mindspore.ops
Operators can be used in the construct function of Cell.
Examples
>>> from mindspore.ops import operations as P
>>> from mindspore.ops import composite as C
>>> from mindspore.ops import functional as F
Note
The Primitive operators in operations need to be used after instantiation.
The composite operators are pre-defined combination of operator.
The functional operators are the pre-instantiated Primitive operators, which can be used directly like a function.
For functional operators usage, please refer to https://gitee.com/mindspore/mindspore/blob/master/mindspore/ops/functional.py
- class mindspore.ops.AiCPURegOp(op_name)[source]
Class for AiCPU op info register
- attr(name=None, value_type=None, value=None, **kwargs)[source]
Register AiCPU op attribute information.
- input(index=None, name=None, param_type=None, **kwargs)[source]
Register AiCPU op input information.
- class mindspore.ops.AkgRegOp(op_name)[source]
Class for Akg op info register.
- attr(name=None, param_type=None, value_type=None, **kwargs)[source]
Register Akg op attribute information.
- class mindspore.ops.DataType[source]
Various combinations of dtype and format.
The current list below maybe not completed. If necessary, please add it.
- class mindspore.ops.Primitive(name)[source]
Primitive is base class for primitives in python.
- Parameters
name (str) – Name for current Primitive.
Examples
>>> add = Primitive('add') >>> >>> # or work with prim_attr_register: >>> # init a Primitive class with attr1 and attr2 >>> class Add(Primitive): >>> @prim_attr_register >>> def __init__(self, attr1, attr2): >>> # check attr1 and attr2 or do some initializations >>> # init a Primitive obj with attr1=1 and attr2=2 >>> add = Add(attr1=1, attr2=2)
- add_prim_attr(name, value)[source]
Adds primitive attribute.
- Parameters
name (str) – Attribute Name.
value (Any) – Attribute value.
- check_elim(*args)[source]
Check whether or not certain inputs should go into backend. Subclass in need should override this method.
- Parameters
Primitive (Same as arguments of current) –
- Returns
A tuple of two elements, first element indicates whether or not we should filter out current arguments; seconde element is the output in case where we should filter out the arguments.
- init_prim_io_names(inputs, outputs)[source]
Initializes inputs and outpus name of Tensor or attributes.
- class mindspore.ops.PrimitiveWithInfer(name)[source]
PrimitiveWithInfer is base class for primitives in python and defines functions for infer of tracks in python.
There are four method can be overide to define the infer logic of the primitive: __infer__(), infer_shape(), infer_dtype(), and infer_value(). If __infer__() is defined in primitive, the __infer__() has highest priority to be called. If __infer__() is not defined, infer_shape() and infer_dtype() can be defined to describe shape and type infer logic. The infer_value() is used for constant propagation.
- Parameters
name (str) – Name for current Primitive.
Examples
>>> # init a Primitive class with infer >>> class Add(PrimitiveWithInfer): >>> @prim_attr_register >>> def __init__(self): >>> pass >>> >>> def infer_shape(self, x, y): >>> return x # output shape same as first input 'x' >>> >>> def infer_dtype(self, x, y): >>> return x # output type same as first input 'x' >>> >>> # init a Primitive obj >>> add = Add()
- infer_dtype(*args)[source]
Infer output dtype based on input dtype.
- Parameters
inputs (mstype) – data type of inputs.
outputs (mstype) – data type of outputs.
- class mindspore.ops.TBERegOp(op_name)[source]
Class for TBE op info register.
- async_flag(async_flag)[source]
Define the calculation efficiency of operator, whether to support asynchronous calculation.
- Parameters
async_flag (bool) – Value of async flag. Default: false.
- attr(name=None, param_type=None, value_type=None, value=None, default_value=None, **kwargs)[source]
Register TBE op attribute information.
- Parameters
name (str) – Name of the attribute. Default: None.
param_type (str) – Param type of the attribute. Default: None.
value_type (str) – Type of the attribute. Default: None.
value (str) – Value of the attribute. Default: None.
default_value (str) – Default value of attribute. Default: None.
kwargs (dict) – Other information for the attribute.
- binfile_name(binfile_name)[source]
Binary file name of operator. The option is optional.
- Parameters
binfile_name (str) – File name of operator binary.
- compute_cost(compute_cost)[source]
Define the calculation efficiency of operator, which refers to cost model value of the tiling module.
- Parameters
compute_cost (int) – Value of compute cost. Default: 10.
- dynamic_format(dynamic_format)[source]
Whether the operator supports dynamic selection of format and dtype.
- Parameters
dynamic_format (bool) – Value of dynamic format. Default: false.
- input(index=None, name=None, need_compile=None, param_type=None, shape=None, **kwargs)[source]
Register TBE op input information.
- Parameters
index (int) – Order of the input. Default: None.
name (str) – Name of the input. Default: None.
need_compile (bool) – The input need compile whether or not. Default: None.
param_type (str) – Type of the input. Default: None.
shape (str) – Shape of the input. Default: None.
kwargs (dict) – Other information for the input.
- kernel_name(kernel_name)[source]
The name of operator kernel.
- Parameters
kernel_name (str) – Name of operator kernel.
- op_pattern(pattern=None)[source]
The behavior type of opeator, such as broadcast, reduce and so on.
- Parameters
pattern (str) – Value of op pattern.
- output(index=None, name=None, need_compile=None, param_type=None, shape=None, **kwargs)[source]
Register TBE op output information.
- Parameters
index (int) – Order of the output. Default: None.
name (str) – Name of the output. Default: None.
need_compile (bool) – The output need compile whether or not. Default: None.
param_type (str) – Type of the output. Default: None.
shape (str) – Shape of the output. Default: None.
kwargs (dict) – Other information for the output.
- mindspore.ops.constexpr(fn=None, get_instance=True, name=None)[source]
Makes a PrimitiveWithInfer operator, which infer the value while compiling. We can define a function to compute between constant variable and used in constructß.
- Parameters
Examples
>>> a = (1, 2) >>> # make a operator to calculate tuple len >>> @constexpr >>> def tuple_len(x): >>> return len(x) >>> assert tuple_len(a) == 2 >>> >>> # make a operator class to calculate tuple len >>> @constexpr(get_instance=False, name="TupleLen") >>> def tuple_len_class(x): >>> return len(x) >>> assert tuple_len_class()(a) == 2
- mindspore.ops.get_vm_impl_fn(prim)[source]
Gets vm function by primitive obj or primitive name for c++
- mindspore.ops.op_info_register(op_info)[source]
A decorator used as register of operator implementation.
Note
‘op_info’ must be a str of json format represent the op info, the op info will be added into oplib.
- mindspore.ops.prim_attr_register(fn)[source]
Primitive attributes register.
Registering the decorator of the built-in operator primitive __init__ function will add all the parameters of __init__ as operator attributes.
- Parameters
fn (function) – __init__ function of primitive.
- Returns
function, original function.