[Op] Fix reshape and mean (#20058)

    Operator mean falls back to old api
    Operator reshape falls back to old api as it occurs twice in mx.nd.np.all
    Remove reverse keyword in np.reshape to achieve numpy compatibility. Please use npx.reshape if reverse is needed.

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());
   }