[operator] Fix reshape and mean

python/mxnet/base.py

@@ -790,6 +790,7 @@ def write_all_str(module_file, module_all_list):
 
 _NP_OP_PREFIX = '_np_'
 _NP_OP_SUBMODULE_LIST = ['_random_', '_linalg_']
+_NP_OP_IMPLEMENTED_SET = {'_np_reshape'}
 
 _NP_EXT_OP_PREFIX = '_npx_'
 _NP_EXT_OP_SUBMODULE_LIST = ['_image_', '_random_']
@@ -850,12 +851,15 @@ def _init_np_op_module(root_module_name, np_module_name, mx_module_name, make_op
     if np_module_name == 'numpy':
         op_name_prefix = _NP_OP_PREFIX
         submodule_name_list = _NP_OP_SUBMODULE_LIST
+        op_implemented_set = _NP_OP_IMPLEMENTED_SET
     elif np_module_name == 'numpy_extension':
         op_name_prefix = _NP_EXT_OP_PREFIX
         submodule_name_list = _NP_EXT_OP_SUBMODULE_LIST
+        op_implemented_set = set()
     elif np_module_name == 'numpy._internal':
         op_name_prefix = _NP_INTERNAL_OP_PREFIX
         submodule_name_list = []
+        op_implemented_set = set()
     else:
         raise ValueError('unsupported np module name {}'.format(np_module_name))
 
@@ -865,8 +869,12 @@ def _init_np_op_module(root_module_name, np_module_name, mx_module_name, make_op
     op_names = []
     for i in range(size.value):
         name = py_str(plist[i])
-        if name.startswith(op_name_prefix):
-            op_names.append(name)
+        if mx_module_name != 'symbol':
+            if name.startswith(op_name_prefix) and name not in op_implemented_set:
+                op_names.append(name)
+        else:
+            if name.startswith(op_name_prefix):
+                op_names.append(name)
 
     if mx_module_name is None:
         # register np/npx ops for imperative programming

python/mxnet/ndarray/numpy/_op.py

@@ -9476,7 +9476,7 @@ def cumsum(a, axis=None, dtype=None, out=None):
     return _api_internal.cumsum(a, axis, dtype, out)
 
 @set_module('mxnet.ndarray.numpy')
-def reshape(a, newshape, reverse=False, order='C'):
+def reshape(a, newshape, order='C'):
     """
     Gives a new shape to an array without changing its data.
     This function always returns a copy of the input array if
@@ -9537,7 +9537,7 @@ def reshape(a, newshape, reverse=False, order='C'):
            [3., 4.],
            [5., 6.]])
     """
-    return _api_internal.reshape(a, newshape, reverse, order)
+    return _api_internal.reshape(a, newshape, False, order)
 
 @set_module('mxnet.ndarray.numpy')
 def moveaxis(a, source, destination):

python/mxnet/numpy/multiarray.py

@@ -798,7 +798,7 @@ def __getitem__(self, key):
             if not unsupported:
                 new_shape += (-4,)
                 sliced = _npi.slice(self, begin, end, step)
-                return _npi.reshape(sliced, new_shape)
+                return _mx_nd_np.reshape(sliced, new_shape)
 
         # Special handling for cases only supported in imperative mode
         if dc.is_deferred_compute():
@@ -1635,9 +1635,9 @@ def reshape(self, *args, **kwargs):  # pylint: disable=arguments-differ
         if len(args) == 0:
             raise TypeError('reshape() takes exactly 1 argument (0 given)')
         if len(args) == 1 and isinstance(args[0], tuple):
-            return _mx_np_op.reshape(self, newshape=args[0], order=order)
+            return _mx_nd_np.reshape(self, newshape=args[0], order=order)
         else:
-            return _mx_np_op.reshape(self, newshape=args, order=order)
+            return _mx_nd_np.reshape(self, newshape=args, order=order)
 
     def reshape_like(self, *args, **kwargs):
         """Convenience fluent method for :py:func:`reshape_like`.
@@ -7620,7 +7620,7 @@ def mean(a, axis=None, dtype=None, out=None, keepdims=False):  # pylint: disable
     >>> np.mean(a, dtype=np.float64)
     array(0.55, dtype=float64)
     """
-    return _npi.mean(a, axis=axis, dtype=dtype, keepdims=keepdims, out=out)
+    return _mx_nd_np.mean(a, axis=axis, dtype=dtype, keepdims=keepdims, out=out)
 # pylint: enable=redefined-outer-name
 
 
@@ -11810,7 +11810,7 @@ def cumsum(a, axis=None, dtype=None, out=None):
     return _mx_nd_np.cumsum(a, axis=axis, dtype=dtype, out=out)
 
 @set_module('mxnet.numpy')
-def reshape(a, newshape, reverse, order='C'):
+def reshape(a, newshape, order='C'):
     """
     Gives a new shape to an array without changing its data.
     This function always returns a copy of the input array if
@@ -11871,7 +11871,7 @@ def reshape(a, newshape, reverse, order='C'):
            [3., 4.],
            [5., 6.]])
     """
-    return _mx_nd_np.reshape(a, newshape, reverse, order)
+    return _mx_nd_np.reshape(a, newshape, order)
 
 @set_module('mxnet.numpy')
 def moveaxis(a, source, destination):

src/api/operator/numpy/np_broadcast_reduce_op_value.cc

@@ -118,6 +118,8 @@ MXNET_REGISTER_API("_npi.mean")
   op::NumpyReduceAxesParam param;
   if (args[1].type_code() == kNull) {
     param.axis = dmlc::optional<mxnet::Tuple<int>>();
+  } else if (args[1].type_code() == kDLInt) {
+    param.axis = Tuple<int>(1, args[1].operator int64_t());
   } else {
     param.axis = mxnet::Tuple<int>(args[1].operator ObjectRef());
   }