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Update initializers for typing in numpy 1.21+ #516

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Jul 1, 2021
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Update initializers for typing in numpy 1.21+ #516

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18 changes: 9 additions & 9 deletions thinc/initializers.py
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Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
from typing import Callable
from typing import Callable, cast
import numpy

from .backends import Ops
Expand All @@ -16,7 +16,7 @@

def lecun_normal_init(ops: Ops, shape: Shape) -> FloatsXd:
scale = numpy.sqrt(1.0 / shape[1])
return ops.asarray_f(numpy.random.normal(0, scale, shape))
return ops.asarray_f(cast(FloatsXd, numpy.random.normal(0, scale, shape)))


@registry.initializers("lecun_normal_init.v1")
Expand All @@ -26,7 +26,7 @@ def configure_lecun_normal_init() -> Callable[[Shape], FloatsXd]:

def he_normal_init(ops: Ops, shape: Shape) -> FloatsXd:
scale = numpy.sqrt(2.0 / shape[1])
return ops.asarray_f(numpy.random.normal(0, scale, shape))
return ops.asarray_f(cast(FloatsXd, numpy.random.normal(0, scale, shape)))


@registry.initializers("he_normal_init.v1")
Expand All @@ -36,7 +36,7 @@ def configure_he_normal_init() -> Callable[[Shape], FloatsXd]:

def glorot_normal_init(ops: Ops, shape: Shape) -> FloatsXd:
scale = numpy.sqrt(2.0 / (shape[1] + shape[0]))
return ops.asarray_f(numpy.random.normal(0, scale, shape))
return ops.asarray_f(cast(FloatsXd, numpy.random.normal(0, scale, shape)))


@registry.initializers("glorot_normal_init.v1")
Expand All @@ -46,7 +46,7 @@ def configure_glorot_normal_init() -> Callable[[Shape], FloatsXd]:

def he_uniform_init(ops: Ops, shape: Shape) -> FloatsXd:
scale = numpy.sqrt(6.0 / shape[1])
return ops.asarray_f(numpy.random.uniform(-scale, scale, shape))
return ops.asarray_f(cast(FloatsXd, numpy.random.uniform(-scale, scale, shape)))


@registry.initializers("he_uniform_init.v1")
Expand All @@ -56,7 +56,7 @@ def configure_he_uniform_init() -> Callable[[Shape], FloatsXd]:

def lecun_uniform_init(ops: Ops, shape: Shape) -> FloatsXd:
scale = numpy.sqrt(3.0 / shape[1])
return ops.asarray_f(numpy.random.uniform(-scale, scale, shape))
return ops.asarray_f(cast(FloatsXd, numpy.random.uniform(-scale, scale, shape)))


@registry.initializers("lecun_uniform_init.v1")
Expand All @@ -66,7 +66,7 @@ def configure_lecun_uniform_init() -> Callable[[Shape], FloatsXd]:

def glorot_uniform_init(ops: Ops, shape: Shape) -> FloatsXd:
scale = numpy.sqrt(6.0 / (shape[0] + shape[1]))
return ops.asarray_f(numpy.random.uniform(-scale, scale, shape))
return ops.asarray_f(cast(FloatsXd, numpy.random.uniform(-scale, scale, shape)))


@registry.initializers("glorot_uniform_init.v1")
Expand All @@ -87,7 +87,7 @@ def uniform_init(
ops: Ops, shape: Shape, *, lo: float = -0.1, hi: float = 0.1
) -> FloatsXd:
values = numpy.random.uniform(lo, hi, shape)
return ops.asarray_f(values.astype("float32"))
return ops.asarray_f(cast(FloatsXd, values.astype("float32")))


@registry.initializers("uniform_init.v1")
Expand All @@ -99,7 +99,7 @@ def configure_uniform_init(

def normal_init(ops: Ops, shape: Shape, *, mean: int = 0) -> FloatsXd:
size = int(ops.xp.prod(ops.xp.asarray(shape)))
inits = numpy.random.normal(scale=mean, size=size).astype("float32")
inits = cast(FloatsXd, numpy.random.normal(scale=mean, size=size).astype("float32"))
inits = ops.reshape_f(inits, shape)
return ops.asarray_f(inits)

Expand Down