diff --git a/docs/api/api_python/mindspore/mindspore.Tensor.rst b/docs/api/api_python/mindspore/mindspore.Tensor.rst index 63c95a33cdb..cfb106e33d9 100644 --- a/docs/api/api_python/mindspore/mindspore.Tensor.rst +++ b/docs/api/api_python/mindspore/mindspore.Tensor.rst @@ -1475,7 +1475,7 @@ mindspore.Tensor Tensor。 - .. py:method:: tensor_scatter_add(indices, updates) + .. py:method:: scatter_add(indices, updates) 根据指定的更新值和输入索引，通过相加运算更新本Tensor的值。当同一索引有不同值时，更新的结果将是所有值的总和。 @@ -1496,7 +1496,7 @@ mindspore.Tensor - **TypeError** - `indices` 的数据类型既不是int32，也不是int64。 - **ValueError** - Tensor的shape长度小于 `indices` 的shape的最后一个维度。 - .. py:method:: tensor_scatter_div(indices, updates) + .. py:method:: scatter_div(indices, updates) 根据指定的索引, 通过除法进行计算, 将输出赋值到输出Tensor中。 @@ -1518,7 +1518,7 @@ mindspore.Tensor - **TypeError** - `indices` 的数据类型不是int32，也不是int64。 - **ValueError** - Tensor的shape长度小于 `indices` 的shape的最后一个维度。 - .. py:method:: tensor_scatter_min(indices, updates) + .. py:method:: scatter_min(indices, updates) 根据指定的更新值和输入索引，通过最小值运算，将结果赋值到输出Tensor中。 @@ -1541,7 +1541,7 @@ mindspore.Tensor - **TypeError** - `indices` 的数据类型既不是int32，也不是int64。 - **ValueError** - Tensor的shape长度小于 `indices` 的shape的最后一个维度。 - .. py:method:: tensor_scatter_mul(indices, updates) + .. py:method:: scatter_mul(indices, updates) 根据指定的索引， 通过乘法进行计算， 将输出赋值到输出Tensor中。 @@ -1562,7 +1562,7 @@ mindspore.Tensor - **TypeError** - `indices` 的数据类型不是int32，也不是int64。 - **ValueError** - Tensor的shape长度小于 `indices` 的shape的最后一个维度。 - .. py:method:: tensor_scatter_sub(indices, updates) + .. py:method:: scatter_sub(indices, updates) 根据指定的更新值和输入索引，通过减法进行运算，将结果赋值到输出Tensor中。当同一索引有不同值时，更新的结果将是所有值的总和。此操作几乎等同于使用 :class:`mindspore.ops.ScatterNdSub` ，只是更新后的结果是通过算子output返回，而不是直接原地更新input。 diff --git a/mindspore/ccsrc/pipeline/jit/resource.cc b/mindspore/ccsrc/pipeline/jit/resource.cc index 8c515a72da6..ca80835ab65 100644 --- a/mindspore/ccsrc/pipeline/jit/resource.cc +++ b/mindspore/ccsrc/pipeline/jit/resource.cc @@ -112,7 +112,7 @@ BuiltInTypeMap &GetMethodMap() { {"__lt__", prim::kPrimScalarLt}, // P.scalar_lt, {"__gt__", prim::kPrimScalarGt}, // P.scalar_gt, {"__le__", prim::kPrimScalarLe}, // P.scalar_le, - {"__ge__", prim::kPrimScalarGe}, // P.scalar_ge,mindspore/ccsrc/pipeline/jit/resource.cc + {"__ge__", prim::kPrimScalarGe}, // P.scalar_ge, {"__bool__", std::string("float_bool")}, // C.float_bool {"__ms_to_array__", prim::kPrimScalarToArray}, // P.scalar_to_array, }}, @@ -234,11 +234,11 @@ BuiltInTypeMap &GetMethodMap() { {"padding", std::string("padding")}, // padding() {"searchsorted", std::string("searchsorted")}, // P.Select() {"take", std::string("take")}, // P.GatherNd() - {"tensor_scatter_add", std::string("tensor_scatter_add")}, // P.TensorScatterAdd() - {"tensor_scatter_mul", std::string("tensor_scatter_mul")}, // tensor_scatter_mul() - {"tensor_scatter_sub", std::string("tensor_scatter_sub")}, // P.TensorScatterSub() - {"tensor_scatter_min", std::string("tensor_scatter_min")}, // P.TensorScatterMin() - {"tensor_scatter_div", std::string("tensor_scatter_div")}, // P.TensorScatterDiv() + {"scatter_add", std::string("tensor_scatter_add")}, // P.TensorScatterAdd() + {"scatter_mul", std::string("tensor_scatter_mul")}, // tensor_scatter_mul() + {"scatter_sub", std::string("tensor_scatter_sub")}, // P.TensorScatterSub() + {"scatter_min", std::string("tensor_scatter_min")}, // P.TensorScatterMin() + {"scatter_div", std::string("tensor_scatter_div")}, // P.TensorScatterDiv() {"lp_norm", std::string("lp_norm")}, // lp_norm() {"renorm", std::string("renorm")}, // renorm() {"trace", std::string("trace")}, // P.Eye() diff --git a/mindspore/python/mindspore/common/tensor.py b/mindspore/python/mindspore/common/tensor.py index 6f2e8475272..7f6a2d56c92 100644 --- a/mindspore/python/mindspore/common/tensor.py +++ b/mindspore/python/mindspore/common/tensor.py @@ -756,7 +756,7 @@ class Tensor(Tensor_): self._init_check() return tensor_operator_registry.get('bitwise_xor')(self, x) - def tensor_scatter_mul(self, indices, updates): + def scatter_mul(self, indices, updates): """ Creates a new tensor by multiplying the values from the positions in self tensor indicated by `indices`, with values from `updates`. When divided values are provided for the same @@ -802,7 +802,7 @@ class Tensor(Tensor_): >>> # first_input_x = input_x[0][0] * updates[0] = [[-0.1, 0.3, 3.6], [0.4, 0.5, -3.2]] >>> # 6, Perform the multiply operation for the second time: >>> # second_input_x = input_x[0][0] * updates[1] = [[-0.22, 0.3, 3.6], [0.4, 0.5, -3.2]] - >>> output = input_x.tensor_scatter_mul(indices, updates) + >>> output = input_x.scatter_mul(indices, updates) >>> print(output) [[-0.22 0.3 3.6 ] [ 0.4 0.5 -3.2 ]] @@ -810,7 +810,7 @@ class Tensor(Tensor_): self._init_check() return tensor_operator_registry.get('tensor_scatter_mul')(self, indices, updates) - def tensor_scatter_div(self, indices, updates): + def scatter_div(self, indices, updates): """ Creates a new tensor by dividing the values from the positions in self tensor indicated by `indices`, with values from `updates`. When divided values are provided for the same @@ -850,7 +850,7 @@ class Tensor(Tensor_): >>> input_x = Tensor(np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]]).astype('float32')) >>> indices = Tensor(np.array([[0, 0], [0, 0]]).astype('int32')) >>> updates = Tensor(np.array([1.0, 2.0]).astype('float32')) - >>> output = input_x.tensor_scatter_div(indices, updates) + >>> output = input_x.scatter_div(indices, updates) >>> print(output) [[-0.05, 0.3, 3.6 ] [ 0.4, 0.5, -3.2 ]] @@ -2389,7 +2389,7 @@ class Tensor(Tensor_): return reduce_(self, reduce_min(keepdims), cmp_fn=minimum(), axis=axis, keepdims=keepdims, initial=initial, where=where) - def tensor_scatter_add(self, indices, updates): + def scatter_add(self, indices, updates): """ Creates a new tensor by adding the values from the positions in self tensor indicated by `indices`, with values from `updates`. When multiple values are given for the same @@ -2427,7 +2427,7 @@ class Tensor(Tensor_): >>> x = Tensor(np.array([[-0.1, 0.3, 3.6], [0.4, 0.5, -3.2]]).astype('float32')) >>> indices = Tensor(np.array([[0, 0], [0, 0]]).astype('int32')) >>> updates = Tensor(np.array([1.0, 2.2]).astype('float32')) - >>> output = x.tensor_scatter_add(indices, updates) + >>> output = x.scatter_add(indices, updates) >>> print(output) [[ 3.1 0.3 3.6] [ 0.4 0.5 -3.2]] @@ -2435,7 +2435,7 @@ class Tensor(Tensor_): self._init_check() return tensor_operator_registry.get("tensor_scatter_add")()(self, indices, updates) - def tensor_scatter_sub(self, indices, updates): + def scatter_sub(self, indices, updates): """ Creates a new tensor by subtracting the values from the positions in self tensor indicated by `indices`, with values from `updates`. When multiple values are provided for the same @@ -2473,7 +2473,7 @@ class Tensor(Tensor_): >>> x = Tensor(np.array([[-0.1, 0.3, 3.6], [0.4, 0.5, -3.2]]).astype('float32')) >>> indices = Tensor(np.array([[0, 0], [0, 0]]).astype('int32')) >>> updates = Tensor(np.array([1.0, 2.2]).astype('float32')) - >>> output = x.tensor_scatter_sub(indices, updates) + >>> output = x.scatter_sub(indices, updates) >>> print(output) [[-3.3000002 0.3 3.6 ] [ 0.4 0.5 -3.2 ]] @@ -2481,7 +2481,7 @@ class Tensor(Tensor_): self._init_check() return tensor_operator_registry.get('tensor_scatter_sub')()(self, indices, updates) - def tensor_scatter_min(self, indices, updates): + def scatter_min(self, indices, updates): """ By comparing the value at the position indicated by `indices` in self tensor with the value in the `updates`, the value at the index will eventually be equal to the smallest one to create a new tensor. @@ -2516,7 +2516,7 @@ class Tensor(Tensor_): >>> x = Tensor(np.array([[-0.1, 0.3, 3.6], [0.4, 0.5, -3.2]]).astype('float32')) >>> indices = Tensor(np.array([[0, 0], [0, 0]]).astype('int32')) >>> updates = Tensor(np.array([1.0, 2.2]).astype('float32')) - >>> output = x.tensor_scatter_min(indices, updates) + >>> output = x.scatter_min(indices, updates) >>> print(output) [[ -0.1 0.3 3.6] [ 0.4 0.5 -3.2]] diff --git a/tests/st/ops/ascend/test_tensor_scatter_arithmetic.py b/tests/st/ops/ascend/test_tensor_scatter_arithmetic.py index 54061d679ac..f2c3b7e8312 100644 --- a/tests/st/ops/ascend/test_tensor_scatter_arithmetic.py +++ b/tests/st/ops/ascend/test_tensor_scatter_arithmetic.py @@ -197,9 +197,9 @@ def test_tensor_scatter_arithmetic_tensor_op(func, data_type, index_type): expected = tensor_scatter_np(func, input_x, indices, updates) if func == 'add': - output = input_x.tensor_scatter_add(indices, updates) + output = input_x.scatter_add(indices, updates) elif func == 'sub': - output = input_x.tensor_scatter_sub(indices, updates) + output = input_x.scatter_sub(indices, updates) np.testing.assert_allclose(output.asnumpy(), expected, rtol=1e-6) diff --git a/tests/st/ops/cpu/test_tensor_scatter_arithmetic.py b/tests/st/ops/cpu/test_tensor_scatter_arithmetic.py index 97be6bef9ab..b4a6e20c608 100644 --- a/tests/st/ops/cpu/test_tensor_scatter_arithmetic.py +++ b/tests/st/ops/cpu/test_tensor_scatter_arithmetic.py @@ -266,7 +266,7 @@ def test_tensor_scatter_arithmetic_tensor_func_check(func, data_type, index_type expected = tensor_scatter_np(func, input_x, indices, updates) if func == 'div': - output = input_x.tensor_scatter_div(indices, updates) + output = input_x.scatter_div(indices, updates) np.testing.assert_allclose(output.asnumpy(), expected, rtol=1e-6)