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forked from M-Labs/nac3
nac3/nac3standalone/demo/interpret_demo.py

282 lines
7.1 KiB
Python
Executable File

#!/usr/bin/env python3
import sys
import importlib.util
import importlib.machinery
import math
import numpy as np
import numpy.typing as npt
import scipy as sp
import pathlib
from numpy import int32, int64, uint32, uint64
from scipy import special
from typing import TypeVar, Generic, Literal, Union
T = TypeVar('T')
class Option(Generic[T]):
_nac3_option: T
def __init__(self, v: T):
self._nac3_option = v
def is_none(self):
return self._nac3_option is None
def is_some(self):
return not self.is_none()
def unwrap(self):
return self._nac3_option
def __repr__(self) -> str:
if self.is_none():
return "none"
else:
return "Some({})".format(repr(self._nac3_option))
def __str__(self) -> str:
if self.is_none():
return "none"
else:
return "Some({})".format(str(self._nac3_option))
def Some(v: T) -> Option[T]:
return Option(v)
none = Option(None)
class _ConstGenericMarker:
pass
def ConstGeneric(name, constraint):
return TypeVar(name, _ConstGenericMarker, constraint)
N = TypeVar("N", bound=np.uint64)
class _NDArrayDummy(Generic[T, N]):
pass
# https://stackoverflow.com/questions/67803260/how-to-create-a-type-alias-with-a-throw-away-generic
NDArray = Union[npt.NDArray[T], _NDArrayDummy[T, N]]
def _bool(x):
if isinstance(x, np.ndarray):
return np.bool_(x)
else:
return bool(x)
def _float(x):
if isinstance(x, np.ndarray):
return np.float_(x)
else:
return float(x)
def round_away_zero(x):
if isinstance(x, np.ndarray):
return np.vectorize(round_away_zero)(x)
else:
if x >= 0.0:
return math.floor(x + 0.5)
else:
return math.ceil(x - 0.5)
def _floor(x):
if isinstance(x, np.ndarray):
return np.vectorize(_floor)(x)
else:
return math.floor(x)
def _ceil(x):
if isinstance(x, np.ndarray):
return np.vectorize(_ceil)(x)
else:
return math.ceil(x)
def patch(module):
def dbl_nan():
return np.nan
def dbl_inf():
return np.inf
def output_asciiart(x):
if x < 0:
sys.stdout.write("\n")
else:
sys.stdout.write(" .,-:;i+hHM$*#@ "[x])
def output_float(x):
print("%f" % x)
def output_strln(x):
print(x, end='')
def dbg_stack_address(_):
return 0
def extern(fun):
name = fun.__name__
if name == "dbl_nan":
return dbl_nan
elif name == "dbl_inf":
return dbl_inf
elif name == "output_asciiart":
return output_asciiart
elif name == "output_float64":
return output_float
elif name == "output_str":
return output_strln
elif name in {
"output_bool",
"output_int32",
"output_int64",
"output_int32_list",
"output_uint32",
"output_uint64",
"output_strln",
"output_range",
}:
return print
elif name == "dbg_stack_address":
return dbg_stack_address
else:
raise NotImplementedError
module.int32 = int32
module.int64 = int64
module.uint32 = uint32
module.uint64 = uint64
module.bool = _bool
module.float = _float
module.TypeVar = TypeVar
module.ConstGeneric = ConstGeneric
module.Generic = Generic
module.Literal = Literal
module.extern = extern
module.Option = Option
module.Some = Some
module.none = none
# Builtin Math functions
module.round = round_away_zero
module.round64 = round_away_zero
module.np_round = np.round
module.floor = _floor
module.floor64 = _floor
module.np_floor = np.floor
module.ceil = _ceil
module.ceil64 = _ceil
module.np_ceil = np.ceil
# NumPy NDArray factory functions
module.ndarray = NDArray
module.np_ndarray = np.ndarray
module.np_empty = np.empty
module.np_zeros = np.zeros
module.np_ones = np.ones
module.np_full = np.full
module.np_eye = np.eye
module.np_identity = np.identity
module.np_array = np.array
# NumPy Math functions
module.np_isnan = np.isnan
module.np_isinf = np.isinf
module.np_min = np.min
module.np_minimum = np.minimum
module.np_argmin = np.argmin
module.np_max = np.max
module.np_maximum = np.maximum
module.np_argmax = np.argmax
module.np_sin = np.sin
module.np_cos = np.cos
module.np_exp = np.exp
module.np_exp2 = np.exp2
module.np_log = np.log
module.np_log10 = np.log10
module.np_log2 = np.log2
module.np_fabs = np.fabs
module.np_trunc = np.trunc
module.np_sqrt = np.sqrt
module.np_rint = np.rint
module.np_tan = np.tan
module.np_arcsin = np.arcsin
module.np_arccos = np.arccos
module.np_arctan = np.arctan
module.np_sinh = np.sinh
module.np_cosh = np.cosh
module.np_tanh = np.tanh
module.np_arcsinh = np.arcsinh
module.np_arccosh = np.arccosh
module.np_arctanh = np.arctanh
module.np_expm1 = np.expm1
module.np_cbrt = np.cbrt
module.np_arctan2 = np.arctan2
module.np_copysign = np.copysign
module.np_fmax = np.fmax
module.np_fmin = np.fmin
module.np_ldexp = np.ldexp
module.np_hypot = np.hypot
module.np_nextafter = np.nextafter
# NumPy view functions
module.np_broadcast_to = np.broadcast_to
module.np_reshape = np.reshape
module.np_transpose = np.transpose
# NumPy NDArray property getter functions
module.np_size = np.size
module.np_shape = np.shape
module.np_strides = lambda ndarray: ndarray.strides
# SciPy Math functions
module.sp_spec_erf = special.erf
module.sp_spec_erfc = special.erfc
module.sp_spec_gamma = special.gamma
module.sp_spec_gammaln = special.gammaln
module.sp_spec_j0 = special.j0
module.sp_spec_j1 = special.j1
# Linalg functions
module.np_dot = np.dot
module.np_linalg_cholesky = np.linalg.cholesky
module.np_linalg_qr = np.linalg.qr
module.np_linalg_svd = np.linalg.svd
module.np_linalg_inv = np.linalg.inv
module.np_linalg_pinv = np.linalg.pinv
module.np_linalg_matrix_power = np.linalg.matrix_power
module.np_linalg_det = np.linalg.det
module.sp_linalg_lu = lambda x: sp.linalg.lu(x, True)
module.sp_linalg_schur = sp.linalg.schur
module.sp_linalg_hessenberg = lambda x: sp.linalg.hessenberg(x, True)
def file_import(filename, prefix="file_import_"):
filename = pathlib.Path(filename)
modname = prefix + filename.stem
path = str(filename.resolve().parent)
sys.path.insert(0, path)
try:
spec = importlib.util.spec_from_loader(
modname,
importlib.machinery.SourceFileLoader(modname, str(filename)),
)
module = importlib.util.module_from_spec(spec)
patch(module)
spec.loader.exec_module(module)
finally:
sys.path.remove(path)
return module
def main():
demo = file_import(sys.argv[1])
demo.run()
if __name__ == "__main__":
main()