remove tensor

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

@@ -598,22 +598,6 @@ mindspore.Tensor
         - **TypeError** - `lambd` 不是float。
         - **TypeError** - 原始Tensor的dtype既不是float16也不是float32。
 
-    .. py:method:: hardswish()
-
-        Hard Swish激活函数。
-
-        对输入的每个元素计算Hard Swish。
-
-        更多细节参考 :func:`mindspore.ops.hardswish`。
-
-        **返回：**
-
-        Tensor，具有与输入Tensor相同的数据类型和shape。
-
-        **异常：**
-
-        - **TypeError** - 输入Tensor的数据类型既不是float16也不是float32。
-
     .. py:method:: has_init
         :property:
 

mindspore/ccsrc/pipeline/jit/resource.cc

@@ -250,7 +250,6 @@ BuiltInTypeMap &GetMethodMap() {
        {"cdist", std::string("cdist")},                                    // P.cdist
        {"celu", std::string("celu")},                                      // P.celu
        {"hardshrink", std::string("hardshrink")},                          // P.hshrink
-       {"hardswish", std::string("hardswish")},                            // P.HSwish
        {"soft_shrink", std::string("soft_shrink")},                        // P.SoftShrink
        {"one_hot", std::string("one_hot")},                                // P.OneHot
        {"intopk", std::string("intopk")},                                  // P.InTopK

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

@@ -1571,34 +1571,6 @@ def adaptive_avgpool2d(x, output_size):
     return F.adaptive_avgpool2d(x, output_size)
 
 
-def hardswish(x):
-    r"""
-    Hard swish activation function.
-
-    Calculate Hard Swish for each element of input.
-
-    Args:
-        x (Tensor): Input tensor.
-
-    Returns:
-        Tensor, with the same type and shape as the `x`.
-
-    Raises:
-        TypeError: If `x` is not a Tensor.
-        TypeError: If dtype of `x` is neither float16 nor float32.
-
-    Supported Platforms:
-        ``Ascend`` ``GPU`` ``CPU``
-
-    Examples:
-        >>> import mindspore.numpy as np
-        >>> x = np.array([-1, -2, 0, 2, 1])
-        >>> print(x.hardswish())
-        [-0.3333  -0.3333  0  1.666  0.6665]
-    """
-    return P.HSwish()(x)
-
-
 def getitem(data, index):
     """Implementation of `getitem`."""
     return data.__getitem__(index)

mindspore/python/mindspore/common/tensor.py

@@ -3921,34 +3921,6 @@ class Tensor(Tensor_):
         self._init_check()
         return tensor_operator_registry.get('hardshrink')(lambd)(self)
 
-    def hardswish(self):
-        r"""
-        Hard swish activation function.
-
-        Calculate Hard Swish for each element of input.
-
-        Refer to :func:`mindspore.ops.hardswish` for more detail.
-
-        Returns:
-            Tensor, with the same type and shape as the input.
-
-        Raises:
-            TypeError: If dtype of input is neither float16 nor float32.
-
-        Supported Platforms:
-            ``Ascend`` ``GPU`` ``CPU``
-
-        Examples:
-            >>> from mindspore import Tensor
-            >>> a = Tensor([-1, -2, 0, 2, 1]).astype("float16")
-            >>> output = a.hardswish()
-            >>> print(output)
-            [-0.3333  -0.3333  0  1.666  0.6665]
-        """
-
-        self._init_check()
-        return tensor_operator_registry.get('hardswish')()(self)
-
     def soft_shrink(self, lambd=0.5):
         """
         Apply the soft shrink function for a tensor. Calculates the output according to the input elements.

mindspore/python/mindspore/ops/functional.py

@@ -965,7 +965,6 @@ tensor_operator_registry.register('matrix_band_part', matrix_band_part)
 tensor_operator_registry.register('padding', padding)
 tensor_operator_registry.register('celu', P.CeLU)
 tensor_operator_registry.register('hardshrink', P.HShrink)
-tensor_operator_registry.register('hardswish', P.HSwish)
 tensor_operator_registry.register('soft_shrink', P.SoftShrink)
 tensor_operator_registry.register('svd', linalg_ops.Svd)
 tensor_operator_registry.register('diag', P.Diag)