Replacing `is` with `==` for the dtype check.

[pashu123]

Summary

a = np.ndarray([1,1]).astype(np.half)
a

array([[0.007812]], dtype=float16)

a.dtype

dtype('float16')

a.dtype == np.half

True

a.dtype == np.float16

True

a.dtype is np.float16

False

Checking with is leads to inconsistency in checking.

[silvas]

LGTM. Maybe add a comment with a link to here for context: https://stackoverflow.com/questions/26921836/correct-way-to-test-for-numpy-dtype

[pashu123]

Link for more context.

[pashu123]

minor comment placement.

mlir/python/mlir/runtime/np_to_memref.py

class C64(ctypes.Structure):
   _fields_ = [("real", ctypes.c_float), ("imag", ctypes.c_float)]
 
 
 class F16(ctypes.Structure):
   """A ctype representation for MLIR's Float16."""
   _fields_ = [("f16", ctypes.c_int16)]
 
 
+# https://stackoverflow.com/questions/26921836/correct-way-to-test-for-numpy-dtype
 def as_ctype(dtp):
   """Converts dtype to ctype."""
-  if dtp is np.dtype(np.complex128):
+  if dtp == np.dtype(np.complex128):
     return C128
-  if dtp is np.dtype(np.complex64):
+  if dtp == np.dtype(np.complex64):
     return C64
-  if dtp is np.dtype(np.float16):
+  if dtp == np.dtype(np.float16):
     return F16
   return np.ctypeslib.as_ctypes_type(dtp)
 
 
 def to_numpy(array):
   """Converts ctypes array back to numpy dtype array."""
   if array.dtype == C128:
     return array.view("complex128")