!16288 fix numpy-native bugs

From: @yanglf1121
Reviewed-by: @guoqi1024,@liangchenghui
Signed-off-by: @liangchenghui

mindspore/_extends/parse/standard_method.py

@@ -510,7 +510,7 @@ def cumsum(x, axis=None, dtype=None):
     original_dtype = x.dtype
     # If original tensor is int, and has precision less then int32, convert
     # to int32
-    if x.dtype in (mstype.int8, mstype.int16, mstype.uint8, mstype.int16):
+    if x.dtype in (mstype.bool_, mstype.int8, mstype.int16, mstype.uint8, mstype.int16):
         x = x.astype(mstype.int32)
     if axis is None:
         x = x.ravel()

mindspore/common/tensor.py

@@ -796,7 +796,7 @@ class Tensor(Tensor_):
         x = self
         original_dtype = x.dtype
         # If original tensor is int, and has precision less then int32, convert to int32
-        if mstype.issubclass_(x.dtype, mstype.int_) and x.itemsize < 4:
+        if x.dtype in (mstype.bool_, mstype.int8, mstype.int16, mstype.uint8, mstype.int16):
             x = x.astype(mstype.int32)
         if axis is None:
             x = x.ravel()

mindspore/numpy/math_ops.py

@@ -4176,7 +4176,7 @@ def argmax(a, axis=None):
         5
         >>> print(np.argmax(a, axis=0))
         [1 1 1]
-        >>> print(np.argmax(a, axis=0))
+        >>> print(np.argmax(a, axis=1))
         [2 2]
     """
     a = _to_tensor(a)
@@ -4212,7 +4212,7 @@ def argmin(a, axis=None):
         0
         >>> print(np.argmin(a, axis=0))
         [0 0 0]
-        >>> print(np.argmin(a, axis=0))
+        >>> print(np.argmin(a, axis=1))
         [0 0]
     """
     a = _to_tensor(a)
@@ -4653,7 +4653,7 @@ def histogram(a, bins=10, range=None, weights=None, density=False): # pylint: di
     if density:
         count = F.cast(count, mstype.float32)
         count = count/diff(bin_edges)/F.reduce_sum(count)
-    return count.astype(mstype.int32), bin_edges
+    return count, bin_edges
 
 
 @constexpr
@@ -4792,7 +4792,7 @@ def histogramdd(sample, bins=10, range=None, weights=None, density=False): # pyl
             shape = _expanded_shape(ndim, dedges[i].size, i)
             count /= _to_tensor(dedges[i]).reshape(shape)
         count /= s
-    return count.astype(mstype.int32), bin_edges
+    return count, bin_edges
 
 
 def histogram2d(x, y, bins=10, range=None, weights=None, density=False): # pylint: disable=redefined-builtin
@@ -4856,7 +4856,7 @@ def histogram2d(x, y, bins=10, range=None, weights=None, density=False): # pylin
         5.33333349e+00,  6.00000000e+00]))
     """
     count, bin_edges = histogramdd((x, y), bins=bins, range=range, weights=weights, density=density)
-    return count.astype(mstype.int32), bin_edges[0], bin_edges[1]
+    return count, bin_edges[0], bin_edges[1]
 
 
 def matrix_power(a, n):

mindspore/ops/composite/multitype_ops/_compile_utils.py

@@ -910,7 +910,10 @@ def reduce_(a, reduce_fn, cmp_fn=None, axis=None, keepdims=False, initial=None,
         const_utils.raise_value_error('zero-size tensors are not supported.')
 
     if initial is not None:
-        initial = F.fill(dtype, shape, initial)
+        if isinstance(initial, Tensor):
+            initial = F.tile(initial, shape).astype(dtype)
+        else:
+            initial = F.fill(dtype, shape, initial)
         a = cmp_fn(a, initial)
 
     if isinstance(where, Tensor):

tests/st/numpy_native/test_array_ops.py

@@ -1641,7 +1641,7 @@ def test_apply_over_axes():
             match_array(actual.asnumpy(), expected, error=5)
 
 
-@pytest.mark.level1
+@pytest.mark.level2
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training

tests/st/numpy_native/test_math_ops.py

@@ -1372,7 +1372,7 @@ def test_negative():
     match_array(mnp_neg.asnumpy(), onp_neg, 1e-5)
 
 
-@pytest.mark.level1
+@pytest.mark.level0
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -2170,7 +2170,7 @@ def test_bincount():
     match_res(mnp.bincount, onp.bincount, x, weights, minlength=25, error=3)
 
 
-@pytest.mark.level1
+@pytest.mark.level2
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -2193,7 +2193,7 @@ def test_histogram():
             match_all_arrays(mnp_res, onp_res, error=1)
 
 
-@pytest.mark.level1
+@pytest.mark.level2
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training
@@ -2236,7 +2236,7 @@ def test_histogramdd():
     match_all_arrays(mnp_res[1], onp_res[1], error=3)
 
 
-@pytest.mark.level1
+@pytest.mark.level2
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training
 @pytest.mark.platform_x86_gpu_training