Numpy dispatch test of ......

python/mxnet/ndarray/numpy/_op.py

@@ -38,7 +38,7 @@
            'std', 'var', 'indices', 'copysign', 'ravel', 'hanning', 'hamming', 'blackman', 'flip',
            'around', 'hypot', 'rad2deg', 'deg2rad', 'unique', 'lcm', 'tril', 'identity', 'take',
            'ldexp', 'vdot', 'inner', 'outer', 'equal', 'not_equal', 'greater', 'less', 'greater_equal', 'less_equal',
-           'hsplit', 'rot90', 'einsum']
+           'hsplit', 'rot90', 'einsum', 'true_divide']
 
 
 @set_module('mxnet.ndarray.numpy')
@@ -337,10 +337,10 @@ def take(a, indices, axis=None, mode='raise', out=None):
     if mode not in ('wrap', 'clip', 'raise'):
         raise NotImplementedError(
             "function take does not support mode '{}'".format(mode))
-    if axis:
-        return _npi.take(a, indices, axis, mode, out)
-    else:
+    if axis is None:
         return _npi.take(_npi.reshape(a, -1), indices, 0, mode, out)
+    else:
+        return _npi.take(a, indices, axis, mode, out)
 # pylint: enable=redefined-outer-name
 
 
@@ -495,7 +495,11 @@ def unique(ar, return_index=False, return_inverse=False, return_counts=False, ax
     >>> u[indices]
     array([1., 2., 6., 4., 2., 3., 2.])
     """
-    return _npi.unique(ar, return_index, return_inverse, return_counts, axis)
+    ret = _npi.unique(ar, return_index, return_inverse, return_counts, axis)
+    if isinstance(ret, list):
+        return tuple(ret)
+    else:
+        return ret
 
 
 @set_module('mxnet.ndarray.numpy')
@@ -604,6 +608,36 @@ def divide(x1, x2, out=None, **kwargs):
                          _npi.rtrue_divide_scalar, out)
 
 
+@set_module('mxnet.ndarray.numpy')
+def true_divide(x1, x2, out=None):
+    """Returns a true division of the inputs, element-wise.
+
+    Instead of the Python traditional 'floor division', this returns a true
+    division.  True division adjusts the output type to present the best
+    answer, regardless of input types.
+
+    Parameters
+    ----------
+    x1 : ndarray or scalar
+        Dividend array.
+
+    x2 : ndarray or scalar
+        Divisor array.
+
+    out : ndarray
+        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 or scalar
+        This is a scalar if both x1 and x2 are scalars.
+    """
+    return _ufunc_helper(x1, x2, _npi.true_divide, _np.divide, _npi.true_divide_scalar,
+                         _npi.rtrue_divide_scalar, out)
+
+
 @set_module('mxnet.ndarray.numpy')
 @wrap_np_binary_func
 def mod(x1, x2, out=None, **kwargs):

python/mxnet/numpy/multiarray.py

@@ -55,7 +55,7 @@
            'swapaxes', 'clip', 'argmax', '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',
-           'greater_equal', 'less_equal', 'hsplit', 'rot90', 'einsum']
+           'greater_equal', 'less_equal', 'hsplit', 'rot90', 'einsum', 'true_divide']
 
 # Return code for dispatching indexing function call
 _NDARRAY_UNSUPPORTED_INDEXING = -1
@@ -2216,6 +2216,35 @@ def divide(x1, x2, out=None, **kwargs):
     return _mx_nd_np.divide(x1, x2, out=out)
 
 
+@set_module('mxnet.numpy')
+def true_divide(x1, x2, out=None):
+    """Returns a true division of the inputs, element-wise.
+
+    Instead of the Python traditional 'floor division', this returns a true
+    division.  True division adjusts the output type to present the best
+    answer, regardless of input types.
+
+    Parameters
+    ----------
+    x1 : ndarray or scalar
+        Dividend array.
+
+    x2 : ndarray or scalar
+        Divisor array.
+
+    out : ndarray
+        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 or scalar
+        This is a scalar if both x1 and x2 are scalars.
+    """
+    return _mx_nd_np.true_divide(x1, x2, out=out)
+
+
 @set_module('mxnet.numpy')
 @wrap_np_binary_func
 def mod(x1, x2, out=None, **kwargs):

python/mxnet/numpy/utils.py

@@ -23,7 +23,7 @@
 import numpy as onp
 
 __all__ = ['float16', 'float32', 'float64', 'uint8', 'int32', 'int8', 'int64',
-           'bool', 'bool_', 'pi', 'inf', 'nan']
+           'bool', 'bool_', 'pi', 'inf', 'nan', 'PZERO', 'NZERO']
 
 float16 = onp.float16
 float32 = onp.float32
@@ -38,3 +38,5 @@
 pi = onp.pi
 inf = onp.inf
 nan = onp.nan
+PZERO = onp.PZERO
+NZERO = onp.NZERO

python/mxnet/numpy_dispatch_protocol.py

@@ -84,6 +84,7 @@ def _run_with_array_ufunc_proto(*args, **kwargs):
 
 _NUMPY_ARRAY_FUNCTION_LIST = [
     'argmax',
+    'around',
     'broadcast_arrays',
     'broadcast_to',
     'clip',
@@ -93,6 +94,8 @@ def _run_with_array_ufunc_proto(*args, **kwargs):
     'dot',
     'expand_dims',
     'fix',
+    'flip',
+    'inner',
     'max',
     'mean',
     'min',
@@ -108,9 +111,11 @@ def _run_with_array_ufunc_proto(*args, **kwargs):
     'std',
     'sum',
     'swapaxes',
+    'take',
     'tensordot',
     'tile',
     'transpose',
+    'unique',
     'var',
     'zeros_like',
     'meshgrid',
@@ -161,11 +166,17 @@ def _register_array_function():
 
 # https://docs.scipy.org/doc/numpy/reference/ufuncs.html#available-ufuncs
 _NUMPY_ARRAY_UFUNC_LIST = [
+    'abs',
     'add',
+    'arctan2',
+    'copysign',
+    'degrees',
+    'hypot',
+    'lcm',
+    # 'ldexp',
     'subtract',
     'multiply',
-    # Uncomment divide when mxnet.numpy.true_divide is added
-    # 'divide',
+    'true_divide',
     'negative',
     'power',
     'mod',

python/mxnet/symbol/numpy/_symbol.py

@@ -40,7 +40,7 @@
            'std', 'var', 'indices', 'copysign', 'ravel', 'hanning', 'hamming', 'blackman', 'flip',
            'around', 'hypot', 'rad2deg', 'deg2rad', 'unique', 'lcm', 'tril', 'identity', 'take',
            'ldexp', 'vdot', 'inner', 'outer', 'equal', 'not_equal', 'greater', 'less', 'greater_equal',
-           'less_equal', 'hsplit', 'rot90', 'einsum']
+           'less_equal', 'hsplit', 'rot90', 'einsum', 'true_divide']
 
 
 def _num_outputs(sym):
@@ -1082,10 +1082,10 @@ def take(a, indices, axis=None, mode='raise', out=None):
     if mode not in ('wrap', 'clip', 'raise'):
         raise NotImplementedError(
             "function take does not support mode '{}'".format(mode))
-    if axis:
-        return _npi.take(a, indices, axis, mode, out)
-    else:
+    if axis is None:
         return _npi.take(_npi.reshape(a, -1), indices, 0, mode, out)
+    else:
+        return _npi.take(a, indices, axis, mode, out)
 # pylint: enable=redefined-outer-name
 
 
@@ -1164,6 +1164,12 @@ def divide(x1, x2, out=None, **kwargs):
                          _npi.rtrue_divide_scalar, out)
 
 
+@set_module('mxnet.ndarray.numpy')
+def true_divide(x1, x2, out=None):
+    return _ufunc_helper(x1, x2, _npi.true_divide, _np.divide, _npi.true_divide_scalar,
+                         _npi.rtrue_divide_scalar, out)
+
+
 @set_module('mxnet.symbol.numpy')
 @wrap_np_binary_func
 def mod(x1, x2, out=None, **kwargs):