forked from mindspore-Ecosystem/mindspore
fix array_creations
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76a37daa43
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@ -83,6 +83,8 @@ def array(obj, dtype=None, copy=True, ndmin=0):
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>>> print(np.array([1,2,3]))
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[1 2 3]
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"""
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if dtype is not None:
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dtype = _check_dtype(dtype)
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res = asarray(obj, dtype)
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if ndmin > res.ndim:
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@ -163,6 +165,8 @@ def asarray(a, dtype=None):
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>>> print(np.asarray([1,2,3]))
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[1 2 3]
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"""
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if dtype is not None:
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dtype = _check_dtype(dtype)
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if isinstance(a, Tensor):
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if dtype is None or dtype == a.dtype:
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return a
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@ -747,7 +747,7 @@ def array_equal(a1, a2, equal_nan=False):
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Returns `True` if input arrays have same shapes and all elements equal.
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Note:
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In mindpsore, a bool tensor is returned instead, since in Graph mode, the
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In mindspore, a bool tensor is returned instead, since in Graph mode, the
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value cannot be traced and computed at compile time.
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Since on Ascend, :class:`nan` is treated differently, currently the argument
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@ -793,7 +793,7 @@ def array_equiv(a1, a2):
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be broadcasted to create the same shape as the other one.
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Note:
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In mindpsore, a bool tensor is returned instead, since in Graph mode, the
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In mindspore, a bool tensor is returned instead, since in Graph mode, the
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value cannot be traced and computed at compile time.
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Args:
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