MAINT: rm dead code from decorators.py

Author: ev-br

torch_np/_decorators.py

@@ -82,58 +82,3 @@ def wrapped(x1, x2, *args, **kwds):
 
     return wrapped
 
-
-def axis_keepdims_wrapper(func):
-    """`func` accepts an array-like as a 1st arg, returns a tensor.
-
-    This decorator implements the generic handling of axis, out and keepdims
-    arguments for reduction functions.
-
-    Note that we peel off `out=...` and `keepdims=...` args (torch functions never
-    see them). The `axis` argument we normalize and pass through to pytorch functions.
-
-    """
-    # TODO: sort out function signatures: how they flow through all decorators etc
-    @functools.wraps(func)
-    def wrapped(a, axis=None, keepdims=NoValue, *args, **kwds):
-        from ._ndarray import asarray, ndarray
-
-        tensor = asarray(a).get()
-
-        # standardize the axis argument
-        if isinstance(axis, ndarray):
-            axis = operator.index(axis)
-
-        result = _util.axis_expand_func(func, tensor, axis, *args, **kwds)
-
-        if keepdims:
-            result = _util.apply_keepdims(result, axis, tensor.ndim)
-
-        return result
-
-    return wrapped
-
-
-def axis_none_ravel_wrapper(func):
-    """`func` accepts an array-like as a 1st arg, returns a tensor.
-
-    This decorator implements the generic handling of axis=None acting on a
-    raveled array. One use is cumprod / cumsum. concatenate also uses a
-    similar logic.
-
-    """
-
-    @functools.wraps(func)
-    def wrapped(a, axis=None, *args, **kwds):
-        from ._ndarray import asarray, ndarray
-
-        tensor = asarray(a).get()
-
-        # standardize the axis argument
-        if isinstance(axis, ndarray):
-            axis = operator.index(axis)
-
-        result = _util.axis_ravel_func(func, tensor, axis, *args, **kwds)
-        return result
-
-    return wrapped