refactor and reduce float types for some functions, also add bitwise_xor

python/mxnet/ndarray/numpy/_op.py

@@ -36,7 +36,7 @@
            'linspace', 'logspace', 'expand_dims', 'tile', 'arange', 'split', 'vsplit', 'concatenate', 'append',
            'stack', 'vstack', 'column_stack', 'dstack', 'mean', 'maximum', 'minimum', 'swapaxes', 'clip', 'argmax',
            'argmin', 'std', 'var', 'indices', 'copysign', 'ravel', 'hanning', 'hamming', 'blackman', 'flip',
-           'around', 'hypot', 'rad2deg', 'deg2rad', 'unique', 'lcm', 'tril', 'identity', 'take',
+           'around', 'hypot', 'bitwise_xor', 'rad2deg', 'deg2rad', 'unique', 'lcm', 'tril', 'identity', 'take',
            'ldexp', 'vdot', 'inner', 'outer', 'equal', 'not_equal', 'greater', 'less', 'greater_equal', 'less_equal',
            'hsplit', 'rot90', 'einsum', 'true_divide', 'nonzero', 'shares_memory', 'may_share_memory', 'diff', 'resize',
            'nan_to_num']
@@ -4291,6 +4291,44 @@ def hypot(x1, x2, out=None, **kwargs):
     return _ufunc_helper(x1, x2, _npi.hypot, _np.hypot, _npi.hypot_scalar, None, out)
 
 
+@set_module('mxnet.ndarray.numpy')
+@wrap_np_binary_func
+def bitwise_xor(x1, x2, out=None, **kwargs):
+    r"""
+    Compute the bit-wise XOR of two arrays element-wise.
+
+    Parameters
+    ----------
+    x1, x2 : ndarray or scalar
+        Only integer and boolean types are handled. If x1.shape != x2.shape,
+        they must be broadcastable to a common shape (which becomes the shape of the output).
+    out : ndarray, optional
+        A location into which the result is stored. If provided, it must have a shape that the
+        inputs broadcast to. If not provided or None, a freshly-allocated array is returned.
+
+    Returns
+    -------
+    out : ndarray
+        Result.
+
+    Examples
+    --------
+ >>> np.bitwise_xor(13, 17)
+    28
+
+    >>> np.bitwise_xor(31, 5)
+    26
+    >>> np.bitwise_xor(np.array([31,3], dtype='int32'), 5)
+    array([26,  6])
+
+    >>> np.bitwise_xor(np.array([31,3], dtype='int32'), np.array([5,6], dtype='int32'))
+    array([26,  5])
+    >>> np.bitwise_xor(np.array([True, True], dtype='bool'), np.array([False, True], dtype='bool'))
+    array([ True, False])
+    """
+    return _ufunc_helper(x1, x2, _npi.bitwise_xor, _np.bitwise_xor, _npi.bitwise_xor_scalar, None, out)
+
+
 @set_module('mxnet.ndarray.numpy')
 @wrap_np_binary_func
 def ldexp(x1, x2, out=None, **kwargs):

python/mxnet/numpy/multiarray.py

@@ -54,8 +54,8 @@
            'tensordot', 'histogram', 'eye', 'linspace', 'logspace', 'expand_dims', 'tile', 'arange',
            'split', 'vsplit', 'concatenate', 'stack', 'vstack', 'column_stack', 'dstack', 'mean', 'maximum', 'minimum',
            'swapaxes', 'clip', 'argmax', 'argmin', 'std', 'var', 'indices', 'copysign', 'ravel', 'hanning', 'hamming',
-           'blackman', 'flip', 'around', 'arctan2', 'hypot', 'rad2deg', 'deg2rad', 'unique', 'lcm', 'tril',
-           'identity', 'take', 'ldexp', 'vdot', 'inner', 'outer', 'equal', 'not_equal', 'greater', 'less',
+           'blackman', 'flip', 'around', 'arctan2', 'hypot', 'bitwise_xor', 'rad2deg', 'deg2rad', 'unique', 'lcm',
+           'tril', 'identity', 'take', 'ldexp', 'vdot', 'inner', 'outer', 'equal', 'not_equal', 'greater', 'less',
            'greater_equal', 'less_equal', 'hsplit', 'rot90', 'einsum', 'true_divide', 'nonzero', 'shares_memory',
            'may_share_memory', 'diff', 'resize', 'nan_to_num']
 
@@ -6198,6 +6198,44 @@ def hypot(x1, x2, out=None, **kwargs):
     return _mx_nd_np.hypot(x1, x2, out=out)
 
 
+@set_module('mxnet.numpy')
+@wrap_np_binary_func
+def bitwise_xor(x1, x2, out=None, **kwargs):
+    r"""
+    Compute the bit-wise XOR of two arrays element-wise.
+
+    Parameters
+    ----------
+    x1, x2 : ndarray or scalar
+        Only integer and boolean types are handled. If x1.shape != x2.shape,
+        they must be broadcastable to a common shape (which becomes the shape of the output).
+    out : ndarray, optional
+        A location into which the result is stored. If provided, it must have a shape that the
+        inputs broadcast to. If not provided or None, a freshly-allocated array is returned.
+
+    Returns
+    -------
+    out : ndarray
+        Result.
+
+    Examples
+    --------
+    >>> np.bitwise_xor(13, 17)
+    28
+
+    >>> np.bitwise_xor(31, 5)
+    26
+    >>> np.bitwise_xor(np.array([31,3], dtype=np.int32), 5)
+    array([26,  6])
+
+    >>> np.bitwise_xor(np.array([31,3], dtype='int32'), np.array([5,6], dtype='int32'))
+    array([26,  5])
+    >>> np.bitwise_xor(np.array([True, True], dtype='bool'), np.array([False, True], dtype='bool'))
+    array([ True, False])
+    """
+    return _mx_nd_np.bitwise_xor(x1, x2, out=out)
+
+
 @set_module('mxnet.numpy')
 @wrap_np_binary_func
 def ldexp(x1, x2, out=None, **kwargs):

python/mxnet/symbol/numpy/_symbol.py

@@ -38,7 +38,7 @@
            'linspace', 'logspace', 'expand_dims', 'tile', 'arange', 'split', 'vsplit', 'concatenate', 'append',
            'stack', 'vstack', 'column_stack', 'dstack', 'mean', 'maximum', 'minimum', 'swapaxes', 'clip', 'argmax',
            'argmin', 'std', 'var', 'indices', 'copysign', 'ravel', 'hanning', 'hamming', 'blackman', 'flip',
-           'around', 'hypot', 'rad2deg', 'deg2rad', 'unique', 'lcm', 'tril', 'identity', 'take',
+           'around', 'hypot', 'bitwise_xor', 'rad2deg', 'deg2rad', 'unique', 'lcm', 'tril', 'identity', 'take',
            'ldexp', 'vdot', 'inner', 'outer', 'equal', 'not_equal', 'greater', 'less', 'greater_equal',
            'less_equal', 'hsplit', 'rot90', 'einsum', 'true_divide', 'shares_memory', 'may_share_memory', 'diff',
            'resize', 'nan_to_num']
@@ -4058,17 +4058,16 @@ def hypot(x1, x2, out=None, **kwargs):
 
     Parameters
     ----------
-    x1, x2 : array_like
+    x1, x2 : _Symbol or scalar
         Leg of the triangle(s).
-    out : ndarray, None, or tuple of ndarray and None, optional
+    out : _Symbol or None, optional
         A location into which the result is stored. If provided, it must have
         a shape that the inputs broadcast to. If not provided or `None`,
-        a freshly-allocated array is returned. A tuple (possible only as a
-        keyword argument) must have length equal to the number of outputs.
+        a freshly-allocated array is returned.
 
     Returns
     -------
-    z : ndarray
+    z : _Symbol or scalar
         The hypotenuse of the triangle(s).
         This is a scalar if both `x1` and `x2` are scalars.
 
@@ -4080,6 +4079,30 @@ def hypot(x1, x2, out=None, **kwargs):
     return _ufunc_helper(x1, x2, _npi.hypot, _np.hypot, _npi.hypot_scalar, None, out)
 
 
+@set_module('mxnet.symbol.numpy')
+@wrap_np_binary_func
+def bitwise_xor(x1, x2, out=None, **kwargs):
+    r"""
+    Compute the bit-wise XOR of two arrays element-wise.
+
+    Parameters
+    ----------
+    x1, x2 : _Symbol or scalar
+        Only integer and boolean types are handled. If x1.shape != x2.shape,
+        they must be broadcastable to a common shape (which becomes the shape of the output).
+    out : _Symbol or None, optional
+        A location into which the result is stored. If provided, it must have
+        a shape that the inputs broadcast to. If not provided or `None`,
+        a freshly-allocated array is returned.
+
+    Returns
+    -------
+    out : _Symbol or scalar
+        Result.
+    """
+    return _ufunc_helper(x1, x2, _npi.bitwise_xor, _np.bitwise_xor, _npi.bitwise_xor_scalar, None, out)
+
+
 @set_module('mxnet.symbol.numpy')
 def unique(ar, return_index=False, return_inverse=False, return_counts=False, axis=None):
     """

src/operator/elemwise_op_common.h

@@ -209,7 +209,8 @@ inline bool ElemwiseIntType(const nnvm::NodeAttrs& attrs,
   CHECK(in_attrs->at(0) == mshadow::kInt64 ||
         in_attrs->at(0) == mshadow::kInt32 ||
         in_attrs->at(0) == mshadow::kInt8 ||
-        in_attrs->at(0) == mshadow::kUint8) << "Only supports integer types.";
+        in_attrs->at(0) == mshadow::kUint8 ||
+        in_attrs->at(0) == mshadow::kBool) << "Only supports integer types.";
   if (n_in != -1) {
     CHECK_EQ(in_attrs->size(), static_cast<size_t>(n_in)) << " in operator " << attrs.name;
   }