.xshape.shape_builder_impl

class experimental_experiment.xshape.shape_builder_impl.BasicShapeBuilder(verbose: int = 0, opset: int | None = None)

Implements a basic class doing shape inference in an ONNX model.

A couple of environment variables can be set to help debugging any issue.

• ONNXSTOPSHAPE=<name>: raises an exception when name receives a shape.

• ONNXSTOPTYPE=<name>: raises an exception when name receives a type.

• ONNXDYNDIM=<name>: raises an exception when dimension name is used

• ONNXCST=1: shows which constant is requested

• ONNXSHAPECOMPUTE=1: raises an exception when a shape is missing

• ONNXSTOPVALUESHAPE=<name>: more information in function dealing with shapes

add_dynamic_dimension(name: str)

Adds a dynamic dimension.

get_constant(name: str, exc: bool = True, computed_value: bool = False, as_shape: bool = False, multiple_outputs: bool = False) → ndarray | NodeProto

The method returns the constant name. It is a tensor (numpy array) or a NodeProto which must be evaluated. If computed_value is True, the NodeProto is evaluated with the ReferenceEvaluator.

Parameters:

• name – constant name

• exc – raise an exception if anything is impossible to do

• computed_value – compute the value if not a constant

• as_shape – returns a tuple for a shape

• multiple_outputs – allow multiple outputs

Returns:

value

get_debug_msg(limit: int = 1000) → str

Returns a string providing as much information as possible to help the developper understand why a conversion failed.

Parameters:

limit – limit the string if the model is big

Returns:

many pieces of informations about the on going conversion

get_rank(name: str) → int

Returns the rank of a result.

get_shape(name: str) → Tuple[int | torch.SymInt | torch.SymFloat | float | str, ...]

Returns the shape of a result.

get_type(name: str) → int

Returns the type of a result.

has_rank(name: str) → bool

Tells if a result has a rank.

has_shape(name: str, full=False) → bool

Tells if a result has a shape. If full is True, it returns True if the shape exists and if it is a static shape with all dimensions > 0.

has_type(name: str) → bool | int

Tells if a result has a type. This should be always true.

is_constant(name: str) → bool

Tells if a result is a constant.

register_constraint_dimension(dim_name: str, value: Any)

Registers a constraint on a dimension.

Parameters:

• dim_name – dimension name

• value – value to register

register_dynamic_objects_from_dim(dim: str)

Registers all the dynamic objects required in a dimension.

run_model(model: ModelProto | GraphProto, functions: Dict[Tuple[str, str], FunctionProto] | None = None, exc: bool = False)

Runs inference over a model or a graph.

run_node(node: NodeProto, exc: bool = False)

Uses shapes availables in the ShapeBuilder to infer the output shapes and types.

run_value_info(info: ValueInfoProto, is_input: bool)

Fills ShapeBuilder with information coming from an input or output.

set_constant(name: str, value: TensorProto | NodeProto) → bool

Tells if a result is a constant.

set_rank(name: str, value: int) → bool

Sets the rank for a result.

Parameters:

• name – result name

• value – rank

Returns:

True if there is no rank conflict

set_shape(name: str, shape: Tuple[int | torch.SymInt | torch.SymFloat | float | str, ...], exc: bool = False, **_kwargs)

Sets the shape for a result. It is exists, it checks the new shape is equal to the existing one.

Parameters:

• name – result name

• shape – shape

• exc – raise an exception if inconsistency

set_type(name: str, dtype: int, exc: bool = True) → bool

Sets the shape for a result. It is exists, it checks the new shape is equal to the existing one.

Parameters:

• name – name

• dtype – element type (an integer, ONNX), 0 (unknonw is a possible value)

• exc – raises an exception

Returns:

returns True if there is no type conflict

set_value_shape(name: str, value: Any, equal_to: Tuple[str, str] | None = None)

Sets the value for a shape result.

Parameters:

• name – name

• value – it cannot be empty

• equal_to – if specified, the value is also equal to this value

A value can be a string (for an unknown shape, a tuple for a shape, an integer for a single scalar.

value_as_shape(name: str) → bool

Returns the value of a result if it is a shape.