Comments (11)
bvrabete
commented on July 30, 2024
2
For Workload : SpecCpu-2017 ERROR: failed to solve: failed to compute cache key: failed to calculate the checksum of ref 8f74b3ec-14bb-4b3f-bf4a-2415442bc78c::s1b8k8203tvipdcv00euqyggg: "/data": not found
As readme mentioned: need user manually create /data folder and export related binaries --> https://github.com/intel-innersource/applications.benchmarking.benchmark.external-platform-hero-features/blob/23.3_external/workload/SpecCpu-2017/README.mdSure, where can we find these binaries?
SpecCPU is a commercial benchmark so you need to purchase a license from https://spec.org/cpu2017/
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yikedeng
commented on July 30, 2024
1
For Workload : SpecCpu-2017 ERROR: failed to solve: failed to compute cache key: failed to calculate the checksum of ref 8f74b3ec-14bb-4b3f-bf4a-2415442bc78c::s1b8k8203tvipdcv00euqyggg: "/data": not found
As readme mentioned: need user manually create /data folder and export related binaries --> https://github.com/intel-innersource/applications.benchmarking.benchmark.external-platform-hero-features/blob/23.3_external/workload/SpecCpu-2017/README.mdSure, where can we find these binaries?
sure, I will share SpecCpu-2017 related intel internal binary url to you via email.
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xiuying1
commented on July 30, 2024
1
Can you provide information on Python-related errors for BERTLarge-PyTorch-Xeon-Public & ResNet50-PyTorch-Xeon-Public?
After contact Dev, PR: #46 for this issue
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yikedeng
commented on July 30, 2024
For Workload : SpecCpu-2017
ERROR: failed to solve: failed to compute cache key: failed to calculate the checksum of ref 8f74b3ec-14bb-4b3f-bf4a-2415442bc78c::s1b8k8203tvipdcv00euqyggg: "/data": not found
As readme mentioned: need user manually create /data folder and export related binaries --> https://github.com/intel-innersource/applications.benchmarking.benchmark.external-platform-hero-features/blob/23.3_external/workload/SpecCpu-2017/README.md
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dihu1007
commented on July 30, 2024
For Workloads: SmartScience-YOLO-MSTCN-OpenVINO, Video-Structure, 3DHuman-Pose-Estimation
These 3 WLs all need customers to refer to the steps mentioned in readme to add some necessary files before make, hope these can solve the problem you mentioned.
SmartScience-YOLO-MSTCN-OpenVINO:
https://github.com/intel/workload-services-framework/blob/main/workload/SmartScience-YOLO-MSTCN-OpenVINO/README.md#preparation
Video-Structure:
https://github.com/intel/workload-services-framework/blob/main/workload/Video-Structure/README.md#preparation
3DHuman-Pose-Estimation:
https://github.com/intel/workload-services-framework/blob/main/stack/3DHuman-Pose/README.md#usage
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saiprasanna7
commented on July 30, 2024
For Workload : SpecCpu-2017 ERROR: failed to solve: failed to compute cache key: failed to calculate the checksum of ref 8f74b3ec-14bb-4b3f-bf4a-2415442bc78c::s1b8k8203tvipdcv00euqyggg: "/data": not found
As readme mentioned: need user manually create /data folder and export related binaries --> https://github.com/intel-innersource/applications.benchmarking.benchmark.external-platform-hero-features/blob/23.3_external/workload/SpecCpu-2017/README.md
Sure, where can we find these binaries?
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saiprasanna7
commented on July 30, 2024
For Workloads: SmartScience-YOLO-MSTCN-OpenVINO, Video-Structure, 3DHuman-Pose-Estimation These 3 WLs all need customers to refer to the steps mentioned in readme to add some necessary files before make, hope these can solve the problem you mentioned. SmartScience-YOLO-MSTCN-OpenVINO: https://github.com/intel/workload-services-framework/blob/main/workload/SmartScience-YOLO-MSTCN-OpenVINO/README.md#preparation Video-Structure: https://github.com/intel/workload-services-framework/blob/main/workload/Video-Structure/README.md#preparation 3DHuman-Pose-Estimation: https://github.com/intel/workload-services-framework/blob/main/stack/3DHuman-Pose/README.md#usage
Can you provide information on how can we get these files in order to build the docker image?
I see there are files attached in README.md for 3D-Human-Pose-Estimation, but not for other workloads.
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saiprasanna7
commented on July 30, 2024
Can you provide information on Python-related errors for BERTLarge-PyTorch-Xeon-Public & ResNet50-PyTorch-Xeon-Public?
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saiprasanna7
commented on July 30, 2024
Can you provide information on Python-related errors for BERTLarge-PyTorch-Xeon-Public & ResNet50-PyTorch-Xeon-Public?
After contact Dev, PR: #46 for this issue
Tried building with this patch, the BERTLarge workload is failing with following errors:
#18 27.78 Requirement already satisfied: joblib in /root/anaconda3/lib/python3.10/site-packages (from sacremoses->transformers==3.0.2) (1.2.0)
#18 27.84 Building wheels for collected packages: tokenizers, sacremoses
#18 27.84 Building wheel for tokenizers (pyproject.toml): started
#18 28.27 Building wheel for tokenizers (pyproject.toml): finished with status 'error'
#18 28.28 error: subprocess-exited-with-error
#18 28.28
#18 28.28 × Building wheel for tokenizers (pyproject.toml) did not run successfully.
#18 28.28 │ exit code: 1
#18 28.28 ╰─> [48 lines of output]
#18 28.28 /tmp/pip-build-env-_l68llis/overlay/lib/python3.10/site-packages/setuptools/dist.py:314: InformationOnly: Normalizing '0.8.1.rc1' to '0.8.1rc1'
#18 28.28 self.metadata.version = self._normalize_version(
#18 28.28 running bdist_wheel
#18 28.28 running build
#18 28.28 running build_py
#18 28.28 creating build
#18 28.28 creating build/lib.linux-x86_64-cpython-310
#18 28.28 creating build/lib.linux-x86_64-cpython-310/tokenizers
#18 28.28 copying tokenizers/__init__.py -> build/lib.linux-x86_64-cpython-310/tokenizers
#18 28.28 creating build/lib.linux-x86_64-cpython-310/tokenizers/models
#18 28.28 copying tokenizers/models/__init__.py -> build/lib.linux-x86_64-cpython-310/tokenizers/models
#18 28.28 creating build/lib.linux-x86_64-cpython-310/tokenizers/decoders
#18 28.28 copying tokenizers/decoders/__init__.py -> build/lib.linux-x86_64-cpython-310/tokenizers/decoders
#18 28.28 creating build/lib.linux-x86_64-cpython-310/tokenizers/normalizers
#18 28.28 copying tokenizers/normalizers/__init__.py -> build/lib.linux-x86_64-cpython-310/tokenizers/normalizers
#18 28.28 creating build/lib.linux-x86_64-cpython-310/tokenizers/pre_tokenizers
#18 28.28 copying tokenizers/pre_tokenizers/__init__.py -> build/lib.linux-x86_64-cpython-310/tokenizers/pre_tokenizers
#18 28.28 creating build/lib.linux-x86_64-cpython-310/tokenizers/processors
#18 28.28 copying tokenizers/processors/__init__.py -> build/lib.linux-x86_64-cpython-310/tokenizers/processors
#18 28.28 creating build/lib.linux-x86_64-cpython-310/tokenizers/trainers
#18 28.28 copying tokenizers/trainers/__init__.py -> build/lib.linux-x86_64-cpython-310/tokenizers/trainers
#18 28.28 creating build/lib.linux-x86_64-cpython-310/tokenizers/implementations
#18 28.28 copying tokenizers/implementations/__init__.py -> build/lib.linux-x86_64-cpython-310/tokenizers/implementations
#18 28.28 copying tokenizers/implementations/base_tokenizer.py -> build/lib.linux-x86_64-cpython-310/tokenizers/implementations
#18 28.28 copying tokenizers/implementations/bert_wordpiece.py -> build/lib.linux-x86_64-cpython-310/tokenizers/implementations
#18 28.28 copying tokenizers/implementations/char_level_bpe.py -> build/lib.linux-x86_64-cpython-310/tokenizers/implementations
#18 28.28 copying tokenizers/implementations/sentencepiece_bpe.py -> build/lib.linux-x86_64-cpython-310/tokenizers/implementations
#18 28.28 copying tokenizers/implementations/byte_level_bpe.py -> build/lib.linux-x86_64-cpython-310/tokenizers/implementations
#18 28.28 copying tokenizers/__init__.pyi -> build/lib.linux-x86_64-cpython-310/tokenizers
#18 28.28 copying tokenizers/models/__init__.pyi -> build/lib.linux-x86_64-cpython-310/tokenizers/models
#18 28.28 copying tokenizers/decoders/__init__.pyi -> build/lib.linux-x86_64-cpython-310/tokenizers/decoders
#18 28.28 copying tokenizers/normalizers/__init__.pyi -> build/lib.linux-x86_64-cpython-310/tokenizers/normalizers
#18 28.28 copying tokenizers/pre_tokenizers/__init__.pyi -> build/lib.linux-x86_64-cpython-310/tokenizers/pre_tokenizers
#18 28.28 copying tokenizers/processors/__init__.pyi -> build/lib.linux-x86_64-cpython-310/tokenizers/processors
#18 28.28 copying tokenizers/trainers/__init__.pyi -> build/lib.linux-x86_64-cpython-310/tokenizers/trainers
#18 28.28 running build_ext
#18 28.28 running build_rust
#18 28.28 error: can't find Rust compiler
#18 28.28
#18 28.28 If you are using an outdated pip version, it is possible a prebuilt wheel is available for this package but pip is not able to install from it. Installing from the wheel would avoid the need for a Rust compiler.
#18 28.28
#18 28.28 To update pip, run:
#18 28.28
#18 28.28 pip install --upgrade pip
#18 28.28
#18 28.28 and then retry package installation.
#18 28.28
#18 28.28 If you did intend to build this package from source, try installing a Rust compiler from your system package manager and ensure it is on the PATH during installation. Alternatively, rustup (available at https://rustup.rs) is the recommended way to download and update the Rust compiler toolchain.
#18 28.28 [end of output]
#18 28.28
#18 28.28 note: This error originates from a subprocess, and is likely not a problem with pip.
#18 28.29 ERROR: Failed building wheel for tokenizers
#18 28.29 Building wheel for sacremoses (setup.py): started
#18 29.37 Building wheel for sacremoses (setup.py): finished with status 'done'
#18 29.38 Created wheel for sacremoses: filename=sacremoses-0.0.53-py3-none-any.whl size=895241 sha256=a58105eaac7a12184a43fc033ef7a7510230af243983494f6ad41d52989c879d
#18 29.38 Stored in directory: /root/.cache/pip/wheels/00/24/97/a2ea5324f36bc626e1ea0267f33db6aa80d157ee977e9e42fb
#18 29.39 Successfully built sacremoses
#18 29.39 Failed to build tokenizers
#18 29.39 ERROR: Could not build wheels for tokenizers, which is required to install pyproject.toml-based projects
#18 29.39
#18 29.39 [notice] A new release of pip is available: 23.1.1 -> 23.3
#18 29.39 [notice] To update, run: pip install --upgrade pip
------
process "/bin/bash -c source activate base && cd quickstart/language_modeling/pytorch/bert_large/inference/cpu && git clone https://github.com/huggingface/transformers.git && cd transformers && git checkout v3.0.2 && git apply ../enable_ipex_for_squad.diff && pip install -e ./ && pip install tensorboard tensorboardX" did not complete successfully: exit code: 1
workload/BERTLarge-PyTorch-Xeon-Public/CMakeFiles/build_bertlarge-pytorch-xeon-public.dir/build.make:57: recipe for target 'workload/BERTLarge-PyTorch-Xeon-Public/CMakeFiles/build_bertlarge-pytorch-xeon-public' failed
make[2]: *** [workload/BERTLarge-PyTorch-Xeon-Public/CMakeFiles/build_bertlarge-pytorch-xeon-public] Error 1
CMakeFiles/Makefile2:985: recipe for target 'workload/BERTLarge-PyTorch-Xeon-Public/CMakeFiles/build_bertlarge-pytorch-xeon-public.dir/all' failed
make[1]: *** [workload/BERTLarge-PyTorch-Xeon-Public/CMakeFiles/build_bertlarge-pytorch-xeon-public.dir/all] Error 2
Makefile:94: recipe for target 'all' failed
make: *** [all] Error 2
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saiprasanna7
commented on July 30, 2024
Can you provide information on Python-related errors for BERTLarge-PyTorch-Xeon-Public & ResNet50-PyTorch-Xeon-Public?
After contact Dev, PR: #46 for this issue
Tried building with this patch, the BERTLarge workload is failing with following errors:
#18 27.78 Requirement already satisfied: joblib in /root/anaconda3/lib/python3.10/site-packages (from sacremoses->transformers==3.0.2) (1.2.0) #18 27.84 Building wheels for collected packages: tokenizers, sacremoses #18 27.84 Building wheel for tokenizers (pyproject.toml): started #18 28.27 Building wheel for tokenizers (pyproject.toml): finished with status 'error' #18 28.28 error: subprocess-exited-with-error #18 28.28 #18 28.28 × Building wheel for tokenizers (pyproject.toml) did not run successfully. #18 28.28 │ exit code: 1 #18 28.28 ╰─> [48 lines of output] #18 28.28 /tmp/pip-build-env-_l68llis/overlay/lib/python3.10/site-packages/setuptools/dist.py:314: InformationOnly: Normalizing '0.8.1.rc1' to '0.8.1rc1' #18 28.28 self.metadata.version = self._normalize_version( #18 28.28 running bdist_wheel #18 28.28 running build #18 28.28 running build_py #18 28.28 creating build #18 28.28 creating build/lib.linux-x86_64-cpython-310 #18 28.28 creating build/lib.linux-x86_64-cpython-310/tokenizers #18 28.28 copying tokenizers/__init__.py -> build/lib.linux-x86_64-cpython-310/tokenizers #18 28.28 creating build/lib.linux-x86_64-cpython-310/tokenizers/models #18 28.28 copying tokenizers/models/__init__.py -> build/lib.linux-x86_64-cpython-310/tokenizers/models #18 28.28 creating build/lib.linux-x86_64-cpython-310/tokenizers/decoders #18 28.28 copying tokenizers/decoders/__init__.py -> build/lib.linux-x86_64-cpython-310/tokenizers/decoders #18 28.28 creating build/lib.linux-x86_64-cpython-310/tokenizers/normalizers #18 28.28 copying tokenizers/normalizers/__init__.py -> build/lib.linux-x86_64-cpython-310/tokenizers/normalizers #18 28.28 creating build/lib.linux-x86_64-cpython-310/tokenizers/pre_tokenizers #18 28.28 copying tokenizers/pre_tokenizers/__init__.py -> build/lib.linux-x86_64-cpython-310/tokenizers/pre_tokenizers #18 28.28 creating build/lib.linux-x86_64-cpython-310/tokenizers/processors #18 28.28 copying tokenizers/processors/__init__.py -> build/lib.linux-x86_64-cpython-310/tokenizers/processors #18 28.28 creating build/lib.linux-x86_64-cpython-310/tokenizers/trainers #18 28.28 copying tokenizers/trainers/__init__.py -> build/lib.linux-x86_64-cpython-310/tokenizers/trainers #18 28.28 creating build/lib.linux-x86_64-cpython-310/tokenizers/implementations #18 28.28 copying tokenizers/implementations/__init__.py -> build/lib.linux-x86_64-cpython-310/tokenizers/implementations #18 28.28 copying tokenizers/implementations/base_tokenizer.py -> build/lib.linux-x86_64-cpython-310/tokenizers/implementations #18 28.28 copying tokenizers/implementations/bert_wordpiece.py -> build/lib.linux-x86_64-cpython-310/tokenizers/implementations #18 28.28 copying tokenizers/implementations/char_level_bpe.py -> build/lib.linux-x86_64-cpython-310/tokenizers/implementations #18 28.28 copying tokenizers/implementations/sentencepiece_bpe.py -> build/lib.linux-x86_64-cpython-310/tokenizers/implementations #18 28.28 copying tokenizers/implementations/byte_level_bpe.py -> build/lib.linux-x86_64-cpython-310/tokenizers/implementations #18 28.28 copying tokenizers/__init__.pyi -> build/lib.linux-x86_64-cpython-310/tokenizers #18 28.28 copying tokenizers/models/__init__.pyi -> build/lib.linux-x86_64-cpython-310/tokenizers/models #18 28.28 copying tokenizers/decoders/__init__.pyi -> build/lib.linux-x86_64-cpython-310/tokenizers/decoders #18 28.28 copying tokenizers/normalizers/__init__.pyi -> build/lib.linux-x86_64-cpython-310/tokenizers/normalizers #18 28.28 copying tokenizers/pre_tokenizers/__init__.pyi -> build/lib.linux-x86_64-cpython-310/tokenizers/pre_tokenizers #18 28.28 copying tokenizers/processors/__init__.pyi -> build/lib.linux-x86_64-cpython-310/tokenizers/processors #18 28.28 copying tokenizers/trainers/__init__.pyi -> build/lib.linux-x86_64-cpython-310/tokenizers/trainers #18 28.28 running build_ext #18 28.28 running build_rust #18 28.28 error: can't find Rust compiler #18 28.28 #18 28.28 If you are using an outdated pip version, it is possible a prebuilt wheel is available for this package but pip is not able to install from it. Installing from the wheel would avoid the need for a Rust compiler. #18 28.28 #18 28.28 To update pip, run: #18 28.28 #18 28.28 pip install --upgrade pip #18 28.28 #18 28.28 and then retry package installation. #18 28.28 #18 28.28 If you did intend to build this package from source, try installing a Rust compiler from your system package manager and ensure it is on the PATH during installation. Alternatively, rustup (available at https://rustup.rs) is the recommended way to download and update the Rust compiler toolchain. #18 28.28 [end of output] #18 28.28 #18 28.28 note: This error originates from a subprocess, and is likely not a problem with pip. #18 28.29 ERROR: Failed building wheel for tokenizers #18 28.29 Building wheel for sacremoses (setup.py): started #18 29.37 Building wheel for sacremoses (setup.py): finished with status 'done' #18 29.38 Created wheel for sacremoses: filename=sacremoses-0.0.53-py3-none-any.whl size=895241 sha256=a58105eaac7a12184a43fc033ef7a7510230af243983494f6ad41d52989c879d #18 29.38 Stored in directory: /root/.cache/pip/wheels/00/24/97/a2ea5324f36bc626e1ea0267f33db6aa80d157ee977e9e42fb #18 29.39 Successfully built sacremoses #18 29.39 Failed to build tokenizers #18 29.39 ERROR: Could not build wheels for tokenizers, which is required to install pyproject.toml-based projects #18 29.39 #18 29.39 [notice] A new release of pip is available: 23.1.1 -> 23.3 #18 29.39 [notice] To update, run: pip install --upgrade pip ------ process "/bin/bash -c source activate base && cd quickstart/language_modeling/pytorch/bert_large/inference/cpu && git clone https://github.com/huggingface/transformers.git && cd transformers && git checkout v3.0.2 && git apply ../enable_ipex_for_squad.diff && pip install -e ./ && pip install tensorboard tensorboardX" did not complete successfully: exit code: 1 workload/BERTLarge-PyTorch-Xeon-Public/CMakeFiles/build_bertlarge-pytorch-xeon-public.dir/build.make:57: recipe for target 'workload/BERTLarge-PyTorch-Xeon-Public/CMakeFiles/build_bertlarge-pytorch-xeon-public' failed make[2]: *** [workload/BERTLarge-PyTorch-Xeon-Public/CMakeFiles/build_bertlarge-pytorch-xeon-public] Error 1 CMakeFiles/Makefile2:985: recipe for target 'workload/BERTLarge-PyTorch-Xeon-Public/CMakeFiles/build_bertlarge-pytorch-xeon-public.dir/all' failed make[1]: *** [workload/BERTLarge-PyTorch-Xeon-Public/CMakeFiles/build_bertlarge-pytorch-xeon-public.dir/all] Error 2 Makefile:94: recipe for target 'all' failed make: *** [all] Error 2
Tried upgrading the pip to 23.3 but still fails with the same error
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ziyizhang-1
commented on July 30, 2024
Can you provide information on Python-related errors for BERTLarge-PyTorch-Xeon-Public & ResNet50-PyTorch-Xeon-Public?
After contact Dev, PR: #46 for this issue
Tried building with this patch, the BERTLarge workload is failing with following errors:
#18 27.78 Requirement already satisfied: joblib in /root/anaconda3/lib/python3.10/site-packages (from sacremoses->transformers==3.0.2) (1.2.0) #18 27.84 Building wheels for collected packages: tokenizers, sacremoses #18 27.84 Building wheel for tokenizers (pyproject.toml): started #18 28.27 Building wheel for tokenizers (pyproject.toml): finished with status 'error' #18 28.28 error: subprocess-exited-with-error #18 28.28 #18 28.28 × Building wheel for tokenizers (pyproject.toml) did not run successfully. #18 28.28 │ exit code: 1 #18 28.28 ╰─> [48 lines of output] #18 28.28 /tmp/pip-build-env-_l68llis/overlay/lib/python3.10/site-packages/setuptools/dist.py:314: InformationOnly: Normalizing '0.8.1.rc1' to '0.8.1rc1' #18 28.28 self.metadata.version = self._normalize_version( #18 28.28 running bdist_wheel #18 28.28 running build #18 28.28 running build_py #18 28.28 creating build #18 28.28 creating build/lib.linux-x86_64-cpython-310 #18 28.28 creating build/lib.linux-x86_64-cpython-310/tokenizers #18 28.28 copying tokenizers/__init__.py -> build/lib.linux-x86_64-cpython-310/tokenizers #18 28.28 creating build/lib.linux-x86_64-cpython-310/tokenizers/models #18 28.28 copying tokenizers/models/__init__.py -> build/lib.linux-x86_64-cpython-310/tokenizers/models #18 28.28 creating build/lib.linux-x86_64-cpython-310/tokenizers/decoders #18 28.28 copying tokenizers/decoders/__init__.py -> build/lib.linux-x86_64-cpython-310/tokenizers/decoders #18 28.28 creating build/lib.linux-x86_64-cpython-310/tokenizers/normalizers #18 28.28 copying tokenizers/normalizers/__init__.py -> build/lib.linux-x86_64-cpython-310/tokenizers/normalizers #18 28.28 creating build/lib.linux-x86_64-cpython-310/tokenizers/pre_tokenizers #18 28.28 copying tokenizers/pre_tokenizers/__init__.py -> build/lib.linux-x86_64-cpython-310/tokenizers/pre_tokenizers #18 28.28 creating build/lib.linux-x86_64-cpython-310/tokenizers/processors #18 28.28 copying tokenizers/processors/__init__.py -> build/lib.linux-x86_64-cpython-310/tokenizers/processors #18 28.28 creating build/lib.linux-x86_64-cpython-310/tokenizers/trainers #18 28.28 copying tokenizers/trainers/__init__.py -> build/lib.linux-x86_64-cpython-310/tokenizers/trainers #18 28.28 creating build/lib.linux-x86_64-cpython-310/tokenizers/implementations #18 28.28 copying tokenizers/implementations/__init__.py -> build/lib.linux-x86_64-cpython-310/tokenizers/implementations #18 28.28 copying tokenizers/implementations/base_tokenizer.py -> build/lib.linux-x86_64-cpython-310/tokenizers/implementations #18 28.28 copying tokenizers/implementations/bert_wordpiece.py -> build/lib.linux-x86_64-cpython-310/tokenizers/implementations #18 28.28 copying tokenizers/implementations/char_level_bpe.py -> build/lib.linux-x86_64-cpython-310/tokenizers/implementations #18 28.28 copying tokenizers/implementations/sentencepiece_bpe.py -> build/lib.linux-x86_64-cpython-310/tokenizers/implementations #18 28.28 copying tokenizers/implementations/byte_level_bpe.py -> build/lib.linux-x86_64-cpython-310/tokenizers/implementations #18 28.28 copying tokenizers/__init__.pyi -> build/lib.linux-x86_64-cpython-310/tokenizers #18 28.28 copying tokenizers/models/__init__.pyi -> build/lib.linux-x86_64-cpython-310/tokenizers/models #18 28.28 copying tokenizers/decoders/__init__.pyi -> build/lib.linux-x86_64-cpython-310/tokenizers/decoders #18 28.28 copying tokenizers/normalizers/__init__.pyi -> build/lib.linux-x86_64-cpython-310/tokenizers/normalizers #18 28.28 copying tokenizers/pre_tokenizers/__init__.pyi -> build/lib.linux-x86_64-cpython-310/tokenizers/pre_tokenizers #18 28.28 copying tokenizers/processors/__init__.pyi -> build/lib.linux-x86_64-cpython-310/tokenizers/processors #18 28.28 copying tokenizers/trainers/__init__.pyi -> build/lib.linux-x86_64-cpython-310/tokenizers/trainers #18 28.28 running build_ext #18 28.28 running build_rust #18 28.28 error: can't find Rust compiler #18 28.28 #18 28.28 If you are using an outdated pip version, it is possible a prebuilt wheel is available for this package but pip is not able to install from it. Installing from the wheel would avoid the need for a Rust compiler. #18 28.28 #18 28.28 To update pip, run: #18 28.28 #18 28.28 pip install --upgrade pip #18 28.28 #18 28.28 and then retry package installation. #18 28.28 #18 28.28 If you did intend to build this package from source, try installing a Rust compiler from your system package manager and ensure it is on the PATH during installation. Alternatively, rustup (available at https://rustup.rs) is the recommended way to download and update the Rust compiler toolchain. #18 28.28 [end of output] #18 28.28 #18 28.28 note: This error originates from a subprocess, and is likely not a problem with pip. #18 28.29 ERROR: Failed building wheel for tokenizers #18 28.29 Building wheel for sacremoses (setup.py): started #18 29.37 Building wheel for sacremoses (setup.py): finished with status 'done' #18 29.38 Created wheel for sacremoses: filename=sacremoses-0.0.53-py3-none-any.whl size=895241 sha256=a58105eaac7a12184a43fc033ef7a7510230af243983494f6ad41d52989c879d #18 29.38 Stored in directory: /root/.cache/pip/wheels/00/24/97/a2ea5324f36bc626e1ea0267f33db6aa80d157ee977e9e42fb #18 29.39 Successfully built sacremoses #18 29.39 Failed to build tokenizers #18 29.39 ERROR: Could not build wheels for tokenizers, which is required to install pyproject.toml-based projects #18 29.39 #18 29.39 [notice] A new release of pip is available: 23.1.1 -> 23.3 #18 29.39 [notice] To update, run: pip install --upgrade pip ------ process "/bin/bash -c source activate base && cd quickstart/language_modeling/pytorch/bert_large/inference/cpu && git clone https://github.com/huggingface/transformers.git && cd transformers && git checkout v3.0.2 && git apply ../enable_ipex_for_squad.diff && pip install -e ./ && pip install tensorboard tensorboardX" did not complete successfully: exit code: 1 workload/BERTLarge-PyTorch-Xeon-Public/CMakeFiles/build_bertlarge-pytorch-xeon-public.dir/build.make:57: recipe for target 'workload/BERTLarge-PyTorch-Xeon-Public/CMakeFiles/build_bertlarge-pytorch-xeon-public' failed make[2]: *** [workload/BERTLarge-PyTorch-Xeon-Public/CMakeFiles/build_bertlarge-pytorch-xeon-public] Error 1 CMakeFiles/Makefile2:985: recipe for target 'workload/BERTLarge-PyTorch-Xeon-Public/CMakeFiles/build_bertlarge-pytorch-xeon-public.dir/all' failed make[1]: *** [workload/BERTLarge-PyTorch-Xeon-Public/CMakeFiles/build_bertlarge-pytorch-xeon-public.dir/all] Error 2 Makefile:94: recipe for target 'all' failed make: *** [all] Error 2Tried upgrading the pip to 23.3 but still fails with the same error
Since you have upgraded the PyTorch base stack. you also need to bump the transformer version and benchmark code version as well.
Consider:
- Switch intel modelzoo (in Dockerfile.2.benchmark) from
spr-launch-publictopytorch-r2.0-models - Change commit ID to
168256a - Switch
transformerfromv3.0.2tov4.18.0and also theEVAL_SCRIPT(in Dockerfile.1.inference)
Those change had already made in the innersource, please refer to PR8275 and PR8417
from workload-services-framework.
Related Issues (6)
- Lost the image for SGX-setup readme
- Running WSF External Workloads on a Kubernetes Pod without using terraform docker image HOT 2
- Docker image build failed for PyTorch-Xeon
- OpenSSL3-RSAMB kubernetes-config.yaml CONFIG is always set to "qat-rsa"
- Docker Image Name Inconsistency Between Make Build and Kubernetes Config for v23.3 Release HOT 2
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