From f49837803f161a2ecb71d69c2ea5bb3d8918ed87 Mon Sep 17 00:00:00 2001
From: Xingjian Shi <xshiab@connect.ust.hk>
Date: Tue, 2 Jun 2020 08:45:16 -0700
Subject: [PATCH] [Numpy] [Operator] Fix __neg__ (#18467)

* fix negation

* support boolean type

* Update elemwise_unary_op.h

* Update test_numpy_op.py
---
 python/mxnet/numpy/multiarray.py       |  2 +-
 python/mxnet/symbol/numpy/_symbol.py   |  2 +-
 tests/python/unittest/test_numpy_op.py | 21 +++++++++++++++++++--
 3 files changed, 21 insertions(+), 4 deletions(-)

diff --git a/python/mxnet/numpy/multiarray.py b/python/mxnet/numpy/multiarray.py
index 9073f3fca093..f6b4c8081645 100644
--- a/python/mxnet/numpy/multiarray.py
+++ b/python/mxnet/numpy/multiarray.py
@@ -985,7 +985,7 @@ def __mul__(self, other):
         return multiply(self, other)
 
     def __neg__(self):
-        return self.__mul__(-1.0)
+        return negative(self)
 
     @wrap_mxnp_np_ufunc
     def __imul__(self, other):
diff --git a/python/mxnet/symbol/numpy/_symbol.py b/python/mxnet/symbol/numpy/_symbol.py
index b37dd9da0d63..54c155006b04 100644
--- a/python/mxnet/symbol/numpy/_symbol.py
+++ b/python/mxnet/symbol/numpy/_symbol.py
@@ -280,7 +280,7 @@ def __rpow__(self, other):
 
     def __neg__(self):
         """x.__neg__() <=> - x"""
-        return self.__mul__(-1.0)
+        return negative(self)
 
     def __deepcopy__(self, _):
         return super(_Symbol, self).as_np_ndarray()
diff --git a/tests/python/unittest/test_numpy_op.py b/tests/python/unittest/test_numpy_op.py
index 572dd346ac04..2247700ff4f0 100644
--- a/tests/python/unittest/test_numpy_op.py
+++ b/tests/python/unittest/test_numpy_op.py
@@ -2373,10 +2373,10 @@ def hybrid_forward(self, F, a, *args, **kwargs):
                 return getattr(F.np, self._func)(a)
 
         np_func = getattr(_np, func)
-        mx_func = TestUnary(func)
         np_test_data = _np.random.uniform(low, high, shape).astype(_np.float32)
         mx_test_data = mx.numpy.array(np_test_data)
         for hybridize in [True, False]:
+            mx_func = TestUnary(func)
             if hybridize:
                 mx_func.hybridize()
             if ref_grad:
@@ -2420,13 +2420,30 @@ def hybrid_forward(self, F, a, *args, **kwargs):
         funcs['rad2deg'] = (lambda x: 180. / _np.pi * _np.ones(x.shape), -1.0, 1.0)
         funcs['deg2rad'] = (lambda x: _np.pi / 180. * _np.ones(x.shape), -1.0, 1.0)
     ndim = random.choice([2, 3, 4])
-    shape = random.choice([rand_shape_nd(ndim, dim=3), (1, 0, 2)])
     for shape in [rand_shape_nd(ndim, dim=3), (1, 0, 2)]:
         for func, func_data in funcs.items():
             ref_grad, low, high = func_data
             check_unary_func(func, ref_grad, shape, low, high)
 
 
+@use_np
+def test_negation():
+    class TestNegation(HybridBlock):
+        def hybrid_forward(self, F, a):
+            return -a
+    mx_func = TestNegation()
+    for dtype in [_np.int8, _np.int32, _np.float16, _np.float32, _np.float64]:
+        np_test_data = _np.random.uniform(-1, 1, (5, 5)).astype(dtype)
+        for hybridize in [True, False]:
+            mx_test_data = mx.numpy.array(np_test_data, dtype=dtype)
+            if hybridize:
+                mx_func.hybridize()
+            y = mx_func(mx_test_data)
+            assert y.shape == (5, 5)
+            assert y.dtype == dtype
+            assert_almost_equal(y.asnumpy(), -np_test_data)
+
+
 @with_seed()
 @use_np
 @retry(3)