"use strict"; /** * @license * Copyright 2017 Google Inc. All Rights Reserved. * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * ============================================================================= */ Object.defineProperty(exports, "__esModule", { value: true }); var LRNProgram = /** @class */ (function () { function LRNProgram(xShape, radius, bias, alpha, beta) { this.variableNames = ['x']; this.outputShape = []; var rad = radius; var maxD = xShape[3] - 1; this.outputShape = xShape; // optimize pow(bias + alpha * sum, -beta) // src: https://github.com/tensorflow/tensorflow/.. // blob/26033a1644a9c4a5fbe3170ab2e864b6a4ccd4ca/.. // tensorflow/core/kernels/mkl_lrn_op.cc#L320 var powOperator; var basis = "float(" + bias + ") + float(" + alpha + ") * sum"; if (beta === 0.5) { powOperator = "inversesqrt(" + basis + ")"; } else if (beta === 1.0) { powOperator = "1.0/(" + basis + ")"; } else { powOperator = "exp(log(" + basis + ") * float(-" + beta + "));"; } this.userCode = "\n void main() {\n ivec4 coords = getOutputCoords();\n int b = coords[0];\n int r = coords[1];\n int c = coords[2];\n int d = coords[3];\n float x = getX(b, r, c, d);\n float sum = 0.0;\n for (int j = -" + rad + "; j <= " + rad + "; j++) {\n int idx = d + j;\n if (idx >= 0 && idx <= " + maxD + ") {\n float z = getX(b, r, c, idx);\n sum += z * z;\n }\n }\n float val = x * " + powOperator + ";\n setOutput(val);\n }\n "; } return LRNProgram; }()); exports.LRNProgram = LRNProgram; //# sourceMappingURL=lrn_gpu.js.map