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Bump PyTorch pin to 2.13
1 parent e500fee commit 0174fd5

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Lines changed: 10 additions & 10 deletions

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Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -1 +1 @@
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release/2.12
1+
release/2.13

.ci/docker/common/install_pytorch.sh

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@@ -40,7 +40,7 @@ install_pytorch_and_domains() {
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# Grab the pinned audio and vision commits from PyTorch
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TORCHAUDIO_VERSION=release/2.11
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export TORCHAUDIO_VERSION
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TORCHVISION_VERSION=release/0.27
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TORCHVISION_VERSION=release/0.28
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export TORCHVISION_VERSION
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install_domains

.ci/scripts/utils.sh

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@@ -107,7 +107,7 @@ install_pytorch_and_domains() {
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local torch_release=$(cat version.txt)
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# Download key must match the upload key below (basename of dist/*.whl,
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# which always carries setup.py's resolved +gitHASH). Branch-ref pins
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# like `release/2.12` would otherwise produce `+gitrelease` here and
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# like `release/2.13` would otherwise produce `+gitrelease` here and
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# never hit the cache.
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local torch_short_hash=$(git rev-parse --short=7 HEAD)
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local torch_wheel_path="cached_artifacts/pytorch/executorch/pytorch_wheels/${system_name}/${python_version}"
@@ -178,7 +178,7 @@ install_pytorch_and_domains() {
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# Grab the pinned audio and vision commits from PyTorch
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TORCHAUDIO_VERSION=release/2.11
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export TORCHAUDIO_VERSION
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TORCHVISION_VERSION=release/0.27
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TORCHVISION_VERSION=release/0.28
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export TORCHVISION_VERSION
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install_domains

install_requirements.py

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@@ -49,7 +49,7 @@ def install_requirements(use_pytorch_nightly):
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# Setting use_pytorch_nightly to false to test the pinned PyTorch commit. Note
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# that we don't need to set any version number there because they have already
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# been installed on CI before this step, so pip won't reinstall them
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("torch==2.12.0" if use_pytorch_nightly else "torch"),
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("torch==2.13.0" if use_pytorch_nightly else "torch"),
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]
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# Install the requirements for core ExecuTorch package.
@@ -112,7 +112,7 @@ def install_optional_example_requirements(use_pytorch_nightly):
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print("Installing torch domain libraries")
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DOMAIN_LIBRARIES = [
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("torchvision==0.27.0" if use_pytorch_nightly else "torchvision"),
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("torchvision==0.28.0" if use_pytorch_nightly else "torchvision"),
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("torchaudio==2.11.0" if use_pytorch_nightly else "torchaudio"),
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]
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# Then install domain libraries

runtime/core/portable_type/c10/c10/util/BFloat16-math.h

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@@ -181,7 +181,7 @@ template <
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typename T,
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typename std::enable_if_t<c10::is_reduced_floating_point_v<T>, int> = 0>
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inline T rsqrt(T a) {
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return 1.0 / std::sqrt(float(a));
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return 1.0f / std::sqrt(float(a));
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}
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template <
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typename T,

runtime/core/portable_type/c10/c10/util/complex_math.h

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@@ -327,7 +327,7 @@ C10_HOST_DEVICE inline c10::complex<T> atanh(const c10::complex<T>& x) {
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template <typename T>
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C10_HOST_DEVICE inline c10::complex<T> log1p(const c10::complex<T>& z) {
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#if defined(__APPLE__) || defined(__MACOSX) || defined(__CUDACC__) || \
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defined(__HIPCC__)
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defined(__HIPCC__) || defined(__SYCL_DEVICE_ONLY__)
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// For Mac, the new implementation yielded a high relative error. Falling back
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// to the old version for now.
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// See https://github.com/numpy/numpy/pull/22611#issuecomment-1667945354

runtime/core/portable_type/c10/torch/headeronly/util/Half.h

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@@ -236,7 +236,7 @@ C10_HOST_DEVICE inline float fp16_ieee_to_fp32_value(uint16_t h) {
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/*
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* - Choose either results of conversion of input as a normalized number, or
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* as a denormalized number, depending on the input exponent. The variable
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* two_w contains input exponent in bits 27-31, therefore if its smaller than
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* two_w contains input exponent in bits 27-31, therefore if it's smaller than
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* 2**27, the input is either a denormal number, or zero.
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* - Combine the result of conversion of exponent and mantissa with the sign
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* of the input number.

torch_pin.py

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@@ -1,2 +1,2 @@
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TORCH_VERSION = "2.12.0"
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TORCH_VERSION = "2.13.0"
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# NIGHTLY_VERSION = "dev20260318" Temporarily pinning to stable release candidate. Revert https://github.com/pytorch/executorch/pull/18287

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