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Add copy argument to Array.__array__ #20077

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Mar 5, 2024
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Add copy argument to Array.__array__ #20077

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6 changes: 4 additions & 2 deletions jax/_src/array.py
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Original file line number Diff line number Diff line change
Expand Up @@ -399,8 +399,10 @@ def is_fully_addressable(self) -> bool:
"""
return self.sharding.is_fully_addressable

def __array__(self, dtype=None, context=None):
return np.asarray(self._value, dtype=dtype)
def __array__(self, dtype=None, context=None, copy=None):
# copy argument is supported by np.asarray starting in numpy 2.0
kwds = {} if copy is None else {'copy': copy}
return np.asarray(self._value, dtype=dtype, **kwds)

def __dlpack__(self, *, stream: int | Any | None = None):
if len(self._arrays) != 1:
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3 changes: 2 additions & 1 deletion jax/_src/basearray.pyi
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Expand Up @@ -181,7 +181,8 @@ class Array(abc.ABC):
# Even though we don't always support the NumPy array protocol, e.g., for
# tracer types, for type checking purposes we must declare support so we
# implement the NumPy ArrayLike protocol.
def __array__(self) -> np.ndarray: ...
def __array__(self, dtype: Optional[np.dtype] = ...,
copy: Optional[bool] = ...) -> np.ndarray: ...
def __dlpack__(self) -> Any: ...

# JAX extensions
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4 changes: 2 additions & 2 deletions tests/lax_numpy_test.py
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Expand Up @@ -3465,7 +3465,7 @@ def testArrayOutputsArrays(self):
assert type(jnp.array(np.array([]))) is array.ArrayImpl

class NDArrayLike:
def __array__(self, dtype=None):
def __array__(self, dtype=None, copy=None):
return np.array([], dtype=dtype)
assert type(jnp.array(NDArrayLike())) is array.ArrayImpl

Expand All @@ -3478,7 +3478,7 @@ def __array__(self, dtype=None):
def testArrayMethod(self):
class arraylike:
dtype = np.dtype('float32')
def __array__(self, dtype=None):
def __array__(self, dtype=None, copy=None):
return np.array(3., dtype=dtype)
a = arraylike()
ans = jnp.array(a)
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