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Size.cpp
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Size.cpp
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#include <c10/util/irange.h>
#include <pybind11/pytypes.h>
#include <torch/csrc/Size.h>
#include <torch/csrc/utils/pybind.h>
#include <torch/csrc/utils/object_ptr.h>
#include <torch/csrc/utils/python_arg_parser.h>
#include <torch/csrc/utils/python_numbers.h>
#include <torch/csrc/utils/python_strings.h>
#include <torch/csrc/utils/python_tuples.h>
#include <string>
#include <torch/csrc/autograd/python_variable.h>
#include <torch/csrc/jit/frontend/tracer.h>
struct THPSize {
PyTupleObject tuple;
};
PyObject* THPSize_New(const torch::autograd::Variable& var) {
if (!torch::jit::tracer::isTracing()) {
auto sizes = var.sizes();
return THPSize_NewFromSizes(var.dim(), sizes.data());
}
auto self = THPObjectPtr(THPSizeType.tp_alloc(&THPSizeType, var.dim()));
if (!self)
throw python_error();
for (const auto i : c10::irange(var.dim())) {
PyObject* py_size_tensor =
THPVariable_Wrap(torch::jit::tracer::getSizeOf(var, i));
if (!py_size_tensor)
throw python_error();
PyTuple_SET_ITEM(self.get(), i, py_size_tensor);
}
return self.release();
}
PyObject* THPSize_NewFromSizes(int64_t dim, const int64_t* sizes) {
auto self = THPObjectPtr(THPSizeType.tp_alloc(&THPSizeType, dim));
if (!self)
throw python_error();
THPUtils_packInt64Array(self, dim, sizes);
return self.release();
}
PyObject* THPSize_NewFromSymSizes(const at::Tensor& self_) {
auto sym_sizes = self_.sym_sizes();
auto ret = THPObjectPtr(THPSizeType.tp_alloc(
&THPSizeType, static_cast<Py_ssize_t>(sym_sizes.size())));
if (!ret)
throw python_error();
for (auto i : c10::irange(sym_sizes.size())) {
auto si = sym_sizes[i];
if (si.is_symbolic()) {
// First check for actual symbolic values.
// Reason: so that we don't replace it by its integer replacement
// implicitly.
TORCH_CHECK(
!torch::jit::tracer::isTracing(),
"JIT Tracing of SymInts isn't supported");
auto py_symint = py::cast(si).release().ptr();
if (!py_symint)
throw python_error();
PyTuple_SET_ITEM(ret.get(), i, py_symint);
} else {
// Otherwise, we know that it is an actual integer value.
auto m = si.maybe_as_int();
if (torch::jit::tracer::isTracing()) {
PyObject* py_size_tensor = THPVariable_Wrap(
torch::jit::tracer::getSizeOf(self_, static_cast<int64_t>(i)));
if (!py_size_tensor)
throw python_error();
PyTuple_SET_ITEM(ret.get(), i, py_size_tensor);
} else {
// NOLINTNEXTLINE(bugprone-unchecked-optional-access)
PyTuple_SET_ITEM(ret.get(), i, THPUtils_packInt64(*m));
}
}
}
return ret.release();
}
static bool isTracedZeroDimVar(PyObject* item) {
if (!THPVariable_Check(item))
return false;
auto& var = THPVariable_Unpack(item);
return var.dim() == 0 && torch::jit::tracer::getValueTrace(var);
}
static PyObject* THPSize_pynew(
PyTypeObject* type,
PyObject* args,
PyObject* kwargs) {
HANDLE_TH_ERRORS
THPObjectPtr self(PyTuple_Type.tp_new(type, args, kwargs));
if (self) {
for (Py_ssize_t i = 0; i < PyTuple_Size(self); ++i) {
PyObject* item = PyTuple_GET_ITEM(self.get(), i);
if (THPUtils_checkLong(item)) {
continue;
}
if (torch::is_symint(item)) {
continue;
}
if (torch::jit::tracer::isTracing() && isTracedZeroDimVar(item)) {
continue;
}
// item.__index__() works with 0-dim tensors and tensors with one element
THPObjectPtr number(PyNumber_Index(item));
if (number && THPUtils_checkLong(number.get())) {
Py_INCREF(number.get());
auto status = PyTuple_SetItem(self, i, number.get());
if (status != 0) {
throw python_error();
}
continue;
}
return PyErr_Format(
PyExc_TypeError,
"torch.Size() takes an iterable of 'int' (item %zd is '%s')",
i,
Py_TYPE(item)->tp_name);
}
}
return self.release();
END_HANDLE_TH_ERRORS
}
static PyObject* THPSize_repr(THPSize* self) {
HANDLE_TH_ERRORS
std::string repr("torch.Size([");
for (Py_ssize_t i = 0; i < PyTuple_Size((PyObject*)self); ++i) {
if (i != 0) {
repr += ", ";
}
auto item = PyTuple_GET_ITEM(self, i);
auto ih = py::handle(item);
repr += torch::is_symint(ih)
? std::string(py::str(ih))
: std::to_string(THPUtils_unpackLong(PyTuple_GET_ITEM(self, i)));
}
repr += "])";
return THPUtils_packString(repr);
END_HANDLE_TH_ERRORS
}
extern PyTypeObject THPSizeType;
template <typename FnType, FnType fn, typename... Args>
static PyObject* wrap_tuple_fn(Args... args) {
THPObjectPtr result((*fn)(std::forward<Args>(args)...));
if (!result)
return nullptr;
if (PyTuple_Check(result.get())) {
return PyObject_CallFunctionObjArgs(
(PyObject*)&THPSizeType, result.get(), nullptr);
}
return result.release();
}
// We use an anonymous namespace instead of static to work around
// (what @peterjc123 think is) a bug in Visual Studio
namespace {
auto sq_concat = PyTuple_Type.tp_as_sequence->sq_concat;
auto sq_repeat = PyTuple_Type.tp_as_sequence->sq_repeat;
binaryfunc mp_subscript = PyTuple_Type.tp_as_mapping->mp_subscript;
} // namespace
static PySequenceMethods THPSize_as_sequence = {
nullptr, /* sq_length */
wrap_tuple_fn<decltype(&sq_concat), &sq_concat>,
wrap_tuple_fn<decltype(&sq_repeat), &sq_repeat>,
nullptr, /* sq_item */
nullptr, /* sq_slice */
nullptr, /* sq_ass_item */
nullptr, /* sq_ass_slice */
nullptr /* sq_contains */
};
static PyMappingMethods THPSize_as_mapping = {
nullptr, /* mp_length */
wrap_tuple_fn<decltype(&mp_subscript), &mp_subscript>,
nullptr};
static PyObject* THPSize_numel(PyObject* _self, PyObject* noargs) {
HANDLE_TH_ERRORS
auto self = (THPSize*)_self;
int64_t numel = 1;
for (Py_ssize_t i = 0; i < PyTuple_Size((PyObject*)self); ++i) {
numel *= THPUtils_unpackLong(PyTuple_GET_ITEM(self, i));
}
return THPUtils_packInt64(numel);
END_HANDLE_TH_ERRORS
}
static PyObject* THPSize_reduce(PyObject* _self, PyObject* noargs) {
HANDLE_TH_ERRORS
auto self = (THPSize*)_self;
auto ret = THPObjectPtr{PyTuple_New(2)};
if (!ret)
throw python_error();
auto obj = (PyObject*)(&THPSizeType);
Py_INCREF(&THPSizeType);
PyTuple_SET_ITEM(ret.get(), 0, obj);
THPObjectPtr t(PyTuple_New(PyTuple_Size((PyObject*)self)));
if (!t)
throw python_error();
for (Py_ssize_t i = 0; i < PyTuple_Size((PyObject*)self); ++i) {
auto d = PyTuple_GET_ITEM(self, i);
Py_INCREF(d);
PyTuple_SET_ITEM(t.get(), i, d);
}
THPObjectPtr dims(Py_BuildValue("(O)", t.get()));
if (!dims)
throw python_error();
PyTuple_SET_ITEM(ret.get(), 1, dims.release());
return ret.release();
END_HANDLE_TH_ERRORS
}
// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables,modernize-avoid-c-arrays,cppcoreguidelines-avoid-c-arrays)
static PyMethodDef THPSize_methods[] = {
{"numel", THPSize_numel, METH_NOARGS, nullptr},
{"__reduce__", THPSize_reduce, METH_NOARGS, nullptr},
{nullptr}};
PyTypeObject THPSizeType = {
PyVarObject_HEAD_INIT(nullptr, 0) "torch.Size", /* tp_name */
sizeof(THPSize), /* tp_basicsize */
0, /* tp_itemsize */
nullptr, /* tp_dealloc */
0, /* tp_vectorcall_offset */
nullptr, /* tp_getattr */
nullptr, /* tp_setattr */
nullptr, /* tp_reserved */
(reprfunc)THPSize_repr, /* tp_repr */
nullptr, /* tp_as_number */
&THPSize_as_sequence, /* tp_as_sequence */
&THPSize_as_mapping, /* tp_as_mapping */
nullptr, /* tp_hash */
nullptr, /* tp_call */
nullptr, /* tp_str */
nullptr, /* tp_getattro */
nullptr, /* tp_setattro */
nullptr, /* tp_as_buffer */
Py_TPFLAGS_DEFAULT, /* tp_flags */
nullptr, /* tp_doc */
nullptr, /* tp_traverse */
nullptr, /* tp_clear */
nullptr, /* tp_richcompare */
0, /* tp_weaklistoffset */
nullptr, /* tp_iter */
nullptr, /* tp_iternext */
THPSize_methods, /* tp_methods */
nullptr, /* tp_members */
nullptr, /* tp_getset */
&PyTuple_Type, /* tp_base */
nullptr, /* tp_dict */
nullptr, /* tp_descr_get */
nullptr, /* tp_descr_set */
0, /* tp_dictoffset */
nullptr, /* tp_init */
nullptr, /* tp_alloc */
THPSize_pynew, /* tp_new */
};
void THPSize_init(PyObject* module) {
if (PyType_Ready(&THPSizeType) < 0) {
throw python_error();
}
Py_INCREF(&THPSizeType);
if (PyModule_AddObject(module, "Size", (PyObject*)&THPSizeType) < 0) {
throw python_error();
}
}