Fix dtype bug (apache#16467)

* fix dtype bug

* override dtype property; add tests

* fix display bug

python/mxnet/numpy/multiarray.py

@@ -706,7 +706,7 @@ def __repr__(self):
             if dtype == _np.float32:
                 array_str = array_str[:array_str.rindex(',')] + ')'
         elif dtype not in (_np.float32, _np.bool_):
-            array_str = array_str[:-1] + ', dtype={})'.format(dtype.__name__)
+            array_str = array_str[:-1] + ', dtype={})'.format(dtype)
 
         context = self.context
         if context.device_type == 'cpu':
@@ -1680,6 +1680,26 @@ def size(self):
         """Number of elements in the array."""
         return super(ndarray, self).size
 
+    @property
+    def dtype(self):
+        """Data-type of the array's elements.
+
+        Returns
+        -------
+        numpy.dtype
+            This NDArray's data type.
+
+        Examples
+        --------
+        >>> x = np.zeros((2,3))
+        >>> x.dtype
+        dtype('float32')
+        >>> y = np.zeros((2,3), dtype='int32')
+        >>> y.dtype
+        dtype('int32')
+        """
+        return _np.dtype(super(ndarray, self).dtype)
+
     def tostype(self, stype):
         raise AttributeError('mxnet.numpy.ndarray object has no attribute tostype')
 

tests/python/unittest/test_numpy_ndarray.py

@@ -1075,6 +1075,29 @@ def test_boolean_indexing_autograd():
     test_boolean_indexing_autograd()
 
 
+@with_seed()
+@use_np
+def test_np_get_dtype():
+    dtypes = [_np.int8, _np.int32, _np.float16, _np.float32, _np.float64, _np.bool, _np.bool_,
+              'int8', 'int32', 'float16', 'float32', 'float64', 'bool', None]
+    objects = [
+        [],
+        (),
+        [[1, 2], [3, 4]],
+        _np.random.uniform(size=rand_shape_nd(3)),
+        _np.random.uniform(size=(3, 0, 4))
+    ]
+    for dtype in dtypes:
+        for src in objects:
+            mx_arr = np.array(src, dtype=dtype)
+            assert mx_arr.ctx == mx.current_context()
+            if isinstance(src, mx.nd.NDArray):
+                np_arr = _np.array(src.asnumpy(), dtype=dtype if dtype is not None else _np.float32)
+            else:
+                np_arr = _np.array(src, dtype=dtype if dtype is not None else _np.float32)
+            assert type(mx_arr.dtype) == type(np_arr.dtype)
+
+
 if __name__ == '__main__':
     import nose
     nose.runmodule()