mindspore.ops.functional

The functional operators are initialized Primitives and can be used directly as functions. An example of the use of the functional operator is as follows:

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]

Neural Network Layer Operators

Activation Functions

functional	Description
mindspore.ops.tanh	Refer to mindspore.ops.Tanh.

Mathematical Operators

Element-by-Element Operations

functional	Description
mindspore.ops.absolute	Refer to mindspore.ops.Abs.
mindspore.ops.acos	Refer to mindspore.ops.ACos.
mindspore.ops.acosh	Refer to mindspore.ops.Acosh.
mindspore.ops.add	Refer to mindspore.ops.Add.
mindspore.ops.addn	Refer to mindspore.ops.AddN.
mindspore.ops.asin	Refer to mindspore.ops.Asin.
mindspore.ops.asinh	Refer to mindspore.ops.Asinh.
mindspore.ops.atan	Refer to mindspore.ops.Atan.
mindspore.ops.atan2	Refer to mindspore.ops.Atan2.
mindspore.ops.atanh	Refer to mindspore.ops.Atanh.
mindspore.ops.bitwise_and	Refer to mindspore.ops.BitwiseAnd.
mindspore.ops.bitwise_or	Refer to mindspore.ops.BitwiseOr.
mindspore.ops.bitwise_xor	Refer to mindspore.ops.BitwiseXor.
mindspore.ops.cos	Refer to mindspore.ops.Cos.
mindspore.ops.cosh	Refer to mindspore.ops.Cosh.
mindspore.ops.div	Refer to mindspore.ops.RealDiv.
mindspore.ops.erf	Refer to mindspore.ops.Erf.
mindspore.ops.erfc	Refer to mindspore.ops.Erfc.
mindspore.ops.exp	Refer to mindspore.ops.Exp.
mindspore.ops.floor	Refer to mindspore.ops.Floor.
mindspore.ops.floordiv	Refer to mindspore.ops.FloorDiv.
mindspore.ops.floormod	Refer to mindspore.ops.FloorMod.
mindspore.ops.log	Refer to mindspore.ops.Log.
mindspore.ops.logical_and	Refer to mindspore.ops.LogicalAnd.
mindspore.ops.logical_not	Refer to mindspore.ops.LogicalNot.
mindspore.ops.logical_or	Refer to mindspore.ops.LogicalOr.
mindspore.ops.invert	Refer to mindspore.ops.Invert.
mindspore.ops.mul	Refer to mindspore.ops.Mul.
mindspore.ops.neg_tensor	Refer to mindspore.ops.Neg.
mindspore.ops.pows	Refer to mindspore.ops.Pow.
mindspore.ops.sin	Refer to mindspore.ops.Sin.
mindspore.ops.sinh	Refer to mindspore.ops.Sinh.
mindspore.ops.sqrt	Refer to mindspore.ops.Sqrt.
mindspore.ops.square	Refer to mindspore.ops.Square.
mindspore.ops.sub	Refer to mindspore.ops.Sub.
mindspore.ops.tan	Refer to mindspore.ops.Tan.
mindspore.ops.tensor_add	Refer to mindspore.ops.Add.
mindspore.ops.tensor_div	Refer to mindspore.ops.RealDiv.
mindspore.ops.tensor_exp	Refer to mindspore.ops.Exp.
mindspore.ops.tensor_expm1	Refer to mindspore.ops.Expm1.
mindspore.ops.tensor_floordiv	Refer to mindspore.ops.FloorDiv.
mindspore.ops.tensor_mod	Refer to mindspore.ops.FloorMod.
mindspore.ops.tensor_mul	Refer to mindspore.ops.Mul.
mindspore.ops.tensor_pow	Refer to mindspore.ops.Pow.
mindspore.ops.tensor_sub	Refer to mindspore.ops.Sub.

Reduction Operators

functional	Description
mindspore.ops.reduce_max	Refer to mindspore.ops.ReduceMax.
mindspore.ops.reduce_mean	Refer to mindspore.ops.ReduceMean.
mindspore.ops.reduce_min	Refer to mindspore.ops.ReduceMin.
mindspore.ops.reduce_prod	Refer to mindspore.ops.ReduceProd.
mindspore.ops.reduce_sum	Refer to mindspore.ops.ReduceSum.

Comparison operators

functional	Description
mindspore.ops.check_bprop	Refer to mindspore.ops.CheckBprop.
mindspore.ops.equal	Refer to mindspore.ops.Equal.
mindspore.ops.ge	Refer to mindspore.ops.GreaterEqual.
mindspore.ops.gt	Refer to mindspore.ops.Greater.
mindspore.ops.le	Refer to mindspore.ops.LessEqual.
mindspore.ops.less	Refer to mindspore.ops.Less.
mindspore.ops.isfinite	Refer to mindspore.ops.IsFinite.
mindspore.ops.isinstance_	Refer to mindspore.ops.IsInstance.
mindspore.ops.isnan	Refer to mindspore.ops.IsNan.
mindspore.ops.issubclass_	Refer to mindspore.ops.IsSubClass.
mindspore.ops.maximum	Refer to mindspore.ops.Maximum.
mindspore.ops.minimum	Refer to mindspore.ops.Minimum.
mindspore.ops.not_equal	Refer to mindspore.ops.NotEqual.
mindspore.ops.same_type_shape	Refer to mindspore.ops.SameTypeShape.
mindspore.ops.tensor_ge	Refer to mindspore.ops.GreaterEqual.
mindspore.ops.tensor_gt	Refer to mindspore.ops.Greater.
mindspore.ops.tensor_le	Refer to mindspore.ops.LessEqual.
mindspore.ops.tensor_lt	Refer to mindspore.ops.Less.

Linear Algebraic Operators

API Name	Description	Supported Platforms
mindspore.ops.matmul	Returns the matrix product of two arrays.	Ascend GPU CPU

Tensor Operation Operators

Tensor Building

functional	Description
mindspore.ops.eye	Refer to mindspore.ops.Eye.
mindspore.ops.fill	Refer to mindspore.ops.Fill.
mindspore.ops.ones_like	Refer to mindspore.ops.OnesLike.
mindspore.ops.zeros_like	Refer to mindspore.ops.ZerosLike.

Randomly Generating Operators

API Name	Description	Supported Platforms
mindspore.ops.gamma	Generates random numbers according to the Gamma random number distribution.	Ascend
mindspore.ops.multinomial	Returns a tensor sampled from the multinomial probability distribution located in the corresponding row of the input tensor.	GPU
mindspore.ops.poisson	Generates random numbers according to the Poisson random number distribution.	Ascend

Array Operation

functional	Description
mindspore.ops.cast	Refer to mindspore.ops.Cast.
mindspore.ops.cumprod	Refer to mindspore.ops.CumProd.
mindspore.ops.cumsum	Refer to mindspore.ops.CumSum.
mindspore.ops.dtype	Refer to mindspore.ops.DType.
mindspore.ops.expand_dims	Refer to mindspore.ops.ExpandDims.
mindspore.ops.gather	Refer to mindspore.ops.Gather.
mindspore.ops.gather_d	Refer to mindspore.ops.GatherD.
mindspore.ops.gather_nd	Refer to mindspore.ops.GatherNd.
mindspore.ops.rank	Refer to mindspore.ops.Rank.
mindspore.ops.reshape	Refer to mindspore.ops.Reshape.
mindspore.ops.scatter_nd	Refer to mindspore.ops.ScatterNd.
mindspore.ops.shape	Refer to mindspore.ops.Shape.
mindspore.ops.size	Refer to mindspore.ops.Size.
mindspore.ops.sort	Refer to mindspore.ops.Sort.
mindspore.ops.squeeze	Refer to mindspore.ops.Squeeze.
mindspore.ops.stack	Refer to mindspore.ops.Stack.
mindspore.ops.strided_slice	Refer to mindspore.ops.StridedSlice.
mindspore.ops.tensor_scatter_add	Refer to mindspore.ops.TensorScatterAdd.
mindspore.ops.tensor_scatter_update	Refer to mindspore.ops.TensorScatterUpdate.
mindspore.ops.tensor_slice	Refer to mindspore.ops.Slice.
mindspore.ops.tile	Refer to mindspore.ops.Tile.
mindspore.ops.transpose	Refer to mindspore.ops.Transpose.

API Name	Description	Supported Platforms
mindspore.ops.select	Returns the selected elements, either from input \(x\) or input \(y\), depending on the condition cond.	Ascend GPU CPU
mindspore.ops.unique	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.	Ascend GPU CPU

Type Conversion

functional	Description
mindspore.ops.scalar_cast	Refer to mindspore.ops.ScalarCast.
mindspore.ops.scalar_to_array	Refer to mindspore.ops.ScalarToArray.
mindspore.ops.scalar_to_tensor	Refer to mindspore.ops.ScalarToTensor.
mindspore.ops.tuple_to_array	Refer to mindspore.ops.TupleToArray.

Parameter Operation Oprators

functional	Description
mindspore.ops.assign	Refer to mindspore.ops.Assign.
mindspore.ops.assign_add	Refer to mindspore.ops.AssignAdd.
mindspore.ops.assign_sub	Refer to mindspore.ops.AssignSub.
mindspore.ops.scatter_nd_update	Refer to mindspore.ops.ScatterNdUpdate.
mindspore.ops.scatter_update	Refer to mindspore.ops.ScatterUpdate.

Debugging Operators

functional	Description
mindspore.ops.print_	Refer to mindspore.ops.Print.

Other Operators

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.Depend.
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.Partial.
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.

API Name	Description	Supported Platforms
mindspore.ops.arange	Returns evenly spaced values within a given interval.	Ascend GPU CPU
mindspore.ops.batch_dot	Computation of batch dot product between samples in two tensors containing batch dims.	Ascend GPU CPU
mindspore.ops.clip_by_global_norm	Clips tensor values by the ratio of the sum of their norms.	Ascend GPU CPU
mindspore.ops.clip_by_value	Clips tensor values to a specified min and max.	Ascend GPU CPU
mindspore.ops.core	A decorator that adds a flag to the function.	Ascend GPU CPU
mindspore.ops.count_nonzero	Count number of nonzero elements across axis of input tensor	Ascend GPU CPU
mindspore.ops.cummin	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'.	Ascend
mindspore.ops.dot	Computation a dot product between samples in two tensors.	Ascend GPU CPU
mindspore.ops.grad	A wrapper function to generate the gradient function for the input function.	Ascend GPU CPU
mindspore.ops.jvp	Compute the jacobian-vector-product of the given network.	Ascend GPU CPU
mindspore.ops.laplace	Generates random numbers according to the Laplace random number distribution.	Ascend
mindspore.ops.narrow	Returns a narrowed tensor from input tensor.	Ascend GPU CPU
mindspore.ops.normal	Generates random numbers according to the Normal (or Gaussian) random number distribution.	Ascend GPU CPU
mindspore.ops.repeat_elements	Repeat elements of a tensor along an axis, like np.repeat .	Ascend GPU CPU
mindspore.ops.sequence_mask	Returns a mask tensor representing the first N positions of each cell.	GPU
mindspore.ops.tensor_dot	Computation of Tensor contraction on arbitrary axes between tensors a and b.	Ascend GPU CPU
mindspore.ops.uniform	Generates random numbers according to the Uniform random number distribution.	Ascend GPU
mindspore.ops.vjp	Compute the vector-jacobian-product of the given network.	Ascend GPU CPU