pytorch/torch/csrc/Size.cpp
Edward Yang 517c7c9861 Canonicalize all includes in PyTorch. (#14849)
Summary:
Anywhere we used #include "foo.h", we now say #include <foo.h>
Paths are adjusted to be rooted out of aten/src, torch/lib, or
the root level directory.

I modified CMakeLists.txt by hand to remove TH and THC from
the include paths.

I used the following script to do the canonicalization:

```
  import subprocess
  import re
  import os.path

  files = subprocess.check_output(['git', 'ls-files']).decode('utf-8').rstrip().split('\n')
  for fn in files:
      if not any(fn.endswith(suff) for suff in ['.cu', '.cpp', '.in', '.h', '.hpp', '.cu', '.cuh', '.cc']):
          continue
      if not any(fn.startswith(pref) for pref in ["aten/", "torch/"]):
          continue
      with open(fn, 'r') as f:
          c = f.read()
      def fmt(p):
          return "#include <{}>".format(p)
      def repl(m):
          p = m.group(1)
          if p in ["dlfcn.h", "unistd.h", "nvrtc.h", "cuda.h", "cuda_runtime.h", "cstdint", "cudnn.h", "Python.h", "cusparse.h", "cuda_runtime_api.h", "cuda_fp16.h", "cublas_v2.h", "stdint.h", "curand_kernel.h"]:
              return fmt(p)
          if any(p.startswith(pref) for pref in ["torch/csrc", "c10/", "ATen/", "caffe2/", "TH/", "THC/", "Eigen/", "gtest/", "zdl/", "gloo/", "onnx/", "miopen/"]):
              return fmt(p)
          for root in ["aten/src", "torch/lib", ""]:
              for bad_root in [os.path.dirname(fn), "aten/src/TH", "aten/src/THC", "torch/csrc"]:
                  new_p = os.path.relpath(os.path.join(bad_root, p), root)
                  if not new_p.startswith("../") and (os.path.exists(os.path.join(root, new_p)) or os.path.exists(os.path.join(root, new_p + ".in"))):
                      return fmt(new_p)
          print("ERROR: ", fn, p)
          return m.group(0)
      new_c = re.sub(r'#include "([^"]+)"', repl, c)
      if new_c != c:
          print(fn)
          with open(fn, 'w') as f:
              f.write(new_c)
```

Signed-off-by: Edward Z. Yang <ezyang@fb.com>
Pull Request resolved: https://github.com/pytorch/pytorch/pull/14849

Reviewed By: dzhulgakov

Differential Revision: D13363445

Pulled By: ezyang

fbshipit-source-id: 52361f878a672785f9306c9e9ab2513128092b68
2018-12-08 19:38:30 -08:00

208 lines
7.2 KiB
C++

#include <torch/csrc/Size.h>
#include <string>
#include <torch/csrc/utils/object_ptr.h>
#include <torch/csrc/utils/python_strings.h>
#include <torch/csrc/utils/python_tuples.h>
#include <torch/csrc/autograd/python_variable.h>
#include <torch/csrc/jit/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 (int64_t i = 0; i < var.dim(); ++i) {
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(int 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();
}
static bool isTracedZeroDimVar(PyObject *item) {
if (!THPVariable_Check(item)) return false;
auto & var = reinterpret_cast<THPVariable*>(item)->cdata;
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::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 += ", ";
}
repr += std::to_string(PyLong_AsLong(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;
#if PY_MAJOR_VERSION == 2
auto sq_slice = PyTuple_Type.tp_as_sequence->sq_slice;
#endif
binaryfunc mp_subscript = PyTuple_Type.tp_as_mapping->mp_subscript;
}
static PySequenceMethods THPSize_as_sequence = {
PyTuple_Type.tp_as_sequence->sq_length,
wrap_tuple_fn<decltype(&sq_concat), &sq_concat>,
wrap_tuple_fn<decltype(&sq_repeat), &sq_repeat>,
PyTuple_Type.tp_as_sequence->sq_item,
#if PY_MAJOR_VERSION == 2
wrap_tuple_fn<decltype(&sq_slice), &sq_slice>,
#else
nullptr, /* sq_slice */
#endif
nullptr, /* sq_ass_item */
nullptr, /* sq_ass_slice */
PyTuple_Type.tp_as_sequence->sq_contains
};
static PyMappingMethods THPSize_as_mapping = {
PyTuple_Type.tp_as_mapping->mp_length,
wrap_tuple_fn<decltype(&mp_subscript), &mp_subscript>,
nullptr
};
static PyObject *THPSize_numel(THPSize *self)
{
HANDLE_TH_ERRORS
int64_t numel = 1;
for (Py_ssize_t i = 0; i < PyTuple_Size((PyObject*)self); ++i) {
numel *= PyLong_AsLong(PyTuple_GET_ITEM(self, i));
}
return THPUtils_packInt64(numel);
END_HANDLE_TH_ERRORS
}
static PyMethodDef THPSize_methods[] = {
{"numel", (PyCFunction)THPSize_numel, 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 */
nullptr, /* tp_print */
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();
}
}