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Update on "[PyTorch] Store Tensor explicitly in IValue"
Enables following diff, which will make toTensor() return `const Tensor&` and allow callers to avoid refcounting overhead. Differential Revision: [D25324617](https://our.internmc.facebook.com/intern/diff/D25324617/) [ghstack-poisoned]
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‎.circleci/cimodel/data/dimensions.py

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]
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ROCM_VERSIONS = [
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"3.9",
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"3.10",
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"4.0",
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]
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ROCM_VERSION_LABELS = ["rocm" + v for v in ROCM_VERSIONS]

‎.circleci/config.yml

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‎BUILD.bazel

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filegroup(
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name = "thc_srcs_cu",
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srcs = [
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"aten/src/THC/THCBlas.cu.cc",
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"aten/src/THC/THCReduceApplyUtils.cu.cc",
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"aten/src/THC/THCSleep.cu.cc",
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"aten/src/THC/THCSortUtils.cu.cc",

‎CONTRIBUTING.md

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[Lint as you type](https://github.com/pytorch/pytorch/wiki/Lint-as-you-type)
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for documentation on how to do this.
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If you haven't set up the pre-commit hook and have already committed files and
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CI reports `flake8` errors, you can run the check locally in your PR branch with:
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```bash
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flake8 $(git diff --name-only $(git merge-base --fork-point master))
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```
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fix the code so that no errors are reported when you re-run the above check again,
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and then commit the fix.
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## Building PyTorch with ASAN
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[ASAN](https://github.com/google/sanitizers/wiki/AddressSanitizer) is very

‎android/gradle/android_tasks.gradle

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import java.nio.file.Files
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import java.nio.file.Paths
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import java.io.FileOutputStream

‎android/pytorch_android/host/build.gradle

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}
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apply from: rootProject.file('gradle/release.gradle')
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‎android/settings.gradle

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project(':pytorch_host').projectDir = file('pytorch_android/host')
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project(':test_app').projectDir = file('test_app/app')
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‎aten/src/ATen/ATen.h

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#include <c10/util/Exception.h>
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#include <ATen/core/UnsafeFromTH.h>
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#include <ATen/core/ivalue.h>
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#include <ATen/core/jit_type.h>

‎aten/src/ATen/LegacyTHFunctionsCUDA.h

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Tensor _thnn_log_sigmoid_backward(const Tensor & grad_output, const Tensor & self, const Tensor & buffer);
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Tensor & _thnn_rrelu_with_noise_forward_out(Tensor & output, const Tensor & self, const Tensor & noise, Scalar lower, Scalar upper, bool training, c10::optional<at::Generator> generator);
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Tensor _thnn_rrelu_with_noise_forward(const Tensor & self, const Tensor & noise, Scalar lower, Scalar upper, bool training, c10::optional<at::Generator> generator);
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Tensor & _thnn_rrelu_with_noise_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, const Tensor & noise, Scalar lower, Scalar upper, bool training);
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Tensor _thnn_rrelu_with_noise_backward(const Tensor & grad_output, const Tensor & self, const Tensor & noise, Scalar lower, Scalar upper, bool training);
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Tensor & _thnn_rrelu_with_noise_forward_(Tensor & self, const Tensor & noise, Scalar lower, Scalar upper, bool training, c10::optional<at::Generator> generator);
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std::tuple<Tensor &,Tensor &,Tensor &> _thnn_conv2d_forward_out(Tensor & output, Tensor & columns, Tensor & ones, const Tensor & self, const Tensor & weight, IntArrayRef kernel_size, const Tensor & bias, IntArrayRef stride, IntArrayRef padding);

‎aten/src/ATen/MemoryOverlap.cpp

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if (!a->is_contiguous() || !b->is_contiguous()) {
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return MemOverlapStatus::TOO_HARD;
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}
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if (!a->has_storage() || !b->has_storage()) {
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return MemOverlapStatus::NO;
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}
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if (a->storage().data() == b->storage().data()) {
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const auto a_begin = static_cast<char*>(a->data());
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const auto a_end = a_begin + a->numel() * a->itemsize();

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