qualia_codegen_core.graph package

Subpackages

Submodules

Module contents

class qualia_codegen_core.graph.ModelGraph(nodes: list[LayerNode] | None = None)[source]

Bases: object

add_node(node: LayerNode, innodes: Iterable[LayerNode] | None = None, outnodes: Iterable[LayerNode] | None = None) → None[source]
delete_node(node: LayerNode) → None[source]
delete_node_if(predicate: Callable[[LayerNode], bool]) → None[source]
replace_node(oldnode: LayerNode, newnode: LayerNode) → None[source]
find_node_from_layer(layer: TBaseLayer) → LayerNode | None[source]
get_nodes_for_layers(layers: TBaseLayer | Iterable[TBaseLayer]) → tuple[LayerNode | None, ...][source]
no_none_in_nodes(nodes: Iterable[LayerNode | None]) → TypeGuard[Iterable[LayerNode]][source]
add_layer(layer: TBaseLayer, inlayers: list[TBaseLayer] | None = None, outlayers: list[TBaseLayer] | None = None) → None[source]
property nodes: list[LayerNode]
graphviz() → str | None[source]
classmethod auto_detect(obj: keras.Model | nn.Module) → ModelGraph[source]
class qualia_codegen_core.graph.Quantization(number_type: 'type[int | float] | None' = None, width: 'int | None' = None, long_width: 'int | None' = None, weights_scale_factor: 'int | None' = None, bias_scale_factor: 'int | None' = None, output_scale_factor: 'int | None' = None, weights_round_mode: 'RoundMode | None' = None, output_round_mode: 'RoundMode | None' = None)[source]

Bases: object

number_type: type[int | float] | None = None
width: int | None = None
long_width: int | None = None
weights_scale_factor: int | None = None
bias_scale_factor: int | None = None
output_scale_factor: int | None = None
weights_round_mode: RoundMode | None = None
output_round_mode: RoundMode | None = None