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Renames ArrayApi into BaseArrayApi#16

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Merged
sdpython merged 1 commit intomainfromaapi
Jun 5, 2023
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86 changes: 43 additions & 43 deletionsonnx_array_api/npx/npx_array_api.py
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Expand Up@@ -13,7 +13,7 @@ class ArrayApiError(RuntimeError):
pass


classArrayApi:
classBaseArrayApi:
"""
List of supported method by a tensor.
"""
Expand All@@ -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 classArrayApi."
f"for all methods supported by classBaseArrayApi."
)

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):
Expand Down
6 changes: 3 additions & 3 deletionsonnx_array_api/npx/npx_functions.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -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 importArrayApi
from .npx_tensors importBaseArrayApi
from .npx_types import (
DType,
ElemType,
Expand DownExpand Up@@ -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
Expand DownExpand Up@@ -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)
Expand Down
10 changes: 5 additions & 5 deletionsonnx_array_api/npx/npx_tensors.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -3,7 +3,7 @@
import numpy as np
from onnx.helper import np_dtype_to_tensor_dtype

from .npx_array_api importArrayApi, ArrayApiError
from .npx_array_api importBaseArrayApi, ArrayApiError


class JitTensor:
Expand All@@ -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):
Expand DownExpand Up@@ -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__":
returnArrayApi.generic_method(self, method_name, *args, **kwargs)
returnBaseArrayApi.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)
Expand All@@ -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)

returnArrayApi.generic_method(self, method_name, *args, **kwargs)
returnBaseArrayApi.generic_method(self, method_name, *args, **kwargs)
4 changes: 2 additions & 2 deletionsonnx_array_api/npx/npx_var.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -4,7 +4,7 @@
from onnx import FunctionProto, ModelProto, NodeProto, TensorProto
from onnx.helper import np_dtype_to_tensor_dtype

from .npx_array_api importArrayApi, ArrayApiError
from .npx_array_api importBaseArrayApi, ArrayApiError
from .npx_constants import DEFAULT_OPSETS, ONNX_DOMAIN
from .npx_types import ElemType, OptParType, ParType, TensorType, TupleType

Expand DownExpand Up@@ -181,7 +181,7 @@ def to_onnx(
return onx


class Var(ArrayApi):
class Var(BaseArrayApi):
"""
Defines a variable, a result...

Expand Down
4 changes: 2 additions & 2 deletionsonnx_array_api/ort/ort_tensors.py
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Expand Up@@ -231,15 +231,15 @@ def get_ir_version(cls, ir_version):

class EagerOrtTensor(OrtTensor, OrtCommon, EagerTensor):
"""
Defines a value fora specific backend.
Defines a value for:epkg:`onnxruntime` as a backend.
"""

pass


class JitOrtTensor(OrtTensor, OrtCommon, JitTensor):
"""
Defines a value fora specific backend.
Defines a value for:epkg:`onnxruntime` as a backend.
"""

pass
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