qualia_codegen_core package

Subpackages

Submodules

Module contents

class qualia_codegen_core.Converter(output_path: Path | None = None)[source]

Bases: object

layer_template_files: ClassVar[dict[type[TBaseLayer], str | None]] = {<class 'qualia_codegen_core.graph.layers.TActivationLayer.TActivationLayer'>: 'activation', <class 'qualia_codegen_core.graph.layers.TAddLayer.TAddLayer'>: 'add', <class 'qualia_codegen_core.graph.layers.TAvgPooling1DLayer.TAvgPooling1DLayer'>: 'averagepool1d', <class 'qualia_codegen_core.graph.layers.TAvgPooling2DLayer.TAvgPooling2DLayer'>: 'averagepool2d', <class 'qualia_codegen_core.graph.layers.TBatchNormalization1DLayer.TBatchNormalization1DLayer'>: 'batchnorm1d', <class 'qualia_codegen_core.graph.layers.TBatchNormalization2DLayer.TBatchNormalization2DLayer'>: 'batchnorm2d', <class 'qualia_codegen_core.graph.layers.TConcatenateLayer.TConcatenateLayer'>: 'concatenate', <class 'qualia_codegen_core.graph.layers.TConv1DLayer.TConv1DLayer'>: 'conv1d', <class 'qualia_codegen_core.graph.layers.TConv2DLayer.TConv2DLayer'>: 'conv2d', <class 'qualia_codegen_core.graph.layers.TDenseLayer.TDenseLayer'>: 'fc', <class 'qualia_codegen_core.graph.layers.TFlattenLayer.TFlattenLayer'>: 'flatten', <class 'qualia_codegen_core.graph.layers.TInputLayer.TInputLayer'>: None, <class 'qualia_codegen_core.graph.layers.TMaxPooling1DLayer.TMaxPooling1DLayer'>: 'maxpool1d', <class 'qualia_codegen_core.graph.layers.TMaxPooling2DLayer.TMaxPooling2DLayer'>: 'maxpool2d', <class 'qualia_codegen_core.graph.layers.TPermuteLayer.TPermuteLayer'>: 'permute', <class 'qualia_codegen_core.graph.layers.TSampleNormLayer.TSampleNormLayer'>: 'samplenorm', <class 'qualia_codegen_core.graph.layers.TSliceLayer.TSliceLayer'>: 'slice', <class 'qualia_codegen_core.graph.layers.TSumLayer.TSumLayer'>: 'sum'}
TEMPLATE_PATH = PosixPath('/home/runner/work/qualia-codegen-core/qualia-codegen-core/src/qualia_codegen_core/assets')
weights2carray(node: LayerNode) → dict[str, dict[str, str | tuple[int, ...]]][source]
write_layer_function(template: str, node: LayerNode) → str[source]
write_layer_header(template: str, node: LayerNode) → str[source]
write_layer_weights(template: str, node: LayerNode) → str[source]
render_template(name: str, out: Path, **kwargs: Any) → str[source]
write_model_header(modelgraph: ModelGraph) → str[source]
write_model(modelgraph: ModelGraph, allocation: dict[str, list[list[LayerNode]] | dict[LayerNode, int]] | None) → str[source]
write_numeric_header() → str[source]
write_defines_header(modelgraph: ModelGraph) → str[source]
combine_zeropadding(modelgraph: ModelGraph) → ModelGraph | None[source]
remove_dropout(modelgraph: ModelGraph) → ModelGraph[source]
combine_relu(modelgraph: ModelGraph) → ModelGraph | None[source]
remove_identity(modelgraph: ModelGraph) → ModelGraph[source]
rename_operators(modelgraph: ModelGraph) → ModelGraph[source]
optimize_modelgraph(modelgraph: ModelGraph) → ModelGraph | None[source]
preprocess_modelgraph(modelgraph: ModelGraph) → ModelGraph | None[source]
validate_modelgraph(modelgraph: ModelGraph) → bool[source]
quantize_modelgraph(modelgraph: ModelGraph) → bool[source]
generate_code(modelgraph: ModelGraph, allocation: dict[str, list[list[LayerNode]] | dict[LayerNode, int]]) → str | None[source]
convert_model(modelgraph: ModelGraph) → str | None[source]
class qualia_codegen_core.MetricsConverter(output_path: Path | None = None)[source]

Bases: Converter

metric_classes: ClassVar[dict[str, str]] = {'acc': 'Accuracy', 'corr': 'PearsonCorrelationCoefficient', 'mae': 'MeanAbsoluteError', 'mse': 'MeanSquaredError', 'slope': 'Slope'}
write_metrics_header(metrics: list[str]) → str[source]
write_metrics(metrics: list[str]) → str[source]
convert_metrics(metrics: list[str]) → str | None[source]