Update base for Update on "Preserve python backtrace in autograd engi…

…ne errors."

This PR attempts to address #42560 by capturing the appropriate
exception_ptr in the autograd engine and passing it over to the Future.

As part of this change, there is a significant change the Future API where we
now only accept an exception_ptr as part of setError.

For the example in #42560, the exception trace would now look like:


```
> Traceback (most recent call last):
>   File "test_autograd.py", line 6914, in test_preserve_backtrace
>     Foo.apply(t).sum().backward()
>   File "torch/tensor.py", line 214, in backward
>     torch.autograd.backward(self, gradient, retain_graph, create_graph)
>   File "torch/autograd/__init__.py", line 127, in backward
>     allow_unreachable=True)  # allow_unreachable flag
>   File "torch/autograd/function.py", line 87, in apply
>     return self._forward_cls.backward(self, *args)
>   File "test_autograd.py", line 6910, in backward
>     raise ValueError("something")
> ValueError: something
```

Differential Revision: [D23365408](https://our.internmc.facebook.com/intern/diff/D23365408/)

[ghstack-poisoned]

.circleci/scripts/cpp_doc_push_script.sh

@@ -47,16 +47,11 @@ sudo apt-get -y install doxygen
 # Generate ATen files
 pushd "${pt_checkout}"
 pip install -r requirements.txt
-time python aten/src/ATen/gen.py \
+time python -m tools.codegen.gen \
   -s aten/src/ATen \
-  -d build/aten/src/ATen \
-  aten/src/ATen/Declarations.cwrap \
-  aten/src/THCUNN/generic/THCUNN.h \
-  aten/src/ATen/nn.yaml \
-  aten/src/ATen/native/native_functions.yaml
+  -d build/aten/src/ATen
 
 # Copy some required files
-cp aten/src/ATen/common_with_cwrap.py tools/shared/cwrap_common.py
 cp torch/_utils_internal.py tools/shared
 
 # Generate PyTorch files

.github/workflows/lint.yml

@@ -131,13 +131,9 @@ jobs:
             time python setup.py --cmake-only build
 
             # Generate ATen files.
-            time python aten/src/ATen/gen.py \
+            time python -m tools.codegen.gen \
               -s aten/src/ATen \
-              -d build/aten/src/ATen \
-              aten/src/ATen/Declarations.cwrap \
-              aten/src/THCUNN/generic/THCUNN.h \
-              aten/src/ATen/nn.yaml \
-              aten/src/ATen/native/native_functions.yaml
+              -d build/aten/src/ATen
 
             # Generate PyTorch files.
             time python tools/setup_helpers/generate_code.py            \

.gitignore

@@ -108,9 +108,6 @@ env
 # macOS dir files
 .DS_Store
 
-# Symbolic files
-tools/shared/cwrap_common.py
-
 # Ninja files
 .ninja_deps
 .ninja_log

.jenkins/caffe2/build.sh

@@ -248,6 +248,8 @@ else
     export MAX_JOBS=`expr $(nproc) - 1`
   fi
 
+  pip install --user dataclasses
+
   $PYTHON setup.py install --user
 
   report_compile_cache_stats

.jenkins/pytorch/macos-common.sh

@@ -20,7 +20,7 @@ if [ ! -d "${WORKSPACE_DIR}/miniconda3" ]; then
 fi
 export PATH="${WORKSPACE_DIR}/miniconda3/bin:$PATH"
 source ${WORKSPACE_DIR}/miniconda3/bin/activate
-retry conda install -y mkl mkl-include numpy=1.18.5 pyyaml=5.3 setuptools=46.0.0 cmake cffi ninja typing_extensions
+retry conda install -y mkl mkl-include numpy=1.18.5 pyyaml=5.3 setuptools=46.0.0 cmake cffi ninja typing_extensions dataclasses
 
 # The torch.hub tests make requests to GitHub.
 #

.jenkins/pytorch/win-test-helpers/build_pytorch.bat

@@ -21,8 +21,8 @@ call %INSTALLER_DIR%\install_sccache.bat
 call %INSTALLER_DIR%\install_miniconda3.bat
 
 
-:: Install ninja
-if "%REBUILD%"=="" ( pip install -q "ninja==1.9.0" )
+:: Install ninja and other deps
+if "%REBUILD%"=="" ( pip install -q "ninja==1.9.0" dataclasses )
 
 git submodule sync --recursive
 git submodule update --init --recursive

.jenkins/pytorch/win-test-helpers/setup_pytorch_env.bat

@@ -22,7 +22,7 @@ call %CONDA_PARENT_DIR%\Miniconda3\Scripts\activate.bat %CONDA_PARENT_DIR%\Minic
 if NOT "%BUILD_ENVIRONMENT%"=="" (
     :: We have to pin Python version to 3.6.7, until mkl supports Python 3.7
     :: Numba is pinned to 0.44.0 to avoid https://github.com/numba/numba/issues/4352
-    call conda install -y -q python=3.6.7 numpy mkl cffi pyyaml boto3 protobuf numba==0.44.0 scipy==1.5.0 typing_extensions
+    call conda install -y -q python=3.6.7 numpy mkl cffi pyyaml boto3 protobuf numba==0.44.0 scipy==1.5.0 typing_extensions dataclasses
     if %errorlevel% neq 0 ( exit /b %errorlevel% )
     call conda install -y -q -c conda-forge cmake
     if %errorlevel% neq 0 ( exit /b %errorlevel% )

BUILD.bazel

@@ -106,17 +106,19 @@ cc_test(
     ],
 )
 
+# TODO: refactor this into its own library (but how to make
+# a binary based off of a module in a library?)
 py_binary(
     name = "gen",
-    srcs = ["aten/src/ATen/gen.py"],
+    srcs = ["tools/setup_helpers/gen.py"],
+    deps = [
+        ":tools_codegen"
+    ],
 )
 
 genrule(
     name = "generated_cpp",
     srcs = [
-        "aten/src/ATen/Declarations.cwrap",
-        "aten/src/THCUNN/generic/THCUNN.h",
-        "aten/src/ATen/nn.yaml",
         "aten/src/ATen/native/native_functions.yaml",
     ] + glob(["aten/src/ATen/templates/**"]),
     outs = [
@@ -126,8 +128,6 @@ genrule(
         "aten/src/ATen/CPUType.cpp",
         "aten/src/ATen/Functions.h",
         "aten/src/ATen/Functions.cpp",
-        "aten/src/ATen/LegacyTHFunctionsCPU.h",
-        "aten/src/ATen/LegacyTHFunctionsCPU.cpp",
         "aten/src/ATen/NativeFunctions.h",
         "aten/src/ATen/MkldnnCPUType.h",
         "aten/src/ATen/MkldnnCPUType.cpp",
@@ -141,14 +141,13 @@ genrule(
         "aten/src/ATen/core/TensorMethods.cpp",
         "aten/src/ATen/core/ATenOpList.cpp",
     ],
-    cmd = "$(location :gen) --source-path aten/src/ATen --install_dir `dirname $(location aten/src/ATen/Declarations.yaml)` aten/src/ATen/Declarations.cwrap aten/src/THCUNN/generic/THCUNN.h aten/src/ATen/nn.yaml aten/src/ATen/native/native_functions.yaml",
+    cmd = "$(location :gen) --source-path aten/src/ATen --install_dir `dirname $(location aten/src/ATen/Declarations.yaml)`",
     tools = [":gen"],
 )
 
 py_library(
-    name = "code_template",
-    srcs = ["aten/src/ATen/code_template.py"],
-    imports = ["aten"],
+    name = "tools_codegen",
+    srcs = glob(["tools/codegen/**/*.py"]),
 )
 
 py_library(
@@ -158,7 +157,7 @@ py_library(
         "tools/autograd/*.yaml",
         "tools/autograd/templates/*",
     ]),
-    deps = [":code_template"],
+    deps = [":tools_codegen"],
 )
 
 py_library(

README.md

@@ -169,7 +169,7 @@ If you are building for NVIDIA's Jetson platforms (Jetson Nano, TX1, TX2, AGX Xa
 
 Common
 ```bash
-conda install numpy ninja pyyaml mkl mkl-include setuptools cmake cffi typing_extensions future six requests
+conda install numpy ninja pyyaml mkl mkl-include setuptools cmake cffi typing_extensions future six requests dataclasses
 ```
 
 On Linux

aten/src/ATen/BatchingRegistrations.cpp

@@ -426,6 +426,8 @@ TORCH_LIBRARY_IMPL(aten, Batched, m) {
   m.impl("pow.Tensor_Scalar", unary_pointwise_batching_rule<TensorScalarType, at::pow, Scalar>);
   m.impl("pow.Scalar", pow_scalar_Tensor_batching_rule);
 
+  m.impl("sigmoid_backward", binary_pointwise_batching_rule<TensorTensorType, at::sigmoid_backward>);
+
   // for at::result_type, call the native::result_type implementation.
   // We don't have to do anything special because native::result_type operates
   // on the logical shape of the tensors.