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python_hook.cpp
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python_hook.cpp
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#include <torch/csrc/autograd/python_hook.h>
#include <c10/util/irange.h>
#include <pybind11/pybind11.h>
#include <torch/csrc/Exceptions.h>
#include <torch/csrc/PyInterpreter.h>
#include <torch/csrc/THP.h>
#include <torch/csrc/autograd/python_variable.h>
#include <torch/csrc/dynamo/compiled_autograd.h>
#include <torch/csrc/utils/object_ptr.h>
#include <torch/csrc/utils/pybind.h>
#include <torch/csrc/utils/python_strings.h>
#include <iostream>
#include <sstream>
using torch::autograd::Variable;
using torch::autograd::variable_list;
static PyObject* wrap_variables(const variable_list& c_variables);
static variable_list unwrap_variables(PyObject* py_variables);
static std::string hook_name(PyObject* hook);
static void check_result(PyObject* original, PyObject* result, PyObject* hook);
static void check_single_result(
PyObject* original,
PyObject* result,
PyObject* hook);
namespace torch {
namespace autograd {
namespace {
// This function is called in 4 different cases:
// 1) TensorPreHook
// 2) PreHook
// 3) PostHook
// 4) TensorPostAccGradHook
//
// Depending on the case, args and res can hold different types of objects:
//
// args:
// TensorPreHook (Tensor,)
// PreHook ((Tensor, ...),) (grad_outputs,)
// PostHook ((Tensor, ...), (Tensor, ...)) (grad_inputs, grad_outputs)
// TensorPostAccGradHook ((Tensor), ()) (tensor,)
//
// res:
// TensorPreHook Tensor
// PreHook ((Tensor, ...),) (grad_outputs,)
// PostHook ((Tensor, ...),) (grad_inputs,)
// TensorPostAccGradHook None
//
// This function returns True if any hook returned non-None value, and False
// otherwise.
bool _call_hooks(PyObject* dict, PyObject* args) {
// Note: [Extend Hook Lifetime]
// Hold a reference to hooks till we iterate over them.
// This is to handle the case when hook calls `handle.remove` inside it
// and it's refcount goes to `0`, Python is free to GC it.
// We hold onto a stale pointer and subsequent call to
// `check_single_result`, which tries to fetch the `hook`'s name segfaults.
// So, we use `PyDict_Values` which returns a new reference to the values
// i.e. we hold the reference to the hooks till we have iterated over them.
// Reference: https://github.com/pytorch/pytorch/issues/58354
auto hooks = THPObjectPtr{PyDict_Values(dict)};
bool is_modified = false;
const auto len = PyList_Size(hooks);
for (Py_ssize_t idx = 0; idx < len; ++idx) {
const auto hook = PyList_GetItem(hooks, idx);
THPObjectPtr res(PyObject_CallObject(hook, args));
if (!res)
throw python_error();
if (res == Py_None)
continue;
PyObject* args0 = PyTuple_GetItem(args, 0);
if (res == args0)
continue;
if (PyTuple_CheckExact(args0)) {
check_result(args0, res, hook);
} else {
check_single_result(args0, res, hook);
}
PyTuple_SetItem(args, 0, res.release());
is_modified = true;
}
return is_modified;
}
} // namespace
PyFunctionTensorPreHook::PyFunctionTensorPreHook(
PyObject* dict,
size_t value_idx)
: dict(dict), value_idx(value_idx) {
Py_INCREF(dict);
}
// NOLINTNEXTLINE(bugprone-exception-escape)
PyFunctionTensorPreHook::~PyFunctionTensorPreHook() {
// If python is already dead, leak the wrapped python objects
if (Py_IsInitialized()) {
pybind11::gil_scoped_acquire gil;
Py_DECREF(dict);
}
}
auto PyFunctionTensorPreHook::operator()(const variable_list& values)
-> variable_list {
pybind11::gil_scoped_acquire gil;
THPObjectPtr value(THPVariable_Wrap(values.at(value_idx)));
if (!value)
throw python_error();
THPObjectPtr tup(PyTuple_New(1));
PyTuple_SET_ITEM(tup.get(), 0, value.release());
bool is_tup_modified = _call_hooks(dict, tup.get());
variable_list results(values);
if (is_tup_modified) {
results[value_idx] = THPVariable_Unpack(PyTuple_GetItem(tup.get(), 0));
}
return results;
}
PyFunctionPreHook::PyFunctionPreHook(PyObject* dict) : dict(dict) {
Py_INCREF(dict);
}
// NOLINTNEXTLINE(bugprone-exception-escape)
PyFunctionPreHook::~PyFunctionPreHook() {
// If python is already dead, leak the wrapped python objects
if (Py_IsInitialized()) {
pybind11::gil_scoped_acquire gil;
Py_DECREF(dict);
}
}
auto PyFunctionPreHook::operator()(const variable_list& grad_outputs_)
-> variable_list {
pybind11::gil_scoped_acquire gil;
THPObjectPtr grad_outputs(wrap_variables(grad_outputs_));
THPObjectPtr tup(PyTuple_New(1));
PyTuple_SET_ITEM(tup.get(), 0, grad_outputs.release());
_call_hooks(dict, tup.get());
return unwrap_variables(PyTuple_GetItem(tup.get(), 0));
}
PyFunctionPostHook::PyFunctionPostHook(PyObject* dict) : dict(dict) {
Py_INCREF(dict);
}
// NOLINTNEXTLINE(bugprone-exception-escape)
PyFunctionPostHook::~PyFunctionPostHook() {
// If python is already dead, leak the wrapped python objects
if (Py_IsInitialized()) {
pybind11::gil_scoped_acquire gil;
Py_DECREF(dict);
}
}
auto PyFunctionPostHook::operator()(
const variable_list& _outputs, /* grad_inputs */
const variable_list& _inputs /* grad_outputs */) -> variable_list {
pybind11::gil_scoped_acquire gil;
THPObjectPtr grad_inputs(wrap_variables(_outputs));
THPObjectPtr grad_outputs(wrap_variables(_inputs));
THPObjectPtr tup(PyTuple_New(2));
PyTuple_SET_ITEM(tup.get(), 0, grad_inputs.release());
PyTuple_SET_ITEM(tup.get(), 1, grad_outputs.release());
_call_hooks(dict, tup.get());
return unwrap_variables(PyTuple_GetItem(tup.get(), 0));
}
void PyFunctionTensorPreHook::compiled_args(CompiledNodeArgs& args) {
PyObject *key = nullptr, *value = nullptr;
Py_ssize_t pos = 0;
while (PyDict_Next(dict, &pos, &key, &value)) {
Py_INCREF(value);
args.add_tensor_pre_hook(
c10::SafePyObject(value, getPyInterpreter()),
static_cast<int>(value_idx));
}
}
void PyFunctionPreHook::compiled_args(CompiledNodeArgs& args) {
PyObject *key = nullptr, *value = nullptr;
Py_ssize_t pos = 0;
while (PyDict_Next(dict, &pos, &key, &value)) {
Py_INCREF(value);
args.add_pre_hook(c10::SafePyObject(value, getPyInterpreter()));
}
}
void PyFunctionPostHook::compiled_args(CompiledNodeArgs& args) {
PyObject *key = nullptr, *value = nullptr;
Py_ssize_t pos = 0;
while (PyDict_Next(dict, &pos, &key, &value)) {
Py_INCREF(value);
args.add_post_hook(c10::SafePyObject(value, getPyInterpreter()));
}
}
PyFunctionTensorPostAccGradHooks::PyFunctionTensorPostAccGradHooks(
PyObject* dict)
: dict(dict) {
Py_INCREF(dict);
}
// NOLINTNEXTLINE(bugprone-exception-escape)
PyFunctionTensorPostAccGradHooks::~PyFunctionTensorPostAccGradHooks() {
// If python is already dead, leak the wrapped python objects
if (Py_IsInitialized()) {
pybind11::gil_scoped_acquire gil;
Py_DECREF(dict);
}
}
auto PyFunctionTensorPostAccGradHooks::operator()(const Variable& tensor)
-> void {
pybind11::gil_scoped_acquire gil;
THPObjectPtr tup(PyTuple_New(1));
PyTuple_SET_ITEM(tup.get(), 0, THPVariable_Wrap(tensor));
bool returned_none = !_call_hooks(dict, tup.get());
TORCH_CHECK(
returned_none, "Tensor post accumulate grad hooks should return None.");
}
void PyFunctionTensorPostAccGradHooks::compiled_args(
torch::dynamo::autograd::CompiledNodeArgs& args) {
PyObject *key = nullptr, *value = nullptr;
Py_ssize_t pos = 0;
while (PyDict_Next(dict, &pos, &key, &value)) {
Py_INCREF(value);
c10::SafePyObject hook_obj(value, getPyInterpreter());
args.add_post_acc_grad_hook(std::move(hook_obj));
}
}
void PyFunctionTensorPostAccGradHooks::apply_with_saved(
Variable& tensor,
torch::dynamo::autograd::SwapSavedVariables& saved) {
for (const auto hook : saved.get_curr_node_call().post_acc_grad_hooks) {
THPObjectPtr py_var(THPVariable_Wrap(tensor));
PyObject_CallMethod(
saved.get_py_compiler(),
"post_acc_grad_hook",
"Oi",
py_var.get(),
hook);
}
}
} // namespace autograd
} // namespace torch
static PyObject* wrap_variables(const variable_list& c_variables) {
size_t num_vars = c_variables.size();
THPObjectPtr tuple(PyTuple_New(static_cast<Py_ssize_t>(num_vars)));
if (!tuple)
throw python_error();
for (const auto i : c10::irange(num_vars)) {
THPObjectPtr var(THPVariable_Wrap(c_variables[i]));
if (!var)
throw python_error();
PyTuple_SET_ITEM(tuple.get(), i, var.release());
}
return tuple.release();
}
static variable_list unwrap_variables(PyObject* py_variables) {
variable_list results(PyTuple_GET_SIZE(py_variables));
for (const auto i : c10::irange(results.size())) {
PyObject* item = PyTuple_GET_ITEM(py_variables, i);
if (item == Py_None) {
continue;
} else if (THPVariable_Check(item)) {
results[i] = THPVariable_Unpack(item);
} else {
// this should never happen, but just in case...
std::stringstream ss;
ss << "expected variable but got " << Py_TYPE(item)->tp_name;
throw std::runtime_error(ss.str());
}
}
return results;
}
static void check_result(PyObject* prev, PyObject* result, PyObject* hook) {
if (!PyTuple_Check(result)) {
PyErr_Format(
PyExc_TypeError,
"expected tuple, but hook returned '%s'",
THPUtils_typename(result));
throw python_error();
}
auto prev_size = PyTuple_GET_SIZE(prev);
auto result_size = PyTuple_GET_SIZE(result);
if (prev_size != result_size) {
std::stringstream ss;
auto name = hook_name(hook);
ss << "hook '" << name << "' has returned an incorrect number ";
ss << "of values (got " << result_size << ", but expected ";
ss << prev_size << ")";
throw std::runtime_error(ss.str());
}
for (const auto i : c10::irange(prev_size)) {
check_single_result(
PyTuple_GET_ITEM(prev, i), PyTuple_GET_ITEM(result, i), hook);
}
}
static void check_single_result(
PyObject* _original,
PyObject* _result,
PyObject* hook) {
if (_result == Py_None)
return;
if (_original == Py_None) {
throw std::runtime_error(
"can't replace a None gradient with a non-None value");
}
if (!PyObject_IsInstance(_result, THPVariableClass)) {
PyErr_Format(
PyExc_TypeError,
"expected Variable, but hook returned '%s'",
THPUtils_typename(_result));
throw python_error();
}
const auto& original = THPVariable_Unpack(_original);
const auto& result = THPVariable_Unpack(_result);
torch::autograd::check_variable_result(original, result, hook_name(hook));
}
static std::string hook_name(PyObject* hook) {
if (PyObject_HasAttrString(hook, "__name__")) {
THPObjectPtr name(PyObject_GetAttrString(hook, "__name__"));
if (!name)
throw python_error();
if (name && THPUtils_checkString(name.get())) {
return THPUtils_unpackString(name.get());
}
}
return "<unknown>";
}