@tensorflow/tfjs-core
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Hardware-accelerated JavaScript library for machine intelligence
29 lines • 1.65 kB
JavaScript
;
Object.defineProperty(exports, "__esModule", { value: true });
var broadcast_util = require("../../ops/broadcast_util");
var BatchNormProgram = (function () {
function BatchNormProgram(xShape, meanShape, varianceShape, offsetShape, scaleShape, varianceEpsilon) {
this.outputShape = [];
this.supportsBroadcasting = true;
this.variableNames = ['x', 'mean', 'variance'];
broadcast_util.assertAndGetBroadcastShape(xShape, meanShape);
broadcast_util.assertAndGetBroadcastShape(xShape, varianceShape);
var offsetSnippet = '0.0';
if (offsetShape != null) {
broadcast_util.assertAndGetBroadcastShape(xShape, offsetShape);
this.variableNames.push('offset');
offsetSnippet = 'getOffsetAtOutCoords()';
}
var scaleSnippet = '1.0';
if (scaleShape != null) {
broadcast_util.assertAndGetBroadcastShape(xShape, scaleShape);
this.variableNames.push('scale');
scaleSnippet = 'getScaleAtOutCoords()';
}
this.outputShape = xShape;
this.userCode = "\n void main() {\n float x = getXAtOutCoords();\n float mean = getMeanAtOutCoords();\n float variance = getVarianceAtOutCoords();\n float offset = " + offsetSnippet + ";\n float scale = " + scaleSnippet + ";\n float inv = scale * inversesqrt(variance + float(" + varianceEpsilon + "));\n setOutput((x - mean) * inv + offset);\n }\n ";
}
return BatchNormProgram;
}());
exports.BatchNormProgram = BatchNormProgram;
//# sourceMappingURL=batchnorm_gpu.js.map