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| import * as tf from '@tensorflow/tfjs-core';
| import { pointwiseConvLayer } from './pointwiseConvLayer';
| var epsilon = 0.0010000000474974513;
| function depthwiseConvLayer(x, params, strides) {
| return tf.tidy(function () {
| var out = tf.depthwiseConv2d(x, params.filters, strides, 'same');
| out = tf.batchNorm(out, params.batch_norm_mean, params.batch_norm_variance, params.batch_norm_offset, params.batch_norm_scale, epsilon);
| return tf.clipByValue(out, 0, 6);
| });
| }
| function getStridesForLayerIdx(layerIdx) {
| return [2, 4, 6, 12].some(function (idx) { return idx === layerIdx; }) ? [2, 2] : [1, 1];
| }
| export function mobileNetV1(x, params) {
| return tf.tidy(function () {
| var conv11 = null;
| var out = pointwiseConvLayer(x, params.conv_0, [2, 2]);
| var convPairParams = [
| params.conv_1,
| params.conv_2,
| params.conv_3,
| params.conv_4,
| params.conv_5,
| params.conv_6,
| params.conv_7,
| params.conv_8,
| params.conv_9,
| params.conv_10,
| params.conv_11,
| params.conv_12,
| params.conv_13
| ];
| convPairParams.forEach(function (param, i) {
| var layerIdx = i + 1;
| var depthwiseConvStrides = getStridesForLayerIdx(layerIdx);
| out = depthwiseConvLayer(out, param.depthwise_conv, depthwiseConvStrides);
| out = pointwiseConvLayer(out, param.pointwise_conv, [1, 1]);
| if (layerIdx === 11) {
| conv11 = out;
| }
| });
| if (conv11 === null) {
| throw new Error('mobileNetV1 - output of conv layer 11 is null');
| }
| return {
| out: out,
| conv11: conv11
| };
| });
| }
| //# sourceMappingURL=mobileNetV1.js.map
|
|
