model

name: str = Field(default='Model', description='Name of the model')

Name of the model.

version: str = Field(default='1.0.0', description='Version of the model')

Version of the model.

description: str = Field(default='', description='Description of the model')

Description of the model.

tensors: dict[str, AirTensor] = Field(default_factory=dict, description='Mapping from tensor ID to its AirTensor metadata')

Mapping from tensor ID to its AirTensor metadata.

operators: list[AirOperator] = Field(default_factory=list, description='Topologically ordered list of operators (nodes) in the graph')

Topologically ordered list of operators (nodes) in the graph.

input_ids: list[str] = Field(default_factory=list, description='IDs of tensors that serve as model inputs')

IDs of tensors that serve as model inputs.

output_ids: list[str] = Field(default_factory=list, description='IDs of tensors that serve as model outputs')

IDs of tensors that serve as model outputs.

inputs: list[AirTensor]

List of AirTensor objects corresponding to model inputs.

outputs: list[AirTensor]

List of AirTensor objects corresponding to model outputs.

add_tensor(tensor: AirTensor) -> None

Register a new tensor in the model.

Raises

Errors raised by add_tensor
Type	Description
`ValueError`	If a tensor with the same ID already exists.

remove_tensor(tid: TensorId) -> None

Remove a tensor from the model by its ID.

Raises

Errors raised by remove_tensor
Type	Description
`KeyError`	If the tensor ID is not found.

add_operator(op: AirOperator) -> None

Append a new operator to the execution list.

Raises

Errors raised by add_operator
Type	Description
`ValueError`	If an operator with the same ID already exists.

has_tensor(tid: TensorId) -> bool

Check if a tensor exists in the model by its ID.

get_tensor(tid: TensorId) -> AirTensor

Lookup a tensor by its ID.

Raises

Errors raised by get_tensor
Type	Description
`KeyError`	If the tensor ID is not found.

tensor_is_shared(tid: TensorId, reader: AirOperator | None = None) -> bool

Whether anything other than reader uses tensor tid.

Uses are other operators, aliases in either direction (following alias chains transitively), and the model’s inputs and outputs. Rewriting a tensor in place is safe only when this is False.

Parameters

Parameters of tensor_is_shared
Name	Type	Default	Description
`tid`	`TensorId`	Required	The tensor to check.
`reader`	`AirOperator \| None`	None	The operator asking; its own references do not count.

Returns

Returns of tensor_is_shared
Value	Type	Description
`bool`	`bool`	``True`` when some other use exists.

rewrite_constant(reader: AirOperator, name: str | int, data) -> AirTensor

Bind reader’s tensor name to data, rewriting it only where that is safe.

The tensor is rewritten in place when nothing else uses it. Otherwise reader is rebound to a copy under <id>_rewritten (or the first free <id>_rewritten_N) whose packed_from names the source, so memory.tensors rules on the source id still place it.

Parameters

Parameters of rewrite_constant
Name	Type	Default	Description
`reader`	`AirOperator`	Required	The operator that owns the rewrite.
`name`	`str \| int`	Required	Its local name for the tensor, or the tensor's position in its inputs.
`data`		Required	The rewritten data.

Returns

Returns of rewrite_constant
Value	Type	Description
`AirTensor`	`AirTensor`	The tensor ``reader`` now reads.

topo_sort() -> list[AirOperator]

Return operators in execution order.

Assumes operators was populated in valid topological order.

prune_unused_tensors() -> list[TensorId]

Remove dangling tensors that are not referenced by any operator or model input/output.