diff --git a/numpy-stubs/__init__.pyi b/numpy-stubs/__init__.pyi
index 0847317..b6c4b0d 100644
--- a/numpy-stubs/__init__.pyi
+++ b/numpy-stubs/__init__.pyi
@@ -7,6 +7,7 @@ from typing import (
     Any,
     ByteString,
     Container,
+    Callable,
     Dict,
     IO,
     Iterable,
@@ -485,6 +486,90 @@ def zeros(
 def ones(
     shape: _ShapeLike, dtype: _DtypeLike = ..., order: Optional[str] = ...
 ) -> ndarray: ...
+def zeros_like(
+    a: _ArrayLike,
+    dtype: Optional[dtype] = ...,
+    order: str = ...,
+    subok: bool = ...,
+    shape: Optional[Union[int, Sequence[int]]] = ...,
+) -> ndarray: ...
+def ones_like(
+    a: _ArrayLike,
+    dtype: Optional[dtype] = ...,
+    order: str = ...,
+    subok: bool = ...,
+    shape: Optional[_ShapeLike] = ...,
+) -> ndarray[int]: ...
+def full(
+    shape: _ShapeLike, fill_value: Any, dtype: Optional[dtype] = ..., order: str = ...
+) -> ndarray: ...
+def full_like(
+    a: _ArrayLike,
+    fill_value: Any,
+    dtype: Optional[dtype] = ...,
+    order: str = ...,
+    subok: bool = ...,
+    shape: Optional[_ShapeLike] = ...,
+) -> ndarray: ...
+def count_nonzero(
+    a: _ArrayLike, axis: Optional[Union[int, Tuple[int], Tuple[int, int]]] = ...
+) -> Union[int, ndarray]: ...
+def isfortran(a: ndarray) -> bool: ...
+def argwhere(a: _ArrayLike) -> ndarray: ...
+def flatnonzero(a: _ArrayLike) -> ndarray: ...
+def correlate(a: _ArrayLike, v: _ArrayLike, mode: str = ...) -> ndarray: ...
+def convolve(a: _ArrayLike, v: _ArrayLike, mode: str = ...) -> ndarray: ...
+def outer(a: _ArrayLike, b: _ArrayLike, out: ndarray = ...) -> ndarray: ...
+def tensordot(
+    a: _ArrayLike,
+    b: _ArrayLike,
+    axes: Union[
+        int, Tuple[int, int], Tuple[Tuple[int, int], ...], Tuple[List[int, int], ...]
+    ] = ...,
+) -> ndarray: ...
+def roll(
+    a: _ArrayLike,
+    shift: Union[int, Tuple[int, ...]],
+    axis: Optional[Union[int, Tuple[int, ...]]] = ...,
+) -> ndarray: ...
+def rollaxis(a: _ArrayLike, axis: int, start: int = ...) -> ndarray: ...
+def moveaxis(
+    a: ndarray,
+    source: Union[int, Sequence[int]],
+    destination: Union[int, Sequence[int]],
+) -> ndarray: ...
+def cross(
+    a: _ArrayLike,
+    b: _ArrayLike,
+    axisa: int = ...,
+    axisb: int = ...,
+    axisc: int = ...,
+    axis: Optional[int] = ...,
+) -> ndarray: ...
+def indices(
+    dimensions: Sequence[int], dtype: dtype = ..., sparse: bool = ...
+) -> Union[ndarray, Tuple[ndarray, ...]]: ...
+def fromfunction(function: Callable, shape: Tuple[int, int], **kwargs) -> Any: ...
+def isscalar(element: Any) -> bool: ...
+def binary_repr(num: int, width: Optional[int] = ...) -> str: ...
+def base_repr(number: int, base: int = ..., padding: int = ...) -> str: ...
+def identity(n: int, dtype: Optional[dtype] = ...) -> ndarray: ...
+def allclose(
+    a: _ArrayLike,
+    b: _ArrayLike,
+    rtol: float = ...,
+    atol: float = ...,
+    equal_nan: bool = ...,
+) -> bool: ...
+def isclose(
+    a: _ArrayLike,
+    b: _ArrayLike,
+    rtol: float = ...,
+    atol: float = ...,
+    equal_nan: bool = ...,
+) -> Union[bool_, ndarray]: ...
+def array_equal(a1: _ArrayLike, a2: _ArrayLike) -> bool: ...
+def array_equiv(a1: _ArrayLike, a2: _ArrayLike) -> bool: ...
 
 # TODO(shoyer): remove when the full numpy namespace is defined
 def __getattr__(name: str) -> Any: ...
diff --git a/numpy-stubs/core/numeric.pyi b/numpy-stubs/core/numeric.pyi
deleted file mode 100644
index 1e43676..0000000
--- a/numpy-stubs/core/numeric.pyi
+++ /dev/null
@@ -1,111 +0,0 @@
-from types import ModuleType
-from typing import (
-    Sequence,
-    Optional,
-    TypeVar,
-    Union,
-    Tuple,
-    List,
-    Iterable,
-    Callable,
-    Any,
-)
-
-from numpy import ndarray, dtype, _ArrayLike, _ShapeLike
-
-_T = TypeVar("_T")
-
-def zeros_like(
-    a: _ArrayLike,
-    dtype: Optional[dtype] = ...,
-    order: str = ...,
-    subok: bool = ...,
-    shape: Optional[Union[int, Sequence[int]]] = ...,
-) -> ndarray[int]: ...
-def ones(
-    shape: _ShapeLike, dtype: Optional[dtype] = ..., order: str = ...
-) -> ndarray[int]: ...
-def ones_like(
-    a: _ArrayLike,
-    dtype: Optional[dtype] = ...,
-    order: str = ...,
-    subok: bool = ...,
-    shape: Optional[_ShapeLike] = ...,
-) -> ndarray[int]: ...
-def full(
-    shape: _ShapeLike, fill_value: _T, dtype: Optional[dtype] = ..., order: str = ...
-) -> ndarray[_T]: ...
-def full_like(
-    a: _ArrayLike,
-    fill_value: _T,
-    dtype: Optional[dtype] = ...,
-    order: str = ...,
-    subok: bool = ...,
-    shape: Optional[_ShapeLike] = ...,
-) -> ndarray[_T]: ...
-def count_nonzero(
-    a: _ArrayLike, axis: Optional[Union[int, Tuple[int], Tuple[int, int]]] = ...
-) -> Union[int, ndarray[int]]: ...
-def isfortran(a: ndarray) -> bool: ...
-def argwhere(a: _ArrayLike) -> ndarray: ...
-def flatnonzero(a: _ArrayLike) -> ndarray: ...
-def correlate(a: _ArrayLike, v: _ArrayLike, mode: str = ...) -> ndarray: ...
-def convolve(a: _ArrayLike, v: _ArrayLike, mode: str = ...) -> ndarray: ...
-def outer(a: _ArrayLike, b: _ArrayLike, out: ndarray = ...) -> ndarray: ...
-def tensordot(
-    a: _ArrayLike,
-    b: _ArrayLike,
-    axes: Union[
-        int, Tuple[int, int], Tuple[Tuple[int, int], ...], Tuple[List[int, int], ...]
-    ] = ...,
-) -> ndarray: ...
-def roll(
-    a: _ArrayLike,
-    shift: Union[int, Tuple[int, ...]],
-    axis: Optional[Union[int, Tuple[int, ...]]] = ...,
-) -> _T: ...
-def rollaxis(a: _ArrayLike, axis: int, start: int = ...) -> ndarray: ...
-def normalize_axis_tuple(
-    axis: Union[int, Iterable[int]],
-    ndim: int,
-    argname: Optional[str] = ...,
-    allow_duplicate: bool = ...,
-) -> Tuple[int, ...]: ...
-def moveaxis(
-    a: ndarray,
-    source: Union[int, Sequence[int]],
-    destination: Union[int, Sequence[int]],
-) -> ndarray: ...
-def cross(
-    a: _ArrayLike,
-    b: _ArrayLike,
-    axisa: int = ...,
-    axisb: int = ...,
-    axisc: int = ...,
-    axis: Optional[int] = ...,
-) -> ndarray: ...
-def indices(
-    dimensions: Sequence[int], dtype: dtype = ..., sparse: bool = ...
-) -> Union[ndarray, Tuple[ndarray, ...]]: ...
-def fromfunction(function: Callable, shape: Tuple[int, int], **kwargs) -> Any: ...
-def isscalar(element: Any) -> bool: ...
-def binary_repr(num: int, width: Optional[int] = ...) -> str: ...
-def base_repr(number: int, base: int = ..., padding: int = ...) -> str: ...
-def identity(n: int, dtype: Optional[dtype] = ...) -> ndarray: ...
-def allclose(
-    a: _ArrayLike,
-    b: _ArrayLike,
-    rtol: float = ...,
-    atol: float = ...,
-    equal_nan: bool = ...,
-) -> bool: ...
-def isclose(
-    a: _ArrayLike,
-    b: _ArrayLike,
-    rtol: float = ...,
-    atol: float = ...,
-    equal_nan: bool = ...,
-) -> _ArrayLike: ...
-def array_equal(a1: _ArrayLike, a2: _ArrayLike) -> bool: ...
-def array_equiv(a1: _ArrayLike, a2: _ArrayLike) -> bool: ...
-def extend_all(module: ModuleType): ...