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Migrate random glue_lowering to overload where easy #8061

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Merged
sklam merged 9 commits into from
Aug 17, 2022
Merged

Migrate random glue_lowering to overload where easy #8061

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bea6f65
Migrate random `glue_lowering` to `overload` where easy
apmasell May 17, 2022
ba597b0
Fix missing array overrides
apmasell Jun 1, 2022
189c9ae
Relax types on hypergeometric
apmasell Jun 2, 2022
fe6fd8e
Add missing tests and remove unncessary type checks
apmasell Jul 18, 2022
4fa48fa
Fix parameter names and test `size=None`
apmasell Jul 20, 2022
c100b2f
Create special unit tests for gamma distribution over array
apmasell Jul 25, 2022
f8684a9
Ensure logseries works on 32-bit
apmasell Jul 26, 2022
74bfeae
Add test for remaining random array implementations
apmasell Jul 27, 2022
f5c5b8f
Add test for vonmises random array
apmasell Aug 4, 2022
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104 changes: 5 additions & 99 deletions numba/core/typing/randomdecl.py
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Original file line number Diff line number Diff line change
Expand Up @@ -33,7 +33,7 @@ def normalize_shape(shape):
if isinstance(shape, types.Integer):
return types.intp, 1
elif (isinstance(shape, types.BaseTuple) and
all(isinstance(v, types.Integer)) for v in shape):
all(isinstance(v, types.Integer) for v in shape)):
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ndim = len(shape)
return types.UniTuple(types.intp, ndim), ndim
else:
Expand Down Expand Up @@ -96,6 +96,7 @@ def concrete_scalar_typer(*args, **kwargs):
class Random_getrandbits(ConcreteTemplate):
cases = [signature(types.uint64, types.int32)]


@glue_typing(random.random, typing_key="random.random")
@glue_typing(np.random.random, typing_key="np.random.random")
class Random_random(ConcreteRandomTemplate):
Expand All @@ -106,6 +107,7 @@ def typer(size=None):
return self.array_typer(size)()
return typer


if numpy_version >= (1, 17):
glue_typing(
np.random.random_sample,
Expand All @@ -125,6 +127,7 @@ def typer(size=None):
class Random_randint(ConcreteTemplate):
cases = [signature(tp, tp, tp) for tp in _int_types]


@glue_typing(np.random.randint, typing_key="np.random.randint")
class Random_randint(ConcreteRandomTemplate):
cases = [signature(tp, tp) for tp in _int_types]
Expand All @@ -142,6 +145,7 @@ class Random_randrange(ConcreteTemplate):
cases += [signature(tp, tp, tp) for tp in _int_types]
cases += [signature(tp, tp, tp, tp) for tp in _int_types]


@glue_typing(random.seed, typing_key="random.seed")
@glue_typing(np.random.seed, typing_key="np.random.seed")
class Random_seed(ConcreteTemplate):
Expand All @@ -152,28 +156,6 @@ class Random_seed(ConcreteTemplate):
# Distributions
#

@glue_typing(np.random.geometric, typing_key="np.random.geometric")
@glue_typing(np.random.logseries, typing_key="np.random.logseries")
@glue_typing(np.random.zipf, typing_key="np.random.zipf")
class Numpy_geometric(ConcreteRandomTemplate):
cases = [signature(types.int64, tp) for tp in _float_types]

def generic(self):
def typer(a, size=None):
return self.array_typer(size)(a)
return typer

@glue_typing(np.random.binomial, typing_key="np.random.binomial")
@glue_typing(np.random.negative_binomial,
typing_key="np.random.negative_binomial")
class Numpy_negative_binomial(ConcreteRandomTemplate):
cases = [signature(types.int64, types.int64, tp) for tp in _float_types]

def generic(self):
def typer(n, p, size=None):
return self.array_typer(size)(n, p)
return typer

@glue_typing(np.random.poisson, typing_key="np.random.poisson")
class Numpy_poisson(ConcreteRandomTemplate):
cases = [signature(types.int64, tp) for tp in _float_types]
Expand All @@ -184,29 +166,7 @@ def typer(lam=None, size=None):
return self.array_typer(size)(lam)
return typer

@glue_typing(np.random.exponential, typing_key="np.random.exponential")
@glue_typing(np.random.rayleigh, typing_key="np.random.rayleigh")
class Numpy_exponential(ConcreteRandomTemplate):
cases = [signature(tp, tp) for tp in _float_types]
cases += [signature(tp) for tp in _float_types]

def generic(self):
def typer(scale=None, size=None):
return self.array_typer(size)(scale)
return typer

@glue_typing(np.random.hypergeometric, typing_key="np.random.hypergeometric")
class Numpy_hypergeometric(ConcreteRandomTemplate):
cases = [signature(tp, tp, tp, tp) for tp in _int_types]

def generic(self):
def typer(ngood, nbad, nsample, size=None):
return self.array_typer(size)(ngood, nbad, nsample)
return typer

@glue_typing(np.random.laplace, typing_key="np.random.laplace")
@glue_typing(np.random.logistic, typing_key="np.random.logistic")
@glue_typing(np.random.lognormal, typing_key="np.random.lognormal")
@glue_typing(np.random.normal, typing_key="np.random.normal")
class Numpy_normal(ConcreteRandomTemplate):
cases = [signature(tp, tp, tp) for tp in _float_types]
Expand All @@ -218,40 +178,11 @@ def typer(loc=None, scale=None, size=None):
return self.array_typer(size)(loc, scale)
return typer

@glue_typing(np.random.gamma, typing_key="np.random.gamma")
class Numpy_gamma(ConcreteRandomTemplate):
cases = [signature(tp, tp, tp) for tp in _float_types]
cases += [signature(tp, tp) for tp in _float_types]

def generic(self):
def typer(shape, scale=None, size=None):
return self.array_typer(size)(shape, scale)
return typer

@glue_typing(np.random.triangular, typing_key="np.random.triangular")
class Random_ternary_distribution(ConcreteRandomTemplate):
cases = [signature(tp, tp, tp, tp) for tp in _float_types]

def generic(self):
def typer(left, mode, right, size=None):
return self.array_typer(size)(left, mode, right)
return typer


@glue_typing(np.random.beta, typing_key="np.random.beta")
@glue_typing(np.random.f, typing_key="np.random.f")
@glue_typing(np.random.gumbel, typing_key="np.random.gumbel")
@glue_typing(np.random.uniform, typing_key="np.random.uniform")
@glue_typing(np.random.vonmises, typing_key="np.random.vonmises")
@glue_typing(np.random.wald, typing_key="np.random.wald")
@glue_typing(random.betavariate, typing_key="random.betavariate")
@glue_typing(random.gammavariate, typing_key="random.gammavariate")
@glue_typing(random.gauss, typing_key="random.gauss")
@glue_typing(random.lognormvariate, typing_key="random.lognormvariate")
@glue_typing(random.normalvariate, typing_key="random.normalvariate")
@glue_typing(random.uniform, typing_key="random.uniform")
@glue_typing(random.vonmisesvariate, typing_key="random.vonmisesvariate")
@glue_typing(random.weibullvariate, typing_key="random.weibullvariate")
class Random_binary_distribution(ConcreteRandomTemplate):
cases = [signature(tp, tp, tp) for tp in _float_types]

Expand All @@ -261,27 +192,7 @@ def typer(a, b, size=None):
return typer


@glue_typing(np.random.chisquare, typing_key="np.random.chisquare")
@glue_typing(np.random.pareto, typing_key="np.random.pareto")
@glue_typing(np.random.power, typing_key="np.random.power")
@glue_typing(np.random.standard_gamma, typing_key="np.random.standard_gamma")
@glue_typing(np.random.standard_t, typing_key="np.random.standard_t")
@glue_typing(np.random.weibull, typing_key="np.random.weibull")
@glue_typing(random.expovariate, typing_key="random.expovariate")
@glue_typing(random.paretovariate, typing_key="random.paretovariate")
class Random_unary_distribution(ConcreteRandomTemplate):
cases = [signature(tp, tp) for tp in _float_types]

def generic(self):
def typer(a, size=None):
return self.array_typer(size)(a)
return typer


@glue_typing(np.random.standard_cauchy, typing_key="np.random.standard_cauchy")
@glue_typing(np.random.standard_normal, typing_key="np.random.standard_normal")
@glue_typing(np.random.standard_exponential,
typing_key="np.random.standard_exponential")
class Random_nullary_distribution(ConcreteRandomTemplate):
cases = [signature(tp) for tp in _float_types]

Expand All @@ -291,10 +202,5 @@ def typer(size=None):
return typer


@glue_typing(random.triangular, typing_key="random.triangular")
class Random_triangular(ConcreteTemplate):
cases = [signature(tp, tp, tp) for tp in _float_types]
cases += [signature(tp, tp, tp, tp) for tp in _float_types]

# NOTE: some functions can have @overloads in numba.targets.randomimpl,
# and therefore don't need a typing declaration here.
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