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.buckconfig

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**/.git, \
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cmake-out, \
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pip-out
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[buck2]
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restarter=true

.ci/scripts/setup-linux.sh

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# of nightly. This allows CI to test against latest commits from PyTorch
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install_executorch "use-pt-pinned-commit"
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build_executorch_runner "${BUILD_TOOL}"
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do_not_use_nightly_on_ci
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if [[ "${GITHUB_BASE_REF:-}" == *main* || "${GITHUB_BASE_REF:-}" == *gh* ]]; then
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do_not_use_nightly_on_ci
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fi

.ci/scripts/setup-macos.sh

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# the pinned commit from PyTorch
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install_executorch "use-pt-pinned-commit"
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build_executorch_runner "${BUILD_TOOL}"
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do_not_use_nightly_on_ci
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if [[ "${GITHUB_BASE_REF:-}" == *main* || "${GITHUB_BASE_REF:-}" == *gh* ]]; then
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do_not_use_nightly_on_ci
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fi

.github/workflows/pull.yml

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PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
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# install pybind
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bash install_executorch.sh --pybind xnnpack --use-pt-pinned-commit
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# install Llava requirements
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bash examples/models/llama/install_requirements.sh
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bash examples/models/llava/install_requirements.sh
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PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
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# install pybind
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bash install_executorch.sh --pybind xnnpack --use-pt-pinned-commit
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# install phi-3-mini requirements
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bash examples/models/phi-3-mini/install_requirements.sh
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PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
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# install pybind
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bash install_executorch.sh --pybind xnnpack --use-pt-pinned-commit
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# install llama requirements
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bash examples/models/llama/install_requirements.sh
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PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
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# install pybind
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bash install_executorch.sh --pybind xnnpack --use-pt-pinned-commit
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# install llama requirements
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bash examples/models/llama/install_requirements.sh
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PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
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# install pybind
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bash install_executorch.sh --pybind xnnpack --use-pt-pinned-commit
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# install llama requirements
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bash examples/models/llama/install_requirements.sh
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.gitmodules

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[submodule "third-party/ao"]
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path = third-party/ao
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url = https://github.com/pytorch/ao.git
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[submodule "backends/cadence/utils/FACTO"]
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path = backends/cadence/utils/FACTO
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url = https://github.com/pytorch-labs/FACTO.git

backends/arm/_passes/annotate_decomposed_matmul.py

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# This source code is licensed under the BSD-style license found in the
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# LICENSE file in the root directory of this source tree.
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# pyre-unsafe
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import itertools
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from typing import List

backends/arm/_passes/arm_pass_manager.py

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self.add_pass(FuseQuantizedActivationPass())
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self.add_pass(RemoveGetItemPass())
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self.add_pass(ConvertSplitToSlicePass())
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self.add_pass(FuseBatchnorm2DPass(exported_program))
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self.add_pass(ConvertMmToBmmPass())
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self.add_pass(DecomposeLinearPass())
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self.add_pass(DecomposeBatchNormPass())
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self.add_pass(ConvertMeanDimToAveragePoolPass())
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self.add_pass(DecomposeDivPass())
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self.add_pass(DecomposeSoftmaxesPass())
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self.add_pass(FuseBatchnorm2DPass(exported_program))
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self.add_pass(AnnotateDecomposedMatmulPass())
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self.add_pass(QuantizeOperatorArguments())

backends/arm/_passes/fold_qdq_with_annotated_qparams_pass.py

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# This source code is licensed under the BSD-style license found in the
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# LICENSE file in the root directory of this source tree.
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# pyre-unsafe
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import copy
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from typing import cast, Dict, Set, Tuple

backends/arm/_passes/fuse_batchnorm2d_pass.py

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# This source code is licensed under the BSD-style license found in the
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# LICENSE file in the root directory of this source tree.
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# pyre-unsafe
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import torch
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from executorch.exir import ExportedProgram
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from executorch.exir.dialects._ops import ops as exir_ops

backends/arm/_passes/fuse_quantized_activation_pass.py

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# This source code is licensed under the BSD-style license found in the
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# LICENSE file in the root directory of this source tree.
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# pyre-unsafe
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import torch
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from executorch.backends.arm.tosa_quant_utils import q_op
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from executorch.exir.dialects._ops import ops as exir_ops

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