import math
import warnings
import torch
import torch.backends.cudnn as cudnn
from torch._six import PY37
from ..nn.modules.utils import _single, _pair, _triple, _quadruple, _list_with_default
from collections import OrderedDict
from typing import Dict, Optional
_builtin_table: Optional[Dict[int, str]] = None
_modules_containing_builtins = (torch, torch._C._nn, torch._C._fft, torch._C._linalg) # type: ignore
_builtin_ops = [
# Pairs of (function, op_name)
(_pair, "aten::_pair"),
(_quadruple, "aten::_quadruple"),
(_single, "aten::_single"),
(_triple, "aten::_triple"),
(_list_with_default, "aten::list_with_default"),
(OrderedDict, "aten::dict"),
(dict, "aten::dict"),
(cudnn.is_acceptable, "aten::cudnn_is_acceptable"),
(math.ceil, "aten::ceil"),
(math.copysign, "aten::copysign"),
(math.erf, "aten::erf"),
(math.erfc, "aten::erfc"),
(math.exp, "aten::exp"),
(math.expm1, "aten::expm1"),
(math.fabs, "aten::fabs"),
(math.floor, "aten::floor"),
(math.gamma, "aten::gamma"),
(math.lgamma, "aten::lgamma"),
(math.log, "aten::log"),
(math.log10, "aten::log10"),
(math.log1p, "aten::log1p"),
(math.pow, "aten::pow"),
(math.sqrt, "aten::sqrt"),
(math.isnan, "aten::isnan"),
(math.asinh, "aten::asinh"),
(math.atanh, "aten::atanh"),
(math.cosh, "aten::cosh"),
(math.sinh, "aten::sinh"),
(math.tanh, "aten::tanh"),
(math.acos, "aten::acos"),
(math.asin, "aten::asin"),
(math.atan, "aten::atan"),
(math.atan2, "aten::atan2"),
(math.cos, "aten::cos"),
(math.sin, "aten::sin"),
(math.tan, "aten::tan"),
(math.asinh, "aten::asinh"),
(math.atanh, "aten::atanh"),
(math.acosh, "aten::acosh"),
(math.sinh, "aten::sinh"),
(math.cosh, "aten::cosh"),
(math.tanh, "aten::tanh"),
(math.fmod, "aten::fmod"),
(math.modf, "aten::modf"),
(math.factorial, "aten::factorial"),
(math.frexp, "aten::frexp"),
(math.isnan, "aten::isnan"),
(math.isinf, "aten::isinf"),
(math.degrees, "aten::degrees"),
(math.radians, "aten::radians"),
(math.ldexp, "aten::ldexp"),
(torch._assert, "aten::_assert"),
(torch.autograd.grad, "aten::grad"),
(torch.autograd.backward, "aten::backward"),
(torch._C._infer_size, "aten::_infer_size"),
(torch.nn.functional._no_grad_embedding_renorm_, "aten::_no_grad_embedding_renorm_"), # type: ignore
(torch.nn.functional.assert_int_or_pair, "aten::_assert_int_or_pair"),
(torch.nn.init._no_grad_fill_, "aten::_no_grad_fill_"),
(torch.nn.init._no_grad_normal_, "aten::_no_grad_normal_"),
(torch.nn.init._no_grad_uniform_, "aten::_no_grad_uniform_"),
(torch.nn.init._no_grad_zero_, "aten::_no_grad_zero_"),
(torch._C._get_tracing_state, "aten::_get_tracing_state"),
(warnings.warn, "aten::warn"),
(torch._VF.stft, "aten::stft"), # type: ignore
(torch._VF.istft, "aten::istft"), # type: ignore
(torch._VF.cdist, "aten::cdist"), # type: ignore
(torch._VF.norm, "aten::norm"), # type: ignore
(torch._VF.unique_dim, "aten::unique_dim"), # type: ignore
(torch._VF.unique_consecutive, "aten::unique_consecutive"), # type: ignore
(torch._VF.nuclear_norm, "aten::nuclear_norm"), # type: ignore
(torch._VF.frobenius_norm, "aten::frobenius_norm"), # type: ignore
]
# ops in torch.functional are bound to torch
# in these cases, we want to resolve the function to their python implementation
# instead looking up a builtin "aten::" schema
def _gen_torch_functional_registered_ops():
# eventually ops should encompass all of torch/functional.py, (torch.functional.__all__)
# but we are currently only able to compile some of the functions. additionally,
# some functions directly map to their aten:: implementations.
# TODO: add support for more ops
ops = ["stft", "istft", "lu", "lu_unpack", "cdist", "norm", "unique", "unique_consecutive"]
return set(getattr(torch.functional, name) for name in ops)
_functional_registered_ops = _gen_torch_functional_registered_ops()
def _is_special_functional_bound_op(fn):
return fn in _functional_registered_ops
# lazily built to ensure the correct initialization order
def _get_builtin_table():
global _builtin_table
if _builtin_table is not None:
return _builtin_table
_builtin_table = {}
def register_all(mod):
for name in dir(mod):
v = getattr(mod, name)
if callable(v) and not _is_special_functional_bound_op(v) and v is not torch.no_grad:
_builtin_ops.append((v, "aten::" + name))
for mod in _modules_containing_builtins:
register_all(mod)
_builtin_ops.append((math.gcd, "aten::gcd"))
_builtin_ops.append((math.isfinite, "aten::isfinite"))
if PY37:
_builtin_ops.append((math.remainder, "aten::mathremainder")) # type: ignore
import torch.distributed.autograd as dist_autograd
if dist_autograd.is_available():
_builtin_ops.append((dist_autograd.get_gradients, "aten::get_gradients")) # type: ignore
_builtin_ops.append((dist_autograd.backward, "aten::dist_backward")) # type: ignore
# populate the _builtin_table from _builtin_ops
for builtin, aten_op in _builtin_ops:
_builtin_table[id(builtin)] = aten_op
return _builtin_table
def _register_builtin(fn, op):
_get_builtin_table()[id(fn)] = op
def _find_builtin(fn):
return _get_builtin_table().get(id(fn))