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