,<1.2' \
'numpy>=1.10,<1.20' \
'matplotlib==3.4.3' \
'scipy~=1.5.0' \
'scikit-learn~=0.24.1' \
'azureml-core==1.35.0' \
'azureml-defaults==1.35.0' \
'azureml-mlflow==1.35.0' \
'azureml-telemetry==1.35.0' \
'mpi4py==3.1.1'
'numpy>=1.10,<1.20' \
'matplotlib==3.4.3' \
'scipy~=1.5.0' \
'scikit-learn~=0.24.1' \
'azureml-core==1.35.0' \
'azureml-defaults==1.35.0' \
'azureml-mlflow==1.35.0' \
'azureml-telemetry==1.35.0' \
'mpi4py==3.1.1'

# install lightgbm with mpi
RUN pip install --upgrade pip setuptools wheel && \
Expand Down
20 changes: 10 additions & 10 deletions ...ightgbm-v3.3.0/windows_cpu_pip.dockerfile → ...ightgbm-v3.3.3/windows_cpu_pip.dockerfile
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@@ -1,10 +1,10 @@
FROM mcr.microsoft.com/azureml/windows-servercore-1809:latest
LABEL lightgbmbenchmark.windows.cpu.mpi.pip.version="3.3.0/20211108.1"
LABEL lightgbmbenchmark.windows.cpu.mpi.pip.version="3.3.3/20221020.1"

# Those arguments will NOT be used by AzureML
# they are here just to allow for lightgbm-benchmark build to actually check
# dockerfiles in a PR against their actual branch
ARG lightgbm_version="3.3.0"
ARG lightgbm_version="3.3.3"

ENV AZUREML_CONDA_ENVIRONMENT_PATH /azureml-envs/lightgbm

Expand All @@ -17,11 +17,11 @@ RUN conda create -p $AZUREML_CONDA_ENVIRONMENT_PATH \

# Install pip dependencies
RUN pip install 'pandas>=1.1,<1.2' \
'numpy>=1.10,<1.20' \
'scipy~=1.5.0' \
'scikit-learn~=0.24.1' \
'azureml-core==1.35.0' \
'azureml-defaults==1.35.0' \
'azureml-mlflow==1.35.0' \
'azureml-telemetry==1.35.0' \
lightgbm==$($Env:lightgbm_version)
'numpy>=1.10,<1.20' \
'scipy~=1.5.0' \
'scikit-learn~=0.24.1' \
'azureml-core==1.35.0' \
'azureml-defaults==1.35.0' \
'azureml-mlflow==1.35.0' \
'azureml-telemetry==1.35.0' \
lightgbm==$($Env:lightgbm_version)
16 changes: 8 additions & 8 deletions docs/run/azureml/benchmark-inferencing.md
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Expand Up @@ -34,10 +34,10 @@ lightgbm_inferencing_config:

# list all inferencing frameworks and their builds
variants:
- framework: lightgbm_python # v3.3.0 via pypi
- framework: lightgbm_c_api # v3.3.0 with C API prediction
- framework: lightgbm_c_api # v3.3.0 with C API prediction
build: docker/lightgbm-custom/v330_patch_cpu_mpi_build.dockerfile
- framework: lightgbm_python # v3.3.3 via pypi
- framework: lightgbm_c_api # v3.3.3 with C API prediction
- framework: lightgbm_c_api # v3.3.3 with C API prediction
build: docker/lightgbm-custom/v333_patch_cpu_mpi_build.dockerfile
- framework: lightgbm_c_api # v3.2.1 with C API prediction
build: docker/lightgbm-v3.2.1/linux_cpu_mpi_build.dockerfile
- framework: lightgbm_c_api # v3.2.1 with C API prediction
Expand Down Expand Up @@ -88,10 +88,10 @@ For each task, the pipeline will run inferencing "variants", which are different
```yaml
# list all inferencing frameworks and their builds
variants:
- framework: lightgbm_python # v3.3.0 via pypi
- framework: lightgbm_c_api # v3.3.0 with C API prediction
- framework: lightgbm_c_api # v3.3.0 with C API prediction
build: docker/lightgbm-custom/v330_patch_cpu_mpi_build.dockerfile
- framework: lightgbm_python # v3.3.3 via pypi
- framework: lightgbm_c_api # v3.3.3 with C API prediction
- framework: lightgbm_c_api # v3.3.3 with C API prediction
build: docker/lightgbm-custom/v333_patch_cpu_mpi_build.dockerfile
- framework: lightgbm_c_api # v3.2.1 with C API prediction
build: docker/lightgbm-v3.2.1/linux_cpu_mpi_build.dockerfile
- framework: lightgbm_c_api # v3.2.1 with C API prediction
Expand Down
2 changes: 1 addition & 1 deletion docs/run/azureml/train-on-your-data.md
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Expand Up @@ -101,7 +101,7 @@ lightgbm_training_config:
training:
device_type: "gpu"
runtime:
build: "docker/lightgbm-v3.3.0/linux_gpu_pip.dockerfile"
build: "docker/lightgbm-v3.3.3/linux_gpu_pip.dockerfile"
```

When running the pipeline, it will automatically run on the gpu cluster you've named in your `compute/custom.yaml` file.
Expand Down
22 changes: 11 additions & 11 deletions src/scripts/inferencing/lightgbm_c_api/default.dockerfile
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@@ -1,10 +1,10 @@
FROM mcr.microsoft.com/azureml/openmpi3.1.2-ubuntu18.04:20211012.v1
LABEL lightgbmbenchmark.linux.cpu.mpi.build.version="3.3.0/20211115.1"
LABEL lightgbmbenchmark.linux.cpu.mpi.build.version="3.3.3/20221020.1"

# Those arguments will NOT be used by AzureML
# they are here just to allow for lightgbm-benchmark build to actually check
# dockerfiles in a PR against their actual branch
ARG lightgbm_version="3.3.0"
ARG lightgbm_version="3.3.3"
ARG lightgbm_benchmark_branch=main

RUN apt-get update && \
Expand Down Expand Up @@ -57,15 +57,15 @@ ENV PATH $AZUREML_CONDA_ENVIRONMENT_PATH/bin:$PATH
# Install pip dependencies
RUN HOROVOD_WITH_TENSORFLOW=1 \
pip install 'pandas>=1.1,<1.2' \
'numpy>=1.10,<1.20' \
'matplotlib==3.4.3' \
'scipy~=1.5.0' \
'scikit-learn~=0.24.1' \
'azureml-core==1.35.0' \
'azureml-defaults==1.35.0' \
'azureml-mlflow==1.35.0' \
'azureml-telemetry==1.35.0' \
'mpi4py==3.1.1'
'numpy>=1.10,<1.20' \
'matplotlib==3.4.3' \
'scipy~=1.5.0' \
'scikit-learn~=0.24.1' \
'azureml-core==1.35.0' \
'azureml-defaults==1.35.0' \
'azureml-mlflow==1.35.0' \
'azureml-telemetry==1.35.0' \
'mpi4py==3.1.1'

RUN pip install --upgrade pip setuptools wheel && \
pip install 'cmake==3.21.0'
Expand Down
32 changes: 32 additions & 0 deletions src/scripts/inferencing/lightgbm_ort/default.dockerfile
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@@ -0,0 +1,32 @@
FROM mcr.microsoft.com/azureml/openmpi4.1.0-ubuntu20.04:latest
LABEL lightgbmbenchmark.linux.cpu.ray.version="0.1.2/20220111.1"

ENV AZUREML_CONDA_ENVIRONMENT_PATH /azureml-envs/lightgbm

ARG lightgbm_version="3.3.3"

# Create conda environment
RUN conda create -p $AZUREML_CONDA_ENVIRONMENT_PATH \
python=3.8 pip=20.2.4

# Prepend path to AzureML conda environment
ENV PATH $AZUREML_CONDA_ENVIRONMENT_PATH/bin:$PATH

# Install pip dependencies
RUN pip install 'pandas>=1.1,<1.2' \
'numpy>=1.10,<1.20' \
'matplotlib==3.4.3' \
'scipy~=1.5.0' \
'scikit-learn~=0.24.1' \
'azureml-core==1.35.0' \
'azureml-defaults==1.35.0' \
'azureml-mlflow==1.35.0' \
'azureml-telemetry==1.35.0' \
'mpi4py==3.1.1' \
'onnxruntime==1.12.1' \
'onnxmltools==1.11.1' \
'onnxconverter-common==1.12.2'

# install lightgbm with mpi
RUN pip install lightgbm==${lightgbm_version} \
pip install 'protobuf==3.20'
22 changes: 11 additions & 11 deletions src/scripts/inferencing/lightgbm_python/default.dockerfile
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@@ -1,10 +1,10 @@
FROM mcr.microsoft.com/azureml/openmpi3.1.2-ubuntu18.04:20210615.v1
LABEL lightgbmbenchmark.linux.cpu.mpi.pip.version="3.3.0/20211210.1"
LABEL lightgbmbenchmark.linux.cpu.mpi.pip.version="3.3.3/20221020.1"

# Those arguments will NOT be used by AzureML
# they are here just to allow for lightgbm-benchmark build to actually check
# dockerfiles in a PR against their actual branch
ARG lightgbm_version="3.3.0"
ARG lightgbm_version="3.3.3"

ENV AZUREML_CONDA_ENVIRONMENT_PATH /azureml-envs/lightgbm

Expand All @@ -18,15 +18,15 @@ ENV PATH $AZUREML_CONDA_ENVIRONMENT_PATH/bin:$PATH
# Install pip dependencies
RUN HOROVOD_WITH_TENSORFLOW=1 \
pip install 'pandas>=1.1,<1.2' \
'numpy>=1.10,<1.20' \
'matplotlib==3.4.3' \
'scipy~=1.5.0' \
'scikit-learn~=0.24.1' \
'azureml-core==1.35.0' \
'azureml-defaults==1.35.0' \
'azureml-mlflow==1.35.0' \
'azureml-telemetry==1.35.0' \
'mpi4py==3.1.1'
'numpy>=1.10,<1.20' \
'matplotlib==3.4.3' \
'scipy~=1.5.0' \
'scikit-learn~=0.24.1' \
'azureml-core==1.35.0' \
'azureml-defaults==1.35.0' \
'azureml-mlflow==1.35.0' \
'azureml-telemetry==1.35.0' \
'mpi4py==3.1.1'

# install lightgbm with mpi
RUN pip install --upgrade pip setuptools wheel && \
Expand Down
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