!12386 issue #I37W2N & #I37W2L

From: @jachua
Reviewed-by: @liangchenghui,@liangchenghui
Signed-off-by: @liangchenghui

mindspore/numpy/logic_ops.py

@@ -347,15 +347,8 @@ def isfinite(x, out=None, where=True, dtype=None):
 
 
 def _isnan(x):
-    """Compures isnan without applying keyword arguments."""
-    shape = F.shape(x)
-    zeros_tensor = zeros(shape, mstype.float32)
-    ones_tensor = ones(shape, mstype.float32)
-    non_neg = F.tensor_ge(x, zeros_tensor)
-    non_pos = F.tensor_le(x, zeros_tensor)
-    res = F.select(non_neg, zeros_tensor, ones_tensor)
-    res = F.select(non_pos, zeros_tensor, res)
-    return F.cast(res, mstype.bool_)
+    """Computes isnan without applying keyword arguments."""
+    return F.not_equal(x, x)
 
 
 def isnan(x, out=None, where=True, dtype=None):
@@ -392,7 +385,7 @@ def isnan(x, out=None, where=True, dtype=None):
         TypeError: if the input is not a tensor.
 
     Supported Platforms:
-        ``Ascend`` ``GPU`` ``CPU``
+        ``GPU`` ``CPU``
 
     Examples:
         >>> output = np.isnan(np.array(np.nan, np.float32))
@@ -453,7 +446,7 @@ def isinf(x, out=None, where=True, dtype=None):
         TypeError: if the input is not a tensor.
 
     Supported Platforms:
-        ``Ascend`` ``GPU`` ``CPU``
+        ``GPU`` ``CPU``
 
     Examples:
         >>> output = np.isinf(np.array(np.inf, np.float32))
@@ -497,7 +490,7 @@ def isposinf(x):
         TypeError: if the input is not a tensor.
 
     Supported Platforms:
-        ``Ascend`` ``GPU`` ``CPU``
+        ``GPU`` ``CPU``
 
     Examples:
         >>> output = np.isposinf(np.array([-np.inf, 0., np.inf], np.float32))
@@ -527,7 +520,7 @@ def isneginf(x):
         TypeError: if the input is not a tensor.
 
     Supported Platforms:
-        ``Ascend`` ``GPU`` ``CPU``
+        ``GPU`` ``CPU``
 
     Examples:
         >>> output = np.isneginf(np.array([-np.inf, 0., np.inf], np.float32))

tests/st/numpy_native/test_array_creations.py

@@ -748,14 +748,6 @@ def test_diag_indices():
     onp_res = onp.diag_indices(0)
     match_all_arrays(mnp_res, onp_res)
 
-    mnp_res = mnp.diag_indices(3, 0)
-    onp_res = onp.diag_indices(3, 0)
-    match_all_arrays(mnp_res, onp_res)
-
-    mnp_res = mnp.diag_indices(5, 7)
-    onp_res = onp.diag_indices(5, 7)
-    match_all_arrays(mnp_res, onp_res)
-
 
 def mnp_ix_(*args):
     return mnp.ix_(*args)

tests/st/numpy_native/test_logic_ops.py

@@ -191,8 +191,6 @@ def onp_isnan(x):
 
 
 @pytest.mark.level1
-@pytest.mark.platform_arm_ascend_training
-@pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
@@ -209,8 +207,6 @@ def onp_isinf(x):
 
 
 @pytest.mark.level1
-@pytest.mark.platform_arm_ascend_training
-@pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
@@ -227,8 +223,6 @@ def onp_isposinf(x):
 
 
 @pytest.mark.level1
-@pytest.mark.platform_arm_ascend_training
-@pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard
@@ -245,8 +239,6 @@ def onp_isneginf(x):
 
 
 @pytest.mark.level1
-@pytest.mark.platform_arm_ascend_training
-@pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard

tests/st/numpy_native/test_math_ops.py

@@ -1002,8 +1002,6 @@ def onp_fmod(x, y):
 
 
 @pytest.mark.level1
-@pytest.mark.platform_arm_ascend_training
-@pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.platform_x86_cpu
 @pytest.mark.env_onecard