fix: Updated type annotations to use Optional when default paramete…

…r is `None`. (#27255)
ivy-llc · Nov 14, 2023 · cb8d76f · cb8d76f
1 parent d1d471d
commit cb8d76f
Show file tree

Hide file tree

Showing 37 changed files with 126 additions and 118 deletions.
diff --git a/ivy/data_classes/array/conversions.py b/ivy/data_classes/array/conversions.py
@@ -174,7 +174,7 @@ def to_native(
 
 def args_to_native(
     *args: Iterable[Any],
-    include_derived: Dict[str, bool] = None,
+    include_derived: Optional[Dict[str, bool]] = None,
     cont_inplace: bool = False,
     to_ignore: Optional[Union[type, Tuple[type]]] = None,
     **kwargs: Dict[str, Any],

diff --git a/ivy/data_classes/array/experimental/layers.py b/ivy/data_classes/array/experimental/layers.py
@@ -952,7 +952,7 @@ def reduce_window(
     def fft2(
         self: ivy.Array,
         *,
-        s: Sequence[int] = None,
+        s: Optional[Sequence[int]] = None,
         dim: Sequence[int] = (-2, -1),
         norm: str = "backward",
         out: Optional[ivy.Array] = None,
@@ -1144,8 +1144,8 @@ def rfft(
 
     def rfftn(
         self: ivy.Array,
-        s: Sequence[int] = None,
-        axes: Sequence[int] = None,
+        s: Optional[Sequence[int]] = None,
+        axes: Optional[Sequence[int]] = None,
         *,
         norm: str = "backward",
         out: Optional[ivy.Array] = None,
@@ -1291,7 +1291,7 @@ def max_unpool1d(
         kernel_size: Union[Tuple[int], int],
         /,
         *,
-        strides: Union[int, Tuple[int]] = None,
+        strides: Optional[Union[int, Tuple[int]]] = None,
         padding: Union[int, Tuple[int]] = 0,
         data_format: Optional[str] = "NCW",
     ) -> ivy.Array:

diff --git a/ivy/data_classes/array/experimental/manipulation.py b/ivy/data_classes/array/experimental/manipulation.py
@@ -217,7 +217,7 @@ def rot90(
         self: ivy.Array,
         /,
         *,
-        copy: bool = None,
+        copy: Optional[bool] = None,
         k: int = 1,
         axes: Tuple[int, int] = (0, 1),
         out: Optional[ivy.Array] = None,

diff --git a/ivy/data_classes/container/experimental/layers.py b/ivy/data_classes/container/experimental/layers.py
@@ -2753,7 +2753,7 @@ def static_max_unpool1d(
         kernel_size: Union[Tuple[int], int],
         /,
         *,
-        strides: Union[int, Tuple[int]] = None,
+        strides: Optional[Union[int, Tuple[int]]] = None,
         padding: Union[int, Tuple[int]] = 0,
         data_format: Union[str, ivy.Container] = "NCW",
         key_chains: Optional[Union[List[str], Dict[str, str], ivy.Container]] = None,
@@ -2817,7 +2817,7 @@ def max_unpool1d(
         kernel_size: Union[Tuple[int], int],
         /,
         *,
-        strides: Union[int, Tuple[int]] = None,
+        strides: Optional[Union[int, Tuple[int]]] = None,
         padding: Union[int, Tuple[int]] = 0,
         data_format: Optional[str] = "NCW",
     ) -> ivy.Container:

diff --git a/ivy/functional/backends/jax/experimental/layers.py b/ivy/functional/backends/jax/experimental/layers.py
@@ -778,7 +778,7 @@ def reduce_window(
 def fft2(
     x: JaxArray,
     *,
-    s: Sequence[int] = None,
+    s: Optional[Sequence[int]] = None,
     dim: Sequence[int] = (-2, -1),
     norm: str = "backward",
     out: Optional[JaxArray] = None,
@@ -873,8 +873,8 @@ def rfft(
 @with_unsupported_dtypes({"0.4.20 and below": ("float16", "complex")}, backend_version)
 def rfftn(
     x: JaxArray,
-    s: Sequence[int] = None,
-    axes: Sequence[int] = None,
+    s: Optional[Sequence[int]] = None,
+    axes: Optional[Sequence[int]] = None,
     *,
     norm: str = "backward",
     out: Optional[JaxArray] = None,

diff --git a/ivy/functional/backends/jax/general.py b/ivy/functional/backends/jax/general.py
@@ -66,7 +66,7 @@ def get_item(
     /,
     query: Union[JaxArray, Tuple],
     *,
-    copy: bool = None,
+    copy: Optional[bool] = None,
 ) -> JaxArray:
     if ivy.is_array(query) and ivy.is_bool_dtype(query):
         if not len(query.shape):

diff --git a/ivy/functional/backends/mxnet/manipulation.py b/ivy/functional/backends/mxnet/manipulation.py
@@ -111,7 +111,7 @@ def repeat(
     /,
     repeats: Union[(int, List[int])],
     *,
-    axis: int = None,
+    axis: Optional[int] = None,
     out: Optional[Union[(None, mx.ndarray.NDArray)]] = None,
 ) -> Union[(None, mx.ndarray.NDArray)]:
     raise IvyNotImplementedException()

diff --git a/ivy/functional/backends/numpy/creation.py b/ivy/functional/backends/numpy/creation.py
@@ -29,7 +29,7 @@ def arange(
     step: float = 1,
     *,
     dtype: Optional[np.dtype] = None,
-    device: str = None,
+    device: Optional[str] = None,
     out: Optional[np.ndarray] = None,
 ) -> np.ndarray:
     if dtype:
@@ -56,7 +56,7 @@ def asarray(
     *,
     copy: Optional[bool] = None,
     dtype: Optional[np.dtype] = None,
-    device: str = None,
+    device: Optional[str] = None,
     out: Optional[np.ndarray] = None,
 ) -> np.ndarray:
     ret = np.asarray(obj, dtype=dtype)
@@ -67,7 +67,7 @@ def empty(
     shape: Union[ivy.NativeShape, Sequence[int]],
     *,
     dtype: np.dtype,
-    device: str = None,
+    device: Optional[str] = None,
     out: Optional[np.ndarray] = None,
 ) -> np.ndarray:
     return np.empty(shape, dtype)
@@ -78,7 +78,7 @@ def empty_like(
     /,
     *,
     dtype: np.dtype,
-    device: str = None,
+    device: Optional[str] = None,
     out: Optional[np.ndarray] = None,
 ) -> np.ndarray:
     return np.empty_like(x, dtype=dtype)
@@ -92,7 +92,7 @@ def eye(
     k: int = 0,
     batch_shape: Optional[Union[int, Sequence[int]]] = None,
     dtype: np.dtype,
-    device: str = None,
+    device: Optional[str] = None,
     out: Optional[np.ndarray] = None,
 ) -> np.ndarray:
     if n_cols is None:
@@ -132,7 +132,7 @@ def full(
     fill_value: Union[int, float, bool],
     *,
     dtype: Optional[Union[ivy.Dtype, np.dtype]] = None,
-    device: str = None,
+    device: Optional[str] = None,
     out: Optional[np.ndarray] = None,
 ) -> np.ndarray:
     dtype = ivy.default_dtype(dtype=dtype, item=fill_value, as_native=True)
@@ -145,7 +145,7 @@ def full_like(
     fill_value: Number,
     *,
     dtype: np.dtype,
-    device: str = None,
+    device: Optional[str] = None,
     out: Optional[np.ndarray] = None,
 ) -> np.ndarray:
     return np.full_like(x, fill_value, dtype=dtype)
@@ -160,7 +160,7 @@ def linspace(
     axis: Optional[int] = None,
     endpoint: bool = True,
     dtype: np.dtype,
-    device: str = None,
+    device: Optional[str] = None,
     out: Optional[np.ndarray] = None,
 ) -> np.ndarray:
     if axis is None:
@@ -189,7 +189,7 @@ def ones(
     shape: Union[ivy.NativeShape, Sequence[int]],
     *,
     dtype: np.dtype,
-    device: str = None,
+    device: Optional[str] = None,
     out: Optional[np.ndarray] = None,
 ) -> np.ndarray:
     return np.ones(shape, dtype)
@@ -200,7 +200,7 @@ def ones_like(
     /,
     *,
     dtype: np.dtype,
-    device: str = None,
+    device: Optional[str] = None,
     out: Optional[np.ndarray] = None,
 ) -> np.ndarray:
     return np.ones_like(x, dtype=dtype)
@@ -222,7 +222,7 @@ def zeros(
     shape: Union[ivy.NativeShape, Sequence[int]],
     *,
     dtype: np.dtype,
-    device: str = None,
+    device: Optional[str] = None,
     out: Optional[np.ndarray] = None,
 ) -> np.ndarray:
     return np.zeros(shape, dtype)
@@ -233,7 +233,7 @@ def zeros_like(
     /,
     *,
     dtype: np.dtype,
-    device: str = None,
+    device: Optional[str] = None,
     out: Optional[np.ndarray] = None,
 ) -> np.ndarray:
     return np.zeros_like(x, dtype=dtype)
@@ -266,7 +266,7 @@ def one_hot(
     off_value: Optional[Number] = None,
     axis: Optional[int] = None,
     dtype: Optional[np.dtype] = None,
-    device: str = None,
+    device: Optional[str] = None,
     out: Optional[np.ndarray] = None,
 ) -> np.ndarray:
     on_none = on_value is None
@@ -310,6 +310,6 @@ def triu_indices(
     k: int = 0,
     /,
     *,
-    device: str = None,
+    device: Optional[str] = None,
 ) -> Tuple[np.ndarray]:
     return tuple(np.asarray(np.triu_indices(n=n_rows, k=k, m=n_cols)))
diff --git a/ivy/functional/backends/numpy/experimental/creation.py b/ivy/functional/backends/numpy/experimental/creation.py
@@ -32,7 +32,7 @@ def tril_indices(
     k: int = 0,
     /,
     *,
-    device: str = None,
+    device: Optional[str] = None,
 ) -> Tuple[np.ndarray, ...]:
     return tuple(np.asarray(np.tril_indices(n=n_rows, k=k, m=n_cols)))
 

diff --git a/ivy/functional/backends/numpy/experimental/layers.py b/ivy/functional/backends/numpy/experimental/layers.py
@@ -951,7 +951,7 @@ def ifft(
 def fft2(
     x: np.ndarray,
     *,
-    s: Sequence[int] = None,
+    s: Optional[Sequence[int]] = None,
     dim: Sequence[int] = (-2, -1),
     norm: str = "backward",
     out: Optional[np.ndarray] = None,
@@ -1041,8 +1041,8 @@ def rfft(
 
 def rfftn(
     x: np.ndarray,
-    s: Sequence[int] = None,
-    axes: Sequence[int] = None,
+    s: Optional[Sequence[int]] = None,
+    axes: Optional[Sequence[int]] = None,
     *,
     norm: str = "backward",
     out: Optional[np.ndarray] = None,

diff --git a/ivy/functional/backends/numpy/general.py b/ivy/functional/backends/numpy/general.py
@@ -34,7 +34,7 @@ def get_item(
     /,
     query: Union[np.ndarray, Tuple],
     *,
-    copy: bool = None,
+    copy: Optional[bool] = None,
 ) -> np.ndarray:
     return x.__getitem__(query)
 

diff --git a/ivy/functional/backends/numpy/random.py b/ivy/functional/backends/numpy/random.py
@@ -24,7 +24,7 @@ def random_uniform(
     high: Union[float, np.ndarray] = 1.0,
     shape: Optional[Union[ivy.NativeShape, Sequence[int], np.ndarray]] = None,
     dtype: np.dtype,
-    device: str = None,
+    device: Optional[str] = None,
     out: Optional[np.ndarray] = None,
     seed: Optional[int] = None,
 ) -> np.ndarray:
@@ -39,7 +39,7 @@ def random_normal(
     mean: Union[float, np.ndarray] = 0.0,
     std: Union[float, np.ndarray] = 1.0,
     shape: Optional[Union[ivy.NativeShape, Sequence[int]]] = None,
-    device: str = None,
+    device: Optional[str] = None,
     dtype: np.dtype,
     seed: Optional[int] = None,
     out: Optional[np.ndarray] = None,
@@ -60,7 +60,7 @@ def multinomial(
     batch_size: int = 1,
     probs: Optional[np.ndarray] = None,
     replace: bool = True,
-    device: str = None,
+    device: Optional[str] = None,
     seed: Optional[int] = None,
     out: Optional[np.ndarray] = None,
 ) -> np.ndarray:
@@ -95,7 +95,7 @@ def randint(
     /,
     *,
     shape: Optional[Union[ivy.NativeShape, Sequence[int]]] = None,
-    device: str = None,
+    device: Optional[str] = None,
     dtype: Optional[Union[np.dtype, ivy.Dtype]] = None,
     seed: Optional[int] = None,
     out: Optional[np.ndarray] = None,

diff --git a/ivy/functional/backends/paddle/experimental/layers.py b/ivy/functional/backends/paddle/experimental/layers.py
@@ -309,7 +309,7 @@ def fft(
     /,
     *,
     norm: Optional[str] = "backward",
-    n: Union[int, Tuple[int]] = None,
+    n: Optional[Union[int, Tuple[int]]] = None,
     out: Optional[paddle.Tensor] = None,
 ) -> paddle.Tensor:
     if not isinstance(dim, int):
@@ -414,7 +414,7 @@ def ifft(
     dim: int,
     *,
     norm: Optional[str] = "backward",
-    n: Union[int, Tuple[int]] = None,
+    n: Optional[Union[int, Tuple[int]]] = None,
     out: Optional[paddle.Tensor] = None,
 ) -> paddle.Tensor:
     raise IvyNotImplementedException()

diff --git a/ivy/functional/backends/paddle/experimental/norms.py b/ivy/functional/backends/paddle/experimental/norms.py
@@ -107,7 +107,7 @@ def batch_norm(
 
 @with_supported_dtypes({"2.5.2 and below": ("float32", "float64")}, backend_version)
 def l1_normalize(
-    x: paddle.Tensor, /, *, axis: int = None, out: paddle.Tensor = None
+    x: paddle.Tensor, /, *, axis: Optional[int] = None, out: paddle.Tensor = None
 ) -> paddle.Tensor:
     if not isinstance(x, paddle.Tensor):
         x = paddle.to_tensor(x)
@@ -131,7 +131,7 @@ def l1_normalize(
 
 
 def l2_normalize(
-    x: paddle.Tensor, /, *, axis: int = None, out: paddle.Tensor = None
+    x: paddle.Tensor, /, *, axis: Optional[int] = None, out: paddle.Tensor = None
 ) -> paddle.Tensor:
     raise IvyNotImplementedException()
 
@@ -164,6 +164,11 @@ def instance_norm(
 
 
 def lp_normalize(
-    x: paddle.Tensor, /, *, p: float = 2, axis: int = None, out: paddle.Tensor = None
+    x: paddle.Tensor,
+    /,
+    *,
+    p: float = 2,
+    axis: Optional[int] = None,
+    out: paddle.Tensor = None,
 ) -> paddle.Tensor:
     raise IvyNotImplementedException()
diff --git a/ivy/functional/backends/paddle/general.py b/ivy/functional/backends/paddle/general.py
@@ -95,7 +95,7 @@ def get_item(
     /,
     query: Union[paddle.Tensor, Tuple],
     *,
-    copy: bool = None,
+    copy: Optional[bool] = None,
 ) -> paddle.Tensor:
     if copy:
         x = paddle.clone(x)

diff --git a/ivy/functional/backends/paddle/linear_algebra.py b/ivy/functional/backends/paddle/linear_algebra.py
@@ -53,7 +53,7 @@ def cross(
     axisa: int = -1,
     axisb: int = -1,
     axisc: int = -1,
-    axis: int = None,
+    axis: Optional[int] = None,
     out: Optional[paddle.Tensor] = None,
 ) -> paddle.Tensor:
     def _cross(x1, x2, axisa, axisb, axisc, axis):
@@ -433,7 +433,7 @@ def tensorsolve(
     x2: paddle.Tensor,
     /,
     *,
-    axes: Union[int, Tuple[List[int], List[int]]] = None,
+    axes: Optional[Union[int, Tuple[List[int], List[int]]]] = None,
     out: Optional[paddle.Tensor] = None,
 ) -> paddle.Tensor:
     # Implemented as a composite function in ivy.functional.ivy.linear_algebra

diff --git a/ivy/functional/backends/paddle/manipulation.py b/ivy/functional/backends/paddle/manipulation.py
@@ -307,7 +307,7 @@ def repeat(
     /,
     repeats: Union[int, Iterable[int]],
     *,
-    axis: int = None,
+    axis: Optional[int] = None,
     out: Optional[paddle.Tensor] = None,
 ) -> paddle.Tensor:
     # handle the case when repeats contains 0 as paddle doesn't support it