"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 DepthwiseConv2DProgram = /** @class */ (function () {
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function DepthwiseConv2DProgram(convInfo, addBias, activation, hasPreluActivation) {
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if (addBias === void 0) { addBias = false; }
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if (activation === void 0) { activation = null; }
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if (hasPreluActivation === void 0) { hasPreluActivation = false; }
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this.variableNames = ['x', 'W'];
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this.outputShape = convInfo.outShape;
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var xNumRows = convInfo.inHeight;
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var xNumCols = convInfo.inWidth;
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var padTop = convInfo.padInfo.top;
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var padLeft = convInfo.padInfo.left;
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var strideHeight = convInfo.strideHeight;
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var strideWidth = convInfo.strideWidth;
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var dilationHeight = convInfo.dilationHeight;
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var dilationWidth = convInfo.dilationWidth;
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var filterHeight = convInfo.filterHeight;
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var filterWidth = convInfo.filterWidth;
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var channelMul = convInfo.outChannels / convInfo.inChannels;
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var activationSnippet = '', applyActivationSnippet = '';
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if (activation) {
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if (hasPreluActivation) {
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activationSnippet = "float activation(float a) {\n float b = getPreluActivationWeightsAtOutCoords();\n " + activation + "\n }";
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}
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else {
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activationSnippet = "\n float activation(float x) {\n " + activation + "\n }\n ";
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}
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applyActivationSnippet = "result = activation(result);";
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}
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var addBiasSnippet = addBias ? 'result += getBiasAtOutCoords();' : '';
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if (addBias) {
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this.variableNames.push('bias');
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}
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if (hasPreluActivation) {
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this.variableNames.push('preluActivationWeights');
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}
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this.userCode = "\n " + activationSnippet + "\n\n const ivec2 strides = ivec2(" + strideHeight + ", " + strideWidth + ");\n const ivec2 pads = ivec2(" + padTop + ", " + padLeft + ");\n\n void main() {\n ivec4 coords = getOutputCoords();\n int batch = coords.x;\n ivec2 xRCCorner = coords.yz * strides - pads;\n int d2 = coords.w;\n int d1 = d2 / " + channelMul + ";\n int q = d2 - d1 * " + channelMul + ";\n\n int xRCorner = xRCCorner.x;\n int xCCorner = xRCCorner.y;\n\n // Convolve x(?, ?, d1) with w(:, :, d1, q) to get y(yR, yC, d2).\n // ? = to be determined. : = across all values in that axis.\n float dotProd = 0.0;\n // TO DO(dsmilkov): Flatten the two for loops and vec4 the operations.\n for (int wR = 0; wR < " + filterHeight + "; wR++) {\n int xR = xRCorner + wR * " + dilationHeight + ";\n\n if (xR < 0 || xR >= " + xNumRows + ") {\n continue;\n }\n\n for (int wC = 0; wC < " + filterWidth + "; wC++) {\n int xC = xCCorner + wC * " + dilationWidth + ";\n\n if (xC < 0 || xC >= " + xNumCols + ") {\n continue;\n }\n\n float xVal = getX(batch, xR, xC, d1);\n float wVal = getW(wR, wC, d1, q);\n dotProd += xVal * wVal;\n }\n }\n\n float result = dotProd;\n " + addBiasSnippet + "\n " + applyActivationSnippet + "\n setOutput(result);\n }\n ";
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}
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return DepthwiseConv2DProgram;
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}());
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exports.DepthwiseConv2DProgram = DepthwiseConv2DProgram;
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//# sourceMappingURL=conv_gpu_depthwise.js.map
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