mindspore.ops.functional
functional算子是经过初始化后的Primitive，可以直接作为函数使用。functional算子的使用示例如下：
from mindspore import Tensor, ops
from mindspore import dtype as mstype
input_x = Tensor(-1, mstype.int32)
input_dict = {'x':1, 'y':2}
result_abs = ops.absolute(input_x)
print(result_abs)
result_in_dict = ops.in_dict('x', input_dict)
print(result_in_dict)
result_not_in_dict = ops.not_in_dict('x', input_dict)
print(result_not_in_dict)
result_isconstant = ops.isconstant(input_x)
print(result_isconstant)
result_typeof = ops.typeof(input_x)
print(result_typeof)
# outputs:
# 1
# True
# False
# True
# Tensor[Int32]
神经网络层算子
激活函数
functional |
Description |
|---|---|
mindspore.ops.tanh |
Refer to |
数学运算算子
逐元素运算
functional |
Description |
|---|---|
mindspore.ops.absolute |
Refer to |
mindspore.ops.acos |
Refer to |
mindspore.ops.acosh |
Refer to |
mindspore.ops.add |
Refer to |
mindspore.ops.addn |
Refer to |
mindspore.ops.asin |
Refer to |
mindspore.ops.asinh |
Refer to |
mindspore.ops.atan |
Refer to |
mindspore.ops.atan2 |
Refer to |
mindspore.ops.atanh |
Refer to |
mindspore.ops.bitwise_and |
Refer to |
mindspore.ops.bitwise_or |
Refer to |
mindspore.ops.bitwise_xor |
Refer to |
mindspore.ops.cos |
Refer to |
mindspore.ops.cosh |
Refer to |
mindspore.ops.div |
Refer to |
mindspore.ops.erf |
Refer to |
mindspore.ops.erfc |
Refer to |
mindspore.ops.exp |
Refer to |
mindspore.ops.floor |
Refer to |
mindspore.ops.floordiv |
Refer to |
mindspore.ops.floormod |
Refer to |
mindspore.ops.log |
Refer to |
mindspore.ops.logical_and |
Refer to |
mindspore.ops.logical_not |
Refer to |
mindspore.ops.logical_or |
Refer to |
mindspore.ops.invert |
Refer to |
mindspore.ops.mul |
Refer to |
mindspore.ops.neg_tensor |
Refer to |
mindspore.ops.pows |
Refer to |
mindspore.ops.sin |
Refer to |
mindspore.ops.sinh |
Refer to |
mindspore.ops.sqrt |
Refer to |
mindspore.ops.square |
Refer to |
mindspore.ops.sub |
Refer to |
mindspore.ops.tan |
Refer to |
mindspore.ops.tensor_add |
Refer to |
mindspore.ops.tensor_div |
Refer to |
mindspore.ops.tensor_exp |
Refer to |
mindspore.ops.tensor_expm1 |
Refer to |
mindspore.ops.tensor_floordiv |
Refer to |
mindspore.ops.tensor_mod |
Refer to |
mindspore.ops.tensor_mul |
Refer to |
mindspore.ops.tensor_pow |
Refer to |
mindspore.ops.tensor_sub |
Refer to |
Reduction算子
functional |
Description |
|---|---|
mindspore.ops.reduce_max |
Refer to |
mindspore.ops.reduce_mean |
Refer to |
mindspore.ops.reduce_min |
Refer to |
mindspore.ops.reduce_prod |
Refer to |
mindspore.ops.reduce_sum |
Refer to |
比较算子
functional |
Description |
|---|---|
mindspore.ops.check_bprop |
Refer to |
mindspore.ops.equal |
Refer to |
mindspore.ops.ge |
Refer to |
mindspore.ops.gt |
Refer to |
mindspore.ops.le |
Refer to |
mindspore.ops.less |
Refer to |
mindspore.ops.isfinite |
Refer to |
mindspore.ops.isinstance_ |
Refer to |
mindspore.ops.isnan |
Refer to |
mindspore.ops.issubclass_ |
Refer to |
mindspore.ops.maximum |
Refer to |
mindspore.ops.minimum |
Refer to |
mindspore.ops.not_equal |
Refer to |
mindspore.ops.same_type_shape |
Refer to |
mindspore.ops.tensor_ge |
Refer to |
mindspore.ops.tensor_gt |
Refer to |
mindspore.ops.tensor_le |
Refer to |
mindspore.ops.tensor_lt |
Refer to |
线性代数算子
接口名 |
概述 |
支持平台 |
计算两个数组的乘积。 |
|
Tensor操作算子
Tensor创建
functional |
Description |
|---|---|
mindspore.ops.eye |
Refer to |
mindspore.ops.fill |
Refer to |
mindspore.ops.ones_like |
Refer to |
mindspore.ops.zeros_like |
Refer to |
随机生成算子
接口名 |
概述 |
支持平台 |
Generates random numbers according to the Gamma random number distribution. |
|
|
Returns a tensor sampled from the multinomial probability distribution located in the corresponding row of the input tensor. |
|
|
Generates random numbers according to the Poisson random number distribution. |
|
Array操作
functional |
Description |
|---|---|
mindspore.ops.cast |
Refer to |
mindspore.ops.cumprod |
Refer to |
mindspore.ops.cumsum |
Refer to |
mindspore.ops.dtype |
Refer to |
mindspore.ops.expand_dims |
Refer to |
mindspore.ops.gather |
Refer to |
mindspore.ops.gather_d |
Refer to |
mindspore.ops.gather_nd |
Refer to |
mindspore.ops.rank |
Refer to |
mindspore.ops.reshape |
Refer to |
mindspore.ops.scatter_nd |
Refer to |
mindspore.ops.shape |
Refer to |
mindspore.ops.size |
Refer to |
mindspore.ops.sort |
Refer to |
mindspore.ops.squeeze |
Refer to |
mindspore.ops.stack |
Refer to |
mindspore.ops.strided_slice |
Refer to |
mindspore.ops.tensor_scatter_add |
Refer to |
mindspore.ops.tensor_scatter_update |
Refer to |
mindspore.ops.tensor_slice |
Refer to |
mindspore.ops.tile |
Refer to |
mindspore.ops.transpose |
Refer to |
接口名 |
概述 |
支持平台 |
Returns the selected elements, either from input \(x\) or input \(y\), depending on the condition cond. |
|
|
Returns the unique elements of input tensor and also return a tensor containing the index of each value of input tensor corresponding to the output unique tensor. |
|
类型转换
functional |
Description |
|---|---|
mindspore.ops.scalar_cast |
Refer to |
mindspore.ops.scalar_to_array |
Refer to |
mindspore.ops.scalar_to_tensor |
Refer to |
mindspore.ops.tuple_to_array |
Refer to |
Parameter操作算子
functional |
Description |
|---|---|
mindspore.ops.assign |
Refer to |
mindspore.ops.assign_add |
Refer to |
mindspore.ops.assign_sub |
Refer to |
mindspore.ops.scatter_nd_update |
Refer to |
mindspore.ops.scatter_update |
Refer to |
调试算子
functional |
Description |
|---|---|
mindspore.ops.print_ |
Refer to |
其他算子
functional |
Description |
|---|---|
mindspore.ops.bool_and |
Calculate the result of logical AND operation. (Usage is the same as “and” in Python) |
mindspore.ops.bool_eq |
Determine whether the Boolean values are equal. (Usage is the same as “==” in Python) |
mindspore.ops.bool_not |
Calculate the result of logical NOT operation. (Usage is the same as “not” in Python) |
mindspore.ops.bool_or |
Calculate the result of logical OR operation. (Usage is the same as “or” in Python) |
mindspore.ops.depend |
Refer to |
mindspore.ops.in_dict |
Determine if a str in dict. |
mindspore.ops.is_not |
Determine whether the input is not the same as the other one. (Usage is the same as “is not” in Python) |
mindspore.ops.is_ |
Determine whether the input is the same as the other one. (Usage is the same as “is” in Python) |
mindspore.ops.isconstant |
Determine whether the object is constant. |
mindspore.ops.not_in_dict |
Determine whether the object is not in the dict. |
mindspore.ops.partial |
Refer to |
mindspore.ops.scalar_add |
Get the sum of two numbers. (Usage is the same as “+” in Python) |
mindspore.ops.scalar_div |
Get the quotient of dividing the first input number by the second input number. (Usage is the same as “/” in Python) |
mindspore.ops.scalar_eq |
Determine whether two numbers are equal. (Usage is the same as “==” in Python) |
mindspore.ops.scalar_floordiv |
Divide the first input number by the second input number and round down to the closest integer. (Usage is the same as “//” in Python) |
mindspore.ops.scalar_ge |
Determine whether the number is greater than or equal to another number. (Usage is the same as “>=” in Python) |
mindspore.ops.scalar_gt |
Determine whether the number is greater than another number. (Usage is the same as “>” in Python) |
mindspore.ops.scalar_le |
Determine whether the number is less than or equal to another number. (Usage is the same as “<=” in Python) |
mindspore.ops.scalar_log |
Get the natural logarithm of the input number. |
mindspore.ops.scalar_lt |
Determine whether the number is less than another number. (Usage is the same as “<” in Python) |
mindspore.ops.scalar_mod |
Get the remainder of dividing the first input number by the second input number. (Usage is the same as “%” in Python) |
mindspore.ops.scalar_mul |
Get the product of the input two numbers. (Usage is the same as “*” in Python) |
mindspore.ops.scalar_ne |
Determine whether two numbers are not equal. (Usage is the same as “!=” in Python) |
mindspore.ops.scalar_pow |
Compute a number to the power of the second input number. |
mindspore.ops.scalar_sub |
Subtract the second input number from the first input number. (Usage is the same as “-” in Python) |
mindspore.ops.scalar_uadd |
Get the positive value of the input number. |
mindspore.ops.scalar_usub |
Get the negative value of the input number. |
mindspore.ops.shape_mul |
The input of shape_mul must be shape multiply elements in tuple(shape). |
mindspore.ops.stop_gradient |
Disable update during back propagation. (stop_gradient) |
mindspore.ops.string_concat |
Concatenate two strings. |
mindspore.ops.string_eq |
Determine if two strings are equal. |
mindspore.ops.typeof |
Get type of object. |
接口名 |
概述 |
支持平台 |
根据给定的范围返回指定均匀间隔的数据。 |
|
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当输入的两个Tensor是批量数据时，对其进行批量点积操作。 |
|
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通过权重梯度总和的比率来裁剪多个Tensor的值。 |
|
|
将输入Tensor值裁剪到指定的最小值和最大值之间。 |
|
|
A decorator that adds a flag to the function. |
|
|
Count number of nonzero elements across axis of input tensor |
|
|
Computation of the cumulative minimum of elements of 'x' in the dimension axis, and the index location of each maximum value found in the dimension 'axis'. |
|
|
两个Tensor之间的点积。 |
|
|
A wrapper function to generate the gradient function for the input function. |
|
|
Compute the jacobian-vector-product of the given network. |
|
|
Generates random numbers according to the Laplace random number distribution. |
|
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Returns a narrowed tensor from input tensor. |
|
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Generates random numbers according to the Normal (or Gaussian) random number distribution. |
|
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在指定轴上复制输入Tensor的元素，类似 np.repeat 的功能。 |
|
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返回一个表示每个单元的前N个位置的掩码Tensor。 |
|
|
在指定轴上对Tensor a 和 b 进行点乘操作。 |
|
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生成服从均匀分布的随机数。 |
|
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Compute the vector-jacobian-product of the given network. |
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