forked from pytorch/pytorch
-
Notifications
You must be signed in to change notification settings - Fork 0
/
python_cpp_function.cpp
276 lines (235 loc) · 8.02 KB
/
python_cpp_function.cpp
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
#include <c10/util/irange.h>
#include <torch/csrc/autograd/python_cpp_function.h>
#include <torch/csrc/python_headers.h>
#include <memory>
#include <cstdio>
#include <typeindex>
#include <unordered_map>
#include <torch/csrc/autograd/python_function.h>
#include <torch/csrc/autograd/python_variable.h>
#include <torch/csrc/autograd/python_hook.h>
#include <torch/csrc/autograd/python_anomaly_mode.h>
#include <pybind11/pybind11.h>
#include <torch/csrc/utils/python_numbers.h>
#include <torch/csrc/utils/python_strings.h>
#include <torch/csrc/DynamicTypes.h>
#include <torch/csrc/Exceptions.h>
using namespace torch::autograd;
namespace torch { namespace autograd {
namespace {
PyObject* THPCppFunction_call(PyObject* self, PyObject* args, PyObject *kwargs)
{
if (kwargs && PyDict_Size(kwargs) != 0) {
return PyErr_Format(PyExc_TypeError, "keyword arguments are not supported");
}
int num_inputs = PyTuple_GET_SIZE(args);
int num_inputs_required = ((THPCppFunction*)self)->cdata->num_inputs();
if (num_inputs != num_inputs_required) {
return PyErr_Format(PyExc_TypeError, "expected %d arguments, got %d instead",
num_inputs_required, num_inputs);
}
variable_list vars(num_inputs);
for (int i = 0; i != num_inputs; ++i) {
PyObject* arg = PyTuple_GET_ITEM(args, i);
if (arg == Py_None) {
continue;
}
if (!THPVariable_Check(arg)) {
return PyErr_Format(PyExc_TypeError, "argument %d is not a Variable", i);
}
vars[i] = THPVariable_Unpack(arg);
}
variable_list output;
HANDLE_TH_ERRORS {
pybind11::gil_scoped_release nogil;
output = (*((THPCppFunction*)self)->cdata)(std::move(vars));
}
END_HANDLE_TH_ERRORS
int num_outputs = output.size();
if (num_outputs == 1) {
// assume we want to unpack one element tuples for now
return THPVariable_Wrap(output[0]);
}
THPObjectPtr tuple(PyTuple_New(num_outputs));
for (int i = 0; i != num_outputs; ++i) {
PyTuple_SET_ITEM(tuple.get(), i, THPVariable_Wrap(output[i]));
}
return tuple.release();
}
int THPCppFunction_traverse(PyObject* self, visitproc visit, void *arg)
{
auto& fn = *((THPCppFunction*)self)->cdata;
for (const auto& hook : fn.pre_hooks()) {
if (auto pyhook = dynamic_cast<PyFunctionPreHook*>(hook.get())) {
Py_VISIT(pyhook->dict);
}
}
for (const auto& hook : fn.post_hooks()) {
if (auto pyhook = dynamic_cast<PyFunctionPostHook*>(hook.get())) {
Py_VISIT(pyhook->dict);
}
}
return 0;
}
int THPCppFunction_clear(PyObject* self)
{
auto f = (THPCppFunction*)self;
// Remove the weak ref of the c++ object if it exist
if (f->cdata) {
f->cdata->set_pyobj(nullptr);
}
f->cdata.reset();
return 0;
}
void THPCppFunction_dealloc(PyObject* self)
{
THPCppFunction_clear(self);
((THPCppFunction*)self)->cdata.~shared_ptr();
Py_TYPE(self)->tp_free(self);
}
} // namespace
PyObject* THPCppFunction_next_functions(THPCppFunction* self, PyObject* hook)
{
const auto num_next = self->cdata->num_outputs();
THPObjectPtr py_functions(PyTuple_New(num_next));
if (!py_functions) return nullptr;
for (const auto i : c10::irange(num_next)) {
auto& c_tuple = self->cdata->next_edge(i);
THPObjectPtr tuple(PyTuple_New(2));
if (!tuple) return nullptr;
PyObject *py_fn = functionToPyObject(c_tuple.function);
if (!py_fn) return nullptr;
PyTuple_SET_ITEM(tuple.get(), 0, py_fn);
PyObject *py_idx = THPUtils_packUInt32(c_tuple.input_nr);
if (!py_idx) return nullptr;
PyTuple_SET_ITEM(tuple.get(), 1, py_idx);
PyTuple_SET_ITEM(py_functions.get(), i, tuple.release());
}
return py_functions.release();
}
PyObject* THPCppFunction_metadata(THPCppFunction *self, void *_unused)
{
auto metadata = static_cast<PyAnomalyMetadata*>(self->cdata->metadata())->dict();
Py_INCREF(metadata);
return metadata;
}
PyObject* THPCppFunction_requires_grad(THPCppFunction* self, void *unused) {
Py_RETURN_TRUE;
}
PyObject* THPCppFunction_register_hook_dict(PyObject* self, PyObject* _var)
{
if (!THPVariable_Check(_var)) {
return PyErr_Format(PyExc_TypeError, "_register_hook_dict expected a variable");
}
auto var = (THPVariable*)_var;
auto& fn = *((THPCppFunction*)self)->cdata;
std::unique_ptr<FunctionPreHook> hook(
new PyFunctionPreHook(var->backward_hooks, THPVariable_Unpack(var).output_nr()));
fn.add_pre_hook(std::move(hook));
Py_RETURN_NONE;
}
PyObject* THPCppFunction_register_hook(PyObject* self, PyObject* hook)
{
auto& fn = *((THPCppFunction*)self)->cdata;
return registerFunctionHook(fn, hook);
}
PyObject* THPCppFunction_name(PyObject* self, PyObject *noargs) {
auto& fn = *((THPCppFunction*)self)->cdata;
return THPUtils_packString(fn.name());
}
// NOLINTNEXTLINE(cppcoreguidelines-avoid-c-arrays,cppcoreguidelines-avoid-non-const-global-variables,modernize-avoid-c-arrays)
static struct PyMethodDef default_methods[] = {
THP_FUNCTION_DEFAULT_METHODS,
{nullptr}
};
// NOLINTNEXTLINE(cppcoreguidelines-avoid-c-arrays,cppcoreguidelines-avoid-non-const-global-variables,modernize-avoid-c-arrays)
static struct PyGetSetDef default_properties[] = {
THP_FUNCTION_DEFAULT_PROPERTIES,
{nullptr}
};
PyTypeObject* _initFunctionPyTypeObject(PyTypeObject& type, const char* name,
PyGetSetDef* function_properties, PyMethodDef* function_methods)
{
type.tp_flags = Py_TPFLAGS_DEFAULT | Py_TPFLAGS_HAVE_GC;
type.tp_name = name;
type.tp_basicsize = sizeof(THPCppFunction);
type.tp_call = THPCppFunction_call;
type.tp_methods = function_methods ? function_methods : default_methods;
type.tp_getset = function_properties ? function_properties : default_properties;
type.tp_dealloc = THPCppFunction_dealloc;
type.tp_traverse = THPCppFunction_traverse;
type.tp_clear = THPCppFunction_clear;
if (PyType_Ready(&type) < 0) {
auto msg = std::string("Unable to instantiate PyTypeObject for ") + name;
throw std::runtime_error(msg);
}
return &type;
}
static std::unordered_map<std::type_index, THPObjectPtr> cpp_function_types;
struct DefaultFunctionType {
DefaultFunctionType() : type() {
_initFunctionPyTypeObject(type, "CppFunction", nullptr, nullptr);
Py_INCREF(&type);
}
PyTypeObject type;
};
PyObject* functionToPyObject(const std::shared_ptr<Node>& cdata)
{
static DefaultFunctionType default_type;
if (!cdata) {
Py_RETURN_NONE;
}
if (auto pfw = dynamic_cast<PyNode*>(cdata.get())) {
PyObject* obj = pfw->obj;
Py_INCREF(obj);
return obj;
}
if (cdata->pyobj()) {
Py_INCREF(cdata->pyobj());
} else {
auto& fn = *cdata;
auto it = cpp_function_types.find(std::type_index(typeid(fn)));
// NOLINTNEXTLINE(cppcoreguidelines-init-variables)
PyTypeObject* type;
if (it == cpp_function_types.end()) {
type = &default_type.type;
} else {
type = (PyTypeObject*)it->second.get();
}
THPObjectPtr obj(type->tp_alloc(type, 0));
if (!obj) return nullptr;
THPCppFunction* f = (THPCppFunction*)obj.get();
new (&f->cdata) std::shared_ptr<Node>(cdata);
// No INCREF here as we only have a weak reference
cdata->set_pyobj(obj.release());
}
return cdata->pyobj();
}
void registerCppFunction(const std::type_info& type, PyTypeObject* pytype)
{
Py_INCREF((PyObject*)pytype);
cpp_function_types[std::type_index(type)] = THPObjectPtr((PyObject*)pytype);
}
PyObject* registerFunctionHook(Node& fn, PyObject* hook)
{
PyObject* dict = Py_None;
for (const auto& hook : fn.post_hooks()) {
if (auto pyhook = dynamic_cast<PyFunctionPostHook*>(hook.get())) {
dict = pyhook->dict;
break;
}
}
THPObjectPtr register_fn(PyObject_GetAttrString(THPFunctionClass, "_register_hook"));
if (!register_fn) return nullptr;
THPObjectPtr res(PyObject_CallFunctionObjArgs(register_fn.get(), dict, hook, nullptr));
if (!res) return nullptr;
if (dict == Py_None) {
dict = PyTuple_GET_ITEM(res.get(), 0);
std::unique_ptr<FunctionPostHook> hook(new PyFunctionPostHook(dict));
fn.add_post_hook(std::move(hook));
}
PyObject* handle = PyTuple_GET_ITEM(res.get(), 1);
Py_INCREF(handle);
return handle;
}
}} // namespace torch::autograd