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Update base for rebase, fix reciprocal on "Reapply "Implement unary_ufunc functions using elementwise_util (#9386)""
This PR was reverted due to internal test failures, which should be fixed now (and is being sent as an exported diff to make sure). Original summary: One less set of independent implementations to worry about going forward (e.g., we don't have to vectorize these separately from elementwise_util and they get all benefits of elementwise_util). Differential Revision: [D76754824](https://our.internmc.facebook.com/intern/diff/D76754824/) [ghstack-poisoned]
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.ci/docker/ci_commit_pins/pytorch.txt

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.ci/docker/common/install_conda.sh

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@@ -13,7 +13,7 @@ source "$(dirname "${BASH_SOURCE[0]}")/utils.sh"
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install_miniconda() {
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BASE_URL="https://repo.anaconda.com/miniconda"
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CONDA_FILE="Miniconda3-py${PYTHON_VERSION//./}_${MINICONDA_VERSION}-Linux-x86_64.sh"
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if [[ $(uname -m) == "aarch64" ]]; then
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if [[ $(uname -m) == "aarch64" ]]; then
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CONDA_FILE="Miniconda3-py${PYTHON_VERSION//./}_${MINICONDA_VERSION}-Linux-aarch64.sh"
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fi
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@@ -71,4 +71,8 @@ fix_conda_ubuntu_libstdcxx() {
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install_miniconda
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install_python
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install_pip_dependencies
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fix_conda_ubuntu_libstdcxx
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# Hack breaks the job on aarch64 but is still necessary everywhere
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# else.
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if [ "$(uname -m)" != "aarch64" ]; then
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fix_conda_ubuntu_libstdcxx
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fi

.ci/docker/conda-env-ci.txt

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cmake=3.26.4
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cmake=3.31.2
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ninja=1.10.2
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libuv
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llvm-openmp

.ci/scripts/benchmark_tooling/README.md

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##### Filtering Options:
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- `--device-pools`: Filter by private device pool names (e.g., "samsung-galaxy-s22-5g", "samsung-galaxy-s22plus-5g")
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- `--device-pools`: Filter by device pool names (e.g., "apple_iphone_15_private", "samsung_s22_private")
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- `--backends`: Filter by specific backend names (e.g.,"xnnpack_q8")
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- `--models`: Filter by specific model names (e.g., "mv3", "meta-llama-llama-3.2-1b-instruct-qlora-int4-eo8")
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- `--models`: Filter by specific model names (e.g., "mv3", "meta-llama/Llama-3.2-1B-Instruct-SpinQuant_INT4_EO8")
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#### Example Usage
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Filter by multiple private device pools and models:
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```bash
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# This fetches all private table data for models 'llama-3.2-1B' and 'mv3'
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python3 get_benchmark_analysis_data.py \
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python3 .ci/scripts/benchmark_tooling/get_benchmark_analysis_data.py \
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--startTime "2025-06-01T00:00:00" \
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--endTime "2025-06-11T00:00:00" \
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--device-pools 'apple_iphone_15_private' 'samsung_s22_private' \
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```bash
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# This fetches all private iPhone table data for models 'llama-3.2-1B' and 'mv3',
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# and associated public iPhone data
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python3 get_benchmark_analysis_data.py \
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python3 .ci/scripts/benchmark_tooling/get_benchmark_analysis_data.py \
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--startTime "2025-06-01T00:00:00" \
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--endTime "2025-06-11T00:00:00" \
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--device-pools 'apple_iphone_15_private' \
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end_time="2025-06-17T18:00:00"
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)
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# Get results in different formats
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# As DataFrames
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df_results = fetcher.to_df()
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# Export to Excel
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fetcher.to_excel(output_dir="./results")
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# Export to CSV
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fetcher.to_csv(output_dir="./results")
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# Export to JSON
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json_path = fetcher.to_json(output_dir="./results")
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# Get raw dictionary results
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dict_results = fetcher.to_dict()
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# Use the output_data method for flexible output
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results = fetcher.output_data(output_type="excel", output_dir="./results")
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```

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