!35916 [OP]delete space_to_batch_nd tensor api

Merge pull request !35916 from zichun_ye/del_space_to_batch_nd_tensor

docs/api/api_python/mindspore/mindspore.Tensor.rst

@@ -1195,31 +1195,6 @@ mindspore.Tensor
         - **TypeError** - `y` 不是Tensor、int或者float。
         - **ValueError** - 输入的shape不相同。
 
-    .. py:method:: space_to_batch_nd(block_shape, paddings)
-
-        将空间维度划分为对应大小的块，然后在批次维度重排张量。
-
-        更多参考详见 :func:`mindspore.ops.space_to_batch_nd`。
-
-        **参数：**
-
-        - **block_shape** (list[int], tuple[int], int) - 块形状描述空间维度为分割的个数。
-        - **paddings** (tuple, list) - 空间维度的填充大小。
-
-        **返回：**
-
-        Tensor，经过划分排列之后的结果。
-
-        **异常：**
-
-        - **TypeError** - 如果 `block_shape` 不是 list, tuple 或者 int。
-        - **TypeError** - 如果 `paddings` 不是 list 或者 tuple。
-        - **ValueError** - 如果当 `block_shape` 为 list 或 tuple， `block_shape` 不是一维。
-        - **ValueError** - 如果 Ascend 平台上 `block_shape` 长度不是2。
-        - **ValueError** - 如果 `paddings` 的形状不是 (2, M), 其中 M 为 `block_shape` 的长度。
-        - **ValueError** - 如果 `block_shape` 的元素不是大于一的整数。
-        - **ValueError** - 如果 `paddings` 的元素不是非负的整数。
-
     .. py:method:: shape
         :property:
 

mindspore/ccsrc/pipeline/jit/resource.cc

@@ -221,7 +221,6 @@ BuiltInTypeMap &GetMethodMap() {
        {"argmin", std::string("argmin")},                                  // P.Argmax()
        {"resize", std::string("resize")},                                  // P.Reshape()
        {"select", std::string("select")},                                  // P.Select()
-       {"space_to_batch_nd", std::string("space_to_batch_nd")},            // P.SpaceToBatchND
        {"batch_to_space_nd", std::string("batch_to_space_nd")},            // P.BatchToSpaceND
        {"choose", std::string("choose")},                                  // P.Select()
        {"diagonal", std::string("diagonal")},                              // P.Eye()

mindspore/python/mindspore/_extends/parse/standard_method.py

@@ -2191,15 +2191,6 @@ def filter_(fun, iter_):
     return result
 
 
-def space_to_batch_nd(x, block_shape, paddings):
-    """
-    Divides spatial dimensions into blocks and combines the block size with the original batch.
-
-    Refer to :func:`mindspore.ops.space_to_batch_nd` for more detail.
-    """
-    return P.SpaceToBatchND(block_shape, paddings)(x)
-
-
 def batch_to_space_nd(x, block_shape, crops):
     r"""
     Divides batch dimension with blocks and interleaves these blocks back into spatial dimensions.

mindspore/python/mindspore/common/tensor.py

@@ -1566,8 +1566,6 @@ class Tensor(Tensor_):
         self._init_check()
         return tensor_operator_registry.get('col2im')(self, output_size, kernel_size, dilation, padding_value, stride)
 
-
-
     def reshape(self, *shape):
         """
         Give a new shape to a tensor without changing its data.
@@ -3141,48 +3139,6 @@ class Tensor(Tensor_):
             j = tensor_operator_registry.get('select')(mask, mid, j)
         return j
 
-    def space_to_batch_nd(self, block_shape, paddings):
-        r"""
-        Divides spatial dimensions into blocks and combines the block size with the original batch.
-
-        Refer to :func:`mindspore.ops.space_to_batch_nd` for more detail.
-
-        Args:
-            block_shape (Union[list(int), tuple(int), int]): The block size of dividing block with all value greater
-                than 1.
-            paddings (Union[tuple, list]): The padding values for spatial dimensions, containing M subtraction list.
-                Each contains 2 integer values.
-
-        Returns:
-            Tensor, the output tensor with the same data type as the input tensor.
-
-        Raises:
-            ValueError: If `block_shape` is not one dimensional when `block_shape` is a list or tuple.
-            ValueError: If the length of `block_shape` is not 2 on Ascend.
-            ValueError: If the element of `block_shape` is not an integer larger than 1.
-            ValueError: If shape of `paddings` is not (2, M), where M is the length of `block_shape`.
-            ValueError: If the element of `paddings` is not an integer larger than 0.
-            TypeError: If `block_shape` is not one of list, tuple, int.
-            TypeError: If `paddings` is neither list nor tuple.
-
-        Supported Platforms:
-            ``Ascend`` ``CPU``
-
-        Examples:
-            >>> import numpy as np
-            >>> from mindspore import Tensor
-            >>> block_shape = [2, 2]
-            >>> paddings = [[0, 0], [0, 0]]
-            >>> input_x = Tensor(np.array([[[[1, 2], [3, 4]]]]), mindspore.float32)
-            >>> output = input_x.space_to_batch_nd(block_shape, paddings)
-            >>> print(output)
-            [[[[1.]]]
-             [[[2.]]]
-             [[[3.]]]
-             [[[4.]]]]
-        """
-        return tensor_operator_registry.get('space_to_batch_nd')(block_shape, paddings)(self)
-
     def batch_to_space_nd(self, block_shape, crops):
         """
         Divides batch dimension with blocks and interleaves these blocks back into spatial dimensions.

mindspore/python/mindspore/ops/functional.py

@@ -950,7 +950,6 @@ tensor_operator_registry.register('sum', P.ReduceSum)
 tensor_operator_registry.register('split', P.Split)
 tensor_operator_registry.register('select', P.Select)
 tensor_operator_registry.register('zeros_like', P.ZerosLike)
-tensor_operator_registry.register('space_to_batch_nd', P.SpaceToBatchND)
 tensor_operator_registry.register('batch_to_space_nd', P.BatchToSpaceND)
 tensor_operator_registry.register('one_hot', P.OneHot)
 tensor_operator_registry.register('masked_fill', masked_fill)

tests/st/ops/cpu/test_spacetobatchnd_op.py

@@ -117,43 +117,6 @@ def test_space_to_batch_nd_function():
     np.testing.assert_array_equal(output.asnumpy(), expect)
 
 
-class SpaceToBatchNDTensorNet(nn.Cell):
-    def __init__(self, block_size=2):
-        super(SpaceToBatchNDTensorNet, self).__init__()
-        self.block_size = block_size
-
-    def construct(self, x):
-        return x.space_to_batch_nd(self.block_size, [[0, 0], [0, 0]])
-
-
-@pytest.mark.level0
-@pytest.mark.platform_x86_cpu
-@pytest.mark.env_onecard
-def test_space_to_batch_nd_tensor():
-    """
-    Feature: test SpaceToBatchND tensor interface.
-    Description: test tensor interface.
-    Expectation: the result match with numpy result
-    """
-    net = SpaceToBatchNDTensorNet(2)
-    input_x = Tensor(np.arange(16).reshape((1, 1, 4, 4)).astype(np.float32), mindspore.float32)
-    expect = np.array([[[[0, 2],
-                         [8, 10]]],
-                       [[[1, 3],
-                         [9, 11]]],
-                       [[[4, 6],
-                         [12, 14]]],
-                       [[[5, 7],
-                         [13, 15]]]]).astype(np.float32)
-
-    context.set_context(mode=context.PYNATIVE_MODE, device_target="CPU")
-    output = net(input_x)
-    assert (output.asnumpy() == expect).all()
-    context.set_context(mode=context.GRAPH_MODE, device_target="CPU")
-    output = net(input_x)
-    assert (output.asnumpy() == expect).all()
-
-
 class SpaceToBatchNDDynamicShapeNetMS(nn.Cell):
     def __init__(self, block_size, paddings, axis=0):
         super().__init__()