face-api/build/ssdMobilenetv1/extractParamsFromWeigthMap.js

import { disposeUnusedWeightTensors, extractWeightEntryFactory } from '../common';
import { isTensor3D } from '../utils';
function extractorsFactory(weightMap, paramMappings) {
    const extractWeightEntry = extractWeightEntryFactory(weightMap, paramMappings);
    function extractPointwiseConvParams(prefix, idx, mappedPrefix) {
        const filters = extractWeightEntry(`${prefix}/Conv2d_${idx}_pointwise/weights`, 4, `${mappedPrefix}/filters`);
        const batch_norm_offset = extractWeightEntry(`${prefix}/Conv2d_${idx}_pointwise/convolution_bn_offset`, 1, `${mappedPrefix}/batch_norm_offset`);
        return { filters, batch_norm_offset };
    }
    function extractConvPairParams(idx) {
        const mappedPrefix = `mobilenetv1/conv_${idx}`;
        const prefixDepthwiseConv = `MobilenetV1/Conv2d_${idx}_depthwise`;
        const mappedPrefixDepthwiseConv = `${mappedPrefix}/depthwise_conv`;
        const mappedPrefixPointwiseConv = `${mappedPrefix}/pointwise_conv`;
        const filters = extractWeightEntry(`${prefixDepthwiseConv}/depthwise_weights`, 4, `${mappedPrefixDepthwiseConv}/filters`);
        const batch_norm_scale = extractWeightEntry(`${prefixDepthwiseConv}/BatchNorm/gamma`, 1, `${mappedPrefixDepthwiseConv}/batch_norm_scale`);
        const batch_norm_offset = extractWeightEntry(`${prefixDepthwiseConv}/BatchNorm/beta`, 1, `${mappedPrefixDepthwiseConv}/batch_norm_offset`);
        const batch_norm_mean = extractWeightEntry(`${prefixDepthwiseConv}/BatchNorm/moving_mean`, 1, `${mappedPrefixDepthwiseConv}/batch_norm_mean`);
        const batch_norm_variance = extractWeightEntry(`${prefixDepthwiseConv}/BatchNorm/moving_variance`, 1, `${mappedPrefixDepthwiseConv}/batch_norm_variance`);
        return {
            depthwise_conv: {
                filters,
                batch_norm_scale,
                batch_norm_offset,
                batch_norm_mean,
                batch_norm_variance
            },
            pointwise_conv: extractPointwiseConvParams('MobilenetV1', idx, mappedPrefixPointwiseConv)
        };
    }
    function extractMobilenetV1Params() {
        return {
            conv_0: extractPointwiseConvParams('MobilenetV1', 0, 'mobilenetv1/conv_0'),
            conv_1: extractConvPairParams(1),
            conv_2: extractConvPairParams(2),
            conv_3: extractConvPairParams(3),
            conv_4: extractConvPairParams(4),
            conv_5: extractConvPairParams(5),
            conv_6: extractConvPairParams(6),
            conv_7: extractConvPairParams(7),
            conv_8: extractConvPairParams(8),
            conv_9: extractConvPairParams(9),
            conv_10: extractConvPairParams(10),
            conv_11: extractConvPairParams(11),
            conv_12: extractConvPairParams(12),
            conv_13: extractConvPairParams(13)
        };
    }
    function extractConvParams(prefix, mappedPrefix) {
        const filters = extractWeightEntry(`${prefix}/weights`, 4, `${mappedPrefix}/filters`);
        const bias = extractWeightEntry(`${prefix}/biases`, 1, `${mappedPrefix}/bias`);
        return { filters, bias };
    }
    function extractBoxPredictorParams(idx) {
        const box_encoding_predictor = extractConvParams(`Prediction/BoxPredictor_${idx}/BoxEncodingPredictor`, `prediction_layer/box_predictor_${idx}/box_encoding_predictor`);
        const class_predictor = extractConvParams(`Prediction/BoxPredictor_${idx}/ClassPredictor`, `prediction_layer/box_predictor_${idx}/class_predictor`);
        return { box_encoding_predictor, class_predictor };
    }
    function extractPredictionLayerParams() {
        return {
            conv_0: extractPointwiseConvParams('Prediction', 0, 'prediction_layer/conv_0'),
            conv_1: extractPointwiseConvParams('Prediction', 1, 'prediction_layer/conv_1'),
            conv_2: extractPointwiseConvParams('Prediction', 2, 'prediction_layer/conv_2'),
            conv_3: extractPointwiseConvParams('Prediction', 3, 'prediction_layer/conv_3'),
            conv_4: extractPointwiseConvParams('Prediction', 4, 'prediction_layer/conv_4'),
            conv_5: extractPointwiseConvParams('Prediction', 5, 'prediction_layer/conv_5'),
            conv_6: extractPointwiseConvParams('Prediction', 6, 'prediction_layer/conv_6'),
            conv_7: extractPointwiseConvParams('Prediction', 7, 'prediction_layer/conv_7'),
            box_predictor_0: extractBoxPredictorParams(0),
            box_predictor_1: extractBoxPredictorParams(1),
            box_predictor_2: extractBoxPredictorParams(2),
            box_predictor_3: extractBoxPredictorParams(3),
            box_predictor_4: extractBoxPredictorParams(4),
            box_predictor_5: extractBoxPredictorParams(5)
        };
    }
    return {
        extractMobilenetV1Params,
        extractPredictionLayerParams
    };
}
export function extractParamsFromWeigthMap(weightMap) {
    const paramMappings = [];
    const { extractMobilenetV1Params, extractPredictionLayerParams } = extractorsFactory(weightMap, paramMappings);
    const extra_dim = weightMap['Output/extra_dim'];
    paramMappings.push({ originalPath: 'Output/extra_dim', paramPath: 'output_layer/extra_dim' });
    if (!isTensor3D(extra_dim)) {
        throw new Error(`expected weightMap['Output/extra_dim'] to be a Tensor3D, instead have ${extra_dim}`);
    }
    const params = {
        mobilenetv1: extractMobilenetV1Params(),
        prediction_layer: extractPredictionLayerParams(),
        output_layer: {
            extra_dim
        }
    };
    disposeUnusedWeightTensors(weightMap, paramMappings);
    return { params, paramMappings };
}
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