start¶

onnx_array_api.light_api.start(opset:int|None=None,opsets:Dict[str,int]|None=None,ir_version:int|None=None)→OnnxGraph[source]¶

Starts an onnx model.

Parameters:

• opset – main opset version

• opsets – others opsets as a dictionary

• ir_version – specify the ir_version as well

Returns:

an instance ofonnx_array_api.light_api.OnnxGraph

A very simple model:

<<<

fromonnx_array_api.light_apiimportstartonx=start().vin("X").Neg().rename("Y").vout().to_onnx()print(onx)

>>>

ir_version:11graph{node{input:"X"output:"Y"op_type:"Neg"domain:""}name:"light_api"input{name:"X"type{tensor_type{elem_type:1shape{}}}}output{name:"Y"type{tensor_type{elem_type:1shape{}}}}}opset_import{domain:""version:22}

Another with operator Add:

<<<

fromonnx_array_api.light_apiimportstartonx=start().vin("X").vin("Y").bring("X","Y").Add().rename("Z").vout().to_onnx()print(onx)

>>>

ir_version:11graph{node{input:"X"input:"Y"output:"Z"op_type:"Add"domain:""}name:"light_api"input{name:"X"type{tensor_type{elem_type:1shape{}}}}input{name:"Y"type{tensor_type{elem_type:1shape{}}}}output{name:"Z"type{tensor_type{elem_type:1shape{}}}}}opset_import{domain:""version:22}

g¶

onnx_array_api.light_api.g()→OnnxGraph[source]¶

Starts a subgraph.:return: an instance ofonnx_array_api.light_api.OnnxGraph

domain¶

..autofunction:: onnx_array_api.light_api.domain

BaseVar¶

classonnx_array_api.light_api.var.BaseVar(*args,**kwargs)[source]¶

Represents an input, an initializer, a node, an output,multiple variables.

Parameters:

parent – the graph containing the Variable

bring(*vars:List[str|Var])→Var|Vars[source]¶

Creates a set of variable as an instance ofonnx_array_api.light_api.Vars.

cst(value:ndarray,name:str|None=None)→Var[source]¶

Adds an initializer

Parameters:

• value – constant tensor

• name – input name

Returns:

instance ofonnx_array_api.light_api.Var

left_bring(*vars:List[str|Var])→Vars[source]¶

Creates a set of variables as an instance ofonnx_array_api.light_api.Vars.*vars is added to the left,self is added to the right.

make_node(op_type:str,*inputs:List[Var|TensorProto|ndarray],domain:str='',n_outputs:int=1,output_names:List[str]|None=None,**kwargs:Dict[str,Any])→Var|Vars[source]¶

Creates a node with this Var as the first input.

Parameters:

• op_type – operator type

• inputs – others inputs

• domain – domain

• n_outputs – number of outputs

• output_names – output names, if not specified, outputs are givenunique names

• kwargs – node attributes

Returns:

instance ofonnx_array_api.light_api.Var oronnx_array_api.light_api.Vars

right_bring(*vars:List[str|Var])→Vars[source]¶

Creates a set of variables as an instance ofonnx_array_api.light_api.Vars.*vars is added to the right,self is added to the left.

to_onnx()→FunctionProto|GraphProto|ModelProto[source]¶

Creates the onnx graph.

v(name:str)→Var[source]¶

Retrieves another variable than this one.

Parameters:

name – name of the variable

Returns:

instance ofonnx_array_api.light_api.Var

vin(name:str,elem_type:int|dtype=1,shape:Tuple[int,...]|None=None)→Var[source]¶

Declares a new input to the graph.

Parameters:

• name – input name

• elem_type – element_type

• shape – shape

Returns:

instance ofonnx_array_api.light_api.Var

vout(**kwargs:Dict[str,Any])→Var|Vars[source]¶

This method needs to be overwritten for Var and Vars dependingon the number of variable to declare as outputs.

OnnxGraph¶

classonnx_array_api.light_api.OnnxGraph(opset:int|None=None,opsets:Dict[str,int]|None=None,ir_version:int|None=None,proto_type:ProtoType=ProtoType.MODEL)[source]¶

Contains every piece needed to create an onnx model in a single instructions.This API is meant to be light and allows the description of a graph.

Parameters:

• opset – main opset version

• opsets – other opsets as a dictionary

• ir_version – to specify an ir_version

• is_function – aonnx.ModelProto or aonnx.FunctionProto

cst(value:ndarray,name:str|None=None)→Var[source]¶

Adds an initializer

Parameters:

• value – constant tensor

• name – input name

Returns:

instance ofonnx_array_api.light_api.Var

has_name(name:str)→bool[source]¶

Tells if a name is already used.

propertyinput_names:List[str]¶

Returns the input names

make_constant(value:ndarray,name:str|None=None)→TensorProto[source]¶

Adds an initializer to the graph.

make_input(name:str,elem_type:int|dtype=1,shape:Tuple[int,...]|None=None)→ValueInfoProto[source]¶

Adds an input to the graph.

Parameters:

• name – input name

• elem_type – element type (the input is assumed to be a tensor)

• shape – shape

Returns:

an instance of ValueInfoProto

make_node(op_type:str,*inputs:List[Var|TensorProto|ndarray],domain:str='',n_outputs:int=1,output_names:List[str]|None=None,**kwargs:Dict[str,Any])→NodeProto[source]¶

Creates a node.

Parameters:

• op_type – operator type

• inputs – others inputs

• domain – domain

• n_outputs – number of outputs

• output_names – output names, if not specified, outputs are givenunique names

• kwargs – node attributes

Returns:

NodeProto

make_output(name:str,elem_type:int|dtype=1,shape:Tuple[int,...]|None=None)→ValueInfoProto[source]¶

Adds an output to the graph.

Parameters:

• name – input name

• elem_type – element type (the input is assumed to be a tensor)

• shape – shape

Returns:

an instance of ValueInfoProto

If the checker fails, tryshape=[].

propertyoutput_names:List[str]¶

Returns the output names

rename(old_name:str,new_name:str)[source]¶

Renames a variable. The renaming does notchange anything but is stored in a container.

Parameters:

• old_name – old name

• new_name – new name

to_onnx()→FunctionProto|GraphProto|ModelProto[source]¶

Converts the graph into an ONNX graph.

true_name(name:str)→str[source]¶

Some names were renamed. If name is one of them, the functionreturns the new name.

unique_name(prefix='r',value:Any|None=None)→str[source]¶

Returns a unique name.

Parameters:

• prefix – prefix

• value – this name is mapped to this value

Returns:

unique name

vin(name:str,elem_type:int|dtype=1,shape:Tuple[int,...]|None=None)→Var[source]¶

Declares a new input to the graph.

Parameters:

• name – input name

• elem_type – element_type

• shape – shape

Returns:

instance ofonnx_array_api.light_api.Var

ProtoType¶

classonnx_array_api.light_api.model.ProtoType(*values)[source]¶

The same code can be used to output a GraphProto, a FunctionProto or a ModelProto.This class specifies the output type at the beginning of the code.

SubDomain¶

classonnx_array_api.light_api.var.SubDomain(var:BaseVar)[source]¶

Declares a domain or a piece of it (if it contains ‘.’ in its name).

Var¶

classonnx_array_api.light_api.Var(*args,**kwargs)[source]¶

Represents an input, an initializer, a node, an output.

Parameters:

• parent – graph the variable belongs to

• name – input name

• elem_type – element_type

• shape – shape

astype(to:int|dtype)→Var[source]¶

Casts a tensor into another element type.

bring(*vars:List[str|Var])→Var|Vars¶

Creates a set of variable as an instance ofonnx_array_api.light_api.Vars.

cst(value:ndarray,name:str|None=None)→Var¶

Adds an initializer

Parameters:

• value – constant tensor

• name – input name

Returns:

instance ofonnx_array_api.light_api.Var

left_bring(*vars:List[str|Var])→Vars¶

Creates a set of variables as an instance ofonnx_array_api.light_api.Vars.*vars is added to the left,self is added to the right.

make_node(op_type:str,*inputs:List[Var|TensorProto|ndarray],domain:str='',n_outputs:int=1,output_names:List[str]|None=None,**kwargs:Dict[str,Any])→Var|Vars¶

Creates a node with this Var as the first input.

Parameters:

• op_type – operator type

• inputs – others inputs

• domain – domain

• n_outputs – number of outputs

• output_names – output names, if not specified, outputs are givenunique names

• kwargs – node attributes

Returns:

instance ofonnx_array_api.light_api.Var oronnx_array_api.light_api.Vars

propertyname¶

Returns the name of the variable or the new name if it was renamed.

rename(new_name:str)→Var[source]¶

Renames a variable.

reshape(new_shape:Var|TensorProto|ndarray)→Var[source]¶

Reshapes a variable.

right_bring(*vars:List[str|Var])→Vars¶

Creates a set of variables as an instance ofonnx_array_api.light_api.Vars.*vars is added to the right,self is added to the left.

to(to:int|dtype)→Var[source]¶

Casts a tensor into another element type.

to_onnx()→FunctionProto|GraphProto|ModelProto¶

Creates the onnx graph.

v(name:str)→Var¶

Retrieves another variable than this one.

Parameters:

name – name of the variable

Returns:

instance ofonnx_array_api.light_api.Var

vin(name:str,elem_type:int|dtype=1,shape:Tuple[int,...]|None=None)→Var¶

Declares a new input to the graph.

Parameters:

• name – input name

• elem_type – element_type

• shape – shape

Returns:

instance ofonnx_array_api.light_api.Var

vout(elem_type:int|dtype=1,shape:Tuple[int,...]|None=None)→Var[source]¶

Declares a new output to the graph.

Parameters:

• elem_type – element_type

• shape – shape

Returns:

instance ofonnx_array_api.light_api.Var

If the checker fails, tryshape=[].

Vars¶

classonnx_array_api.light_api.Vars(*args,**kwargs)[source]¶

Represents multiple Var.

Parameters:

• parent – graph the variable belongs to

• vars – list of names or variables

bring(*vars:List[str|Var])→Var|Vars¶

Creates a set of variable as an instance ofonnx_array_api.light_api.Vars.

cst(value:ndarray,name:str|None=None)→Var¶

Adds an initializer

Parameters:

• value – constant tensor

• name – input name

Returns:

instance ofonnx_array_api.light_api.Var

left_bring(*vars:List[str|Var])→Vars¶

Creates a set of variables as an instance ofonnx_array_api.light_api.Vars.*vars is added to the left,self is added to the right.

make_node(op_type:str,*inputs:List[Var|TensorProto|ndarray],domain:str='',n_outputs:int=1,output_names:List[str]|None=None,**kwargs:Dict[str,Any])→Var|Vars¶

Creates a node with this Var as the first input.

Parameters:

• op_type – operator type

• inputs – others inputs

• domain – domain

• n_outputs – number of outputs

• output_names – output names, if not specified, outputs are givenunique names

• kwargs – node attributes

Returns:

instance ofonnx_array_api.light_api.Var oronnx_array_api.light_api.Vars

rename(*new_names:List[str])→Vars[source]¶

Renames variables.

right_bring(*vars:List[str|Var])→Vars¶

Creates a set of variables as an instance ofonnx_array_api.light_api.Vars.*vars is added to the right,self is added to the left.

to_onnx()→FunctionProto|GraphProto|ModelProto¶

Creates the onnx graph.

v(name:str)→Var¶

Retrieves another variable than this one.

Parameters:

name – name of the variable

Returns:

instance ofonnx_array_api.light_api.Var

vin(name:str,elem_type:int|dtype=1,shape:Tuple[int,...]|None=None)→Var¶

Declares a new input to the graph.

Parameters:

• name – input name

• elem_type – element_type

• shape – shape

Returns:

instance ofonnx_array_api.light_api.Var

vout(*elem_type_shape:List[int|dtype|Tuple[int|dtype,Tuple[int,...]|None]])→Vars[source]¶

Declares a new output to the graph.

Parameters:

elem_type_shape – list of tuple(element_type, shape)

Returns:

instance ofonnx_array_api.light_api.Vars

If the checker fails, tryshape=[].

One input¶

classonnx_array_api.light_api._op_var.OpsVar[source]¶

Operators taking only one input.

Two inputs or more¶

classonnx_array_api.light_api._op_vars.OpsVars[source]¶

Operators taking multiple inputs.