rename ArrayApi into BaseArrayApi

sdpython · sdpython · Jun 10, 2023 · Jun 5, 2023 · Jun 5, 2023 · Jun 5, 2023
commit 945749ce4446efeede1c24e01d6e1884576163da
diff --git a/onnx_array_api/npx/npx_array_api.py b/onnx_array_api/npx/npx_array_api.py
@@ -13,7 +13,7 @@ class ArrayApiError(RuntimeError):
     pass
 
 
-class ArrayApi:
+class BaseArrayApi:
     """
     List of supported method by a tensor.
     """
@@ -36,145 +36,145 @@ def generic_method(self, method_name, *args: Any, **kwargs: Any) -> Any:
             f"for class {self.__class__.__name__!r}. "
             f"Method 'generic_method' can be overwritten "
             f"as well to change the behaviour "
-            f"for all methods supported by class ArrayApi."
+            f"for all methods supported by class BaseArrayApi."
         )
 
     def numpy(self) -> np.ndarray:
         return self.generic_method("numpy")
 
-    def __neg__(self) -> "ArrayApi":
+    def __neg__(self) -> "BaseArrayApi":
         return self.generic_method("__neg__")
 
-    def __invert__(self) -> "ArrayApi":
+    def __invert__(self) -> "BaseArrayApi":
         return self.generic_method("__invert__")
 
-    def __add__(self, ov: "ArrayApi") -> "ArrayApi":
+    def __add__(self, ov: "BaseArrayApi") -> "BaseArrayApi":
         return self.generic_method("__add__", ov)
 
-    def __radd__(self, ov: "ArrayApi") -> "ArrayApi":
+    def __radd__(self, ov: "BaseArrayApi") -> "BaseArrayApi":
         return self.generic_method("__radd__", ov)
 
-    def __sub__(self, ov: "ArrayApi") -> "ArrayApi":
+    def __sub__(self, ov: "BaseArrayApi") -> "BaseArrayApi":
         return self.generic_method("__sub__", ov)
 
-    def __rsub__(self, ov: "ArrayApi") -> "ArrayApi":
+    def __rsub__(self, ov: "BaseArrayApi") -> "BaseArrayApi":
         return self.generic_method("__rsub__", ov)
 
-    def __mul__(self, ov: "ArrayApi") -> "ArrayApi":
+    def __mul__(self, ov: "BaseArrayApi") -> "BaseArrayApi":
         return self.generic_method("__mul__", ov)
 
-    def __rmul__(self, ov: "ArrayApi") -> "ArrayApi":
+    def __rmul__(self, ov: "BaseArrayApi") -> "BaseArrayApi":
         return self.generic_method("__rmul__", ov)
 
-    def __matmul__(self, ov: "ArrayApi") -> "ArrayApi":
+    def __matmul__(self, ov: "BaseArrayApi") -> "BaseArrayApi":
         return self.generic_method("__matmul__", ov)
 
-    def __truediv__(self, ov: "ArrayApi") -> "ArrayApi":
+    def __truediv__(self, ov: "BaseArrayApi") -> "BaseArrayApi":
         return self.generic_method("__truediv__", ov)
 
-    def __rtruediv__(self, ov: "ArrayApi") -> "ArrayApi":
+    def __rtruediv__(self, ov: "BaseArrayApi") -> "BaseArrayApi":
         return self.generic_method("__rtruediv__", ov)
 
-    def __mod__(self, ov: "ArrayApi") -> "ArrayApi":
+    def __mod__(self, ov: "BaseArrayApi") -> "BaseArrayApi":
         return self.generic_method("__mod__", ov)
 
-    def __rmod__(self, ov: "ArrayApi") -> "ArrayApi":
+    def __rmod__(self, ov: "BaseArrayApi") -> "BaseArrayApi":
         return self.generic_method("__rmod__", ov)
 
-    def __pow__(self, ov: "ArrayApi") -> "ArrayApi":
+    def __pow__(self, ov: "BaseArrayApi") -> "BaseArrayApi":
         return self.generic_method("__pow__", ov)
 
-    def __rpow__(self, ov: "ArrayApi") -> "ArrayApi":
+    def __rpow__(self, ov: "BaseArrayApi") -> "BaseArrayApi":
         return self.generic_method("__rpow__", ov)
 
-    def __lt__(self, ov: "ArrayApi") -> "ArrayApi":
+    def __lt__(self, ov: "BaseArrayApi") -> "BaseArrayApi":
         return self.generic_method("__lt__", ov)
 
-    def __le__(self, ov: "ArrayApi") -> "ArrayApi":
+    def __le__(self, ov: "BaseArrayApi") -> "BaseArrayApi":
         return self.generic_method("__le__", ov)
 
-    def __gt__(self, ov: "ArrayApi") -> "ArrayApi":
+    def __gt__(self, ov: "BaseArrayApi") -> "BaseArrayApi":
         return self.generic_method("__gt__", ov)
 
-    def __ge__(self, ov: "ArrayApi") -> "ArrayApi":
+    def __ge__(self, ov: "BaseArrayApi") -> "BaseArrayApi":
         return self.generic_method("__ge__", ov)
 
-    def __eq__(self, ov: "ArrayApi") -> "ArrayApi":
+    def __eq__(self, ov: "BaseArrayApi") -> "BaseArrayApi":
         return self.generic_method("__eq__", ov)
 
-    def __ne__(self, ov: "ArrayApi") -> "ArrayApi":
+    def __ne__(self, ov: "BaseArrayApi") -> "BaseArrayApi":
         return self.generic_method("__ne__", ov)
 
-    def __lshift__(self, ov: "ArrayApi") -> "ArrayApi":
+    def __lshift__(self, ov: "BaseArrayApi") -> "BaseArrayApi":
         return self.generic_method("__lshift__", ov)
 
-    def __rshift__(self, ov: "ArrayApi") -> "ArrayApi":
+    def __rshift__(self, ov: "BaseArrayApi") -> "BaseArrayApi":
         return self.generic_method("__rshift__", ov)
 
-    def __and__(self, ov: "ArrayApi") -> "ArrayApi":
+    def __and__(self, ov: "BaseArrayApi") -> "BaseArrayApi":
         return self.generic_method("__and__", ov)
 
-    def __rand__(self, ov: "ArrayApi") -> "ArrayApi":
+    def __rand__(self, ov: "BaseArrayApi") -> "BaseArrayApi":
         return self.generic_method("__rand__", ov)
 
-    def __or__(self, ov: "ArrayApi") -> "ArrayApi":
+    def __or__(self, ov: "BaseArrayApi") -> "BaseArrayApi":
         return self.generic_method("__or__", ov)
 
-    def __ror__(self, ov: "ArrayApi") -> "ArrayApi":
+    def __ror__(self, ov: "BaseArrayApi") -> "BaseArrayApi":
         return self.generic_method("__ror__", ov)
 
-    def __xor__(self, ov: "ArrayApi") -> "ArrayApi":
+    def __xor__(self, ov: "BaseArrayApi") -> "BaseArrayApi":
         return self.generic_method("__xor__", ov)
 
-    def __rxor__(self, ov: "ArrayApi") -> "ArrayApi":
+    def __rxor__(self, ov: "BaseArrayApi") -> "BaseArrayApi":
         return self.generic_method("__rxor__", ov)
 
     @property
-    def T(self) -> "ArrayApi":
+    def T(self) -> "BaseArrayApi":
         return self.generic_method("T")
 
-    def astype(self, dtype: Any) -> "ArrayApi":
+    def astype(self, dtype: Any) -> "BaseArrayApi":
         return self.generic_method("astype", dtype)
 
     @property
-    def shape(self) -> "ArrayApi":
+    def shape(self) -> "BaseArrayApi":
         return self.generic_method("shape")
 
-    def reshape(self, shape: "ArrayApi") -> "ArrayApi":
+    def reshape(self, shape: "BaseArrayApi") -> "BaseArrayApi":
         return self.generic_method("reshape", shape)
 
     def sum(
         self, axis: OptParType[TupleType[int]] = None, keepdims: ParType[int] = 0
-    ) -> "ArrayApi":
+    ) -> "BaseArrayApi":
         return self.generic_method("sum", axis=axis, keepdims=keepdims)
 
     def mean(
         self, axis: OptParType[TupleType[int]] = None, keepdims: ParType[int] = 0
-    ) -> "ArrayApi":
+    ) -> "BaseArrayApi":
         return self.generic_method("mean", axis=axis, keepdims=keepdims)
 
     def min(
         self, axis: OptParType[TupleType[int]] = None, keepdims: ParType[int] = 0
-    ) -> "ArrayApi":
+    ) -> "BaseArrayApi":
         return self.generic_method("min", axis=axis, keepdims=keepdims)
 
     def max(
         self, axis: OptParType[TupleType[int]] = None, keepdims: ParType[int] = 0
-    ) -> "ArrayApi":
+    ) -> "BaseArrayApi":
         return self.generic_method("max", axis=axis, keepdims=keepdims)
 
     def prod(
         self, axis: OptParType[TupleType[int]] = None, keepdims: ParType[int] = 0
-    ) -> "ArrayApi":
+    ) -> "BaseArrayApi":
         return self.generic_method("prod", axis=axis, keepdims=keepdims)
 
-    def copy(self) -> "ArrayApi":
+    def copy(self) -> "BaseArrayApi":
         return self.generic_method("copy")
 
-    def flatten(self) -> "ArrayApi":
+    def flatten(self) -> "BaseArrayApi":
         return self.generic_method("flatten")
 
-    def __getitem__(self, index: Any) -> "ArrayApi":
+    def __getitem__(self, index: Any) -> "BaseArrayApi":
         return self.generic_method("__getitem__", index)
 
     def __setitem__(self, index: Any, values: Any):

diff --git a/onnx_array_api/npx/npx_functions.py b/onnx_array_api/npx/npx_functions.py
@@ -8,7 +8,7 @@
 
 from .npx_constants import FUNCTION_DOMAIN
 from .npx_core_api import cst, make_tuple, npxapi_inline, npxapi_no_inline, var
-from .npx_tensors import ArrayApi
+from .npx_tensors import BaseArrayApi
 from .npx_types import (
     DType,
     ElemType,
@@ -173,7 +173,7 @@ def asarray(
         raise RuntimeError("Method 'astype' should be used to change the type.")
     if order is not None:
         raise NotImplementedError(f"order={order!r} not implemented.")
-    if isinstance(a, ArrayApi):
+    if isinstance(a, BaseArrayApi):
         if copy:
             return a.__class__(a, copy=copy)
         return a
@@ -404,7 +404,7 @@ def isdtype(
     dtype: DType, kind: Union[DType, str, Tuple[Union[DType, str], ...]]
 ) -> bool:
     """
-    See :epkg:`ArrayAPI:isdtype`.
+    See :epkg:`BaseArrayAPI:isdtype`.
     This function is not converted into an onnx graph.
     """
     return np_array_api.isdtype(dtype, kind)

diff --git a/onnx_array_api/npx/npx_tensors.py b/onnx_array_api/npx/npx_tensors.py
@@ -3,7 +3,7 @@
 import numpy as np
 from onnx.helper import np_dtype_to_tensor_dtype
 
-from .npx_array_api import ArrayApi, ArrayApiError
+from .npx_array_api import BaseArrayApi, ArrayApiError
 
 
 class JitTensor:
@@ -14,11 +14,11 @@ class JitTensor:
     pass
 
 
-class EagerTensor(ArrayApi):
+class EagerTensor(BaseArrayApi):
     """
     Defines a value for a specific eager mode.
     An eager tensor must overwrite every call to a method listed in class
-    :class:`ArrayApi`.
+    :class:`BaseArrayApi`.
     """
 
     def __iter__(self):
@@ -215,7 +215,7 @@ def generic_method(self, method_name, *args: Any, **kwargs: Any) -> Any:
             return self._generic_method_getitem(method_name, *args, **kwargs)
 
         if method_name == "__setitem__":
-            return ArrayApi.generic_method(self, method_name, *args, **kwargs)
+            return BaseArrayApi.generic_method(self, method_name, *args, **kwargs)
 
         if method_name in {"mean", "sum", "min", "max", "prod"}:
             return self._generic_method_reduce(method_name, *args, **kwargs)
@@ -226,4 +226,4 @@ def generic_method(self, method_name, *args: Any, **kwargs: Any) -> Any:
         if method_name.startswith("__") and method_name.endswith("__"):
             return self._generic_method_operator(method_name, *args, **kwargs)
 
-        return ArrayApi.generic_method(self, method_name, *args, **kwargs)
+        return BaseArrayApi.generic_method(self, method_name, *args, **kwargs)
diff --git a/onnx_array_api/npx/npx_var.py b/onnx_array_api/npx/npx_var.py
@@ -4,7 +4,7 @@
 from onnx import FunctionProto, ModelProto, NodeProto, TensorProto
 from onnx.helper import np_dtype_to_tensor_dtype
 
-from .npx_array_api import ArrayApi, ArrayApiError
+from .npx_array_api import BaseArrayApi, ArrayApiError
 from .npx_constants import DEFAULT_OPSETS, ONNX_DOMAIN
 from .npx_types import ElemType, OptParType, ParType, TensorType, TupleType
 
@@ -181,7 +181,7 @@ def to_onnx(
         return onx
 
 
-class Var(ArrayApi):
+class Var(BaseArrayApi):
     """
     Defines a variable, a result...
 

diff --git a/onnx_array_api/ort/ort_tensors.py b/onnx_array_api/ort/ort_tensors.py
@@ -231,15 +231,15 @@ def get_ir_version(cls, ir_version):
 
 class EagerOrtTensor(OrtTensor, OrtCommon, EagerTensor):
     """
-    Defines a value for a specific backend.
+    Defines a value for :epkg:`onnxruntime` as a backend.
     """
 
     pass
 
 
 class JitOrtTensor(OrtTensor, OrtCommon, JitTensor):
     """
-    Defines a value for a specific backend.
+    Defines a value for :epkg:`onnxruntime` as a backend.
     """
 
     pass