Use "import numpy as np" in the array_api submodule

This avoids importing everything inside the individual functions, but still is
preferred over importing the functions used explicitly, as most of them clash
with the wrapper function names.

1 files changed, 13 insertions, 22 deletions

diff --git a/numpy/_array_api/_creation_functions.py b/numpy/_array_api/_creation_functions.py
index 4e91aa443..b74eca060 100644
--- a/numpy/_array_api/_creation_functions.py
+++ b/numpy/_array_api/_creation_functions.py
@@ -1,76 +1,67 @@
+import numpy as np
+
 def arange(start, /, *, stop=None, step=1, dtype=None, device=None):
-    from .. import arange
     if device is not None:
         # Note: Device support is not yet implemented on ndarray
         raise NotImplementedError("Device support is not yet implemented")
-    return arange(start, stop=stop, step=step, dtype=dtype)
+    return np.arange(start, stop=stop, step=step, dtype=dtype)
 
 def empty(shape, /, *, dtype=None, device=None):
-    from .. import empty
     if device is not None:
         # Note: Device support is not yet implemented on ndarray
         raise NotImplementedError("Device support is not yet implemented")
-    return empty(shape, dtype=dtype)
+    return np.empty(shape, dtype=dtype)
 
 def empty_like(x, /, *, dtype=None, device=None):
-    from .. import empty_like
     if device is not None:
         # Note: Device support is not yet implemented on ndarray
         raise NotImplementedError("Device support is not yet implemented")
-    return empty_like(x, dtype=dtype)
+    return np.empty_like(x, dtype=dtype)
 
 def eye(N, /, *, M=None, k=0, dtype=None, device=None):
-    from .. import eye
     if device is not None:
         # Note: Device support is not yet implemented on ndarray
         raise NotImplementedError("Device support is not yet implemented")
-    return eye(N, M=M, k=k, dtype=dtype)
+    return np.eye(N, M=M, k=k, dtype=dtype)
 
 def full(shape, fill_value, /, *, dtype=None, device=None):
-    from .. import full
     if device is not None:
         # Note: Device support is not yet implemented on ndarray
         raise NotImplementedError("Device support is not yet implemented")
-    return full(shape, fill_value, dtype=dtype)
+    return np.full(shape, fill_value, dtype=dtype)
 
 def full_like(x, fill_value, /, *, dtype=None, device=None):
-    from .. import full_like
     if device is not None:
         # Note: Device support is not yet implemented on ndarray
         raise NotImplementedError("Device support is not yet implemented")
-    return full_like(x, fill_value, dtype=dtype)
+    return np.full_like(x, fill_value, dtype=dtype)
 
 def linspace(start, stop, num, /, *, dtype=None, device=None, endpoint=True):
-    from .. import linspace
     if device is not None:
         # Note: Device support is not yet implemented on ndarray
         raise NotImplementedError("Device support is not yet implemented")
-    return linspace(start, stop, num, dtype=dtype, endpoint=endpoint)
+    return np.linspace(start, stop, num, dtype=dtype, endpoint=endpoint)
 
 def ones(shape, /, *, dtype=None, device=None):
-    from .. import ones
     if device is not None:
         # Note: Device support is not yet implemented on ndarray
         raise NotImplementedError("Device support is not yet implemented")
-    return ones(shape, dtype=dtype)
+    return np.ones(shape, dtype=dtype)
 
 def ones_like(x, /, *, dtype=None, device=None):
-    from .. import ones_like
     if device is not None:
         # Note: Device support is not yet implemented on ndarray
         raise NotImplementedError("Device support is not yet implemented")
-    return ones_like(x, dtype=dtype)
+    return np.ones_like(x, dtype=dtype)
 
 def zeros(shape, /, *, dtype=None, device=None):
-    from .. import zeros
     if device is not None:
         # Note: Device support is not yet implemented on ndarray
         raise NotImplementedError("Device support is not yet implemented")
-    return zeros(shape, dtype=dtype)
+    return np.zeros(shape, dtype=dtype)
 
 def zeros_like(x, /, *, dtype=None, device=None):
-    from .. import zeros_like
     if device is not None:
         # Note: Device support is not yet implemented on ndarray
         raise NotImplementedError("Device support is not yet implemented")
-    return zeros_like(x, dtype=dtype)
+    return np.zeros_like(x, dtype=dtype)