@tensorflow/tfjs-core
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Hardware-accelerated JavaScript library for machine intelligence
54 lines (53 loc) • 3.93 kB
JavaScript
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
var erf_util = require("../../ops/erf_util");
var selu_util = require("../../ops/selu_util");
var UnaryOpProgram = (function () {
function UnaryOpProgram(aShape, opSnippet) {
this.variableNames = ['A'];
this.outputShape = aShape;
this.userCode = "\n float unaryOperation(float x) {\n " + opSnippet + "\n }\n\n void main() {\n float x = getAAtOutCoords();\n float y = unaryOperation(x);\n\n setOutput(y);\n }\n ";
}
return UnaryOpProgram;
}());
exports.UnaryOpProgram = UnaryOpProgram;
var CHECK_NAN_SNIPPET = "if (isNaN(x)) return x;";
exports.ABS = "return abs(x);";
exports.RELU = CHECK_NAN_SNIPPET + "\n return (x < 0.0) ? 0.0 : x;\n";
exports.ELU = "return (x >= 0.0) ? x : (exp(x) - 1.0);";
exports.SELU = "\n // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.\n // see: https://arxiv.org/abs/1706.02515\n float scaleAlpha = " + selu_util.SELU_SCALEALPHA + ";\n float scale = " + selu_util.SELU_SCALE + ";\n return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);\n";
function STEP(alpha) {
if (alpha === void 0) { alpha = 0.0; }
return CHECK_NAN_SNIPPET + ("\n return x > 0.0 ? 1.0 : float(" + alpha + ");\n ");
}
exports.STEP = STEP;
exports.NEG = "return -x;";
exports.CEIL = "return ceil(x);";
exports.FLOOR = "return floor(x);";
exports.SIGN = "\n if (isNaN(x)) { return 0.0; }\n return sign(x);\n";
exports.ROUND = "\n // OpenGL ES does not support round function.\n // The algorithm is based on banker's rounding.\n float base = floor(x);\n if ((x - base) < 0.5) {\n return floor(x);\n } else if ((x - base) > 0.5) {\n return ceil(x);\n } else {\n if (mod(base, 2.0) == 0.0) {\n return base;\n } else {\n return base + 1.0;\n }\n }\n";
exports.EXP = "return exp(x);";
exports.EXPM1 = "return exp(x) - 1.0;";
exports.LOG = "return log(x);";
exports.LOG1P = "return log(1.0 + x);";
exports.SQRT = "return sqrt(x);";
exports.RSQRT = "return inversesqrt(x);";
exports.SIGMOID = "return 1.0 / (1.0 + exp(-1.0 * x));";
exports.SOFTPLUS = "\n float epsilon = 1.1920928955078125e-7;\n float threshold = log(epsilon) + 2.0;\n\n bool too_large = x > -threshold;\n bool too_small = x < threshold;\n\n float result;\n float exp_x = exp(x);\n\n if (too_large){\n result = x;\n }\n else if (too_small){\n result = exp_x;\n }\n else{\n result = log(exp_x + 1.0);\n }\n return result;\n";
exports.SIN = "return sin(x);";
exports.COS = "return cos(x);";
exports.TAN = "return tan(x);";
exports.ASIN = "return asin(x);";
exports.ACOS = "return acos(x);";
exports.ATAN = CHECK_NAN_SNIPPET + "\n return atan(x);\n";
exports.SINH = "\n float e2x = exp(x);\n return (e2x - 1.0 / e2x) / 2.0;\n";
exports.COSH = "\n float e2x = exp(-x);\n return (e2x + 1.0 / e2x) / 2.0;\n";
exports.TANH = "\n float e2x = exp(-2.0 * abs(x));\n return sign(x) * (1.0 - e2x) / (1.0 + e2x);\n";
exports.ASINH = "return log(x + sqrt(x * x + 1.0));";
exports.ACOSH = "return log(x + sqrt(x * x - 1.0));";
exports.ATANH = "return (log(1.0 + x) - log(1.0 - x)) / 2.0;";
exports.ERF = "\n // Error function is calculated approximately with elementary function.\n // See \"Handbook of Mathematical Functions with Formulas,\n // Graphs, and Mathematical Tables\", Abramowitz and Stegun.\n float p = " + erf_util.ERF_P + ";\n float a1 = " + erf_util.ERF_A1 + ";\n float a2 = " + erf_util.ERF_A2 + ";\n float a3 = " + erf_util.ERF_A3 + ";\n float a4 = " + erf_util.ERF_A4 + ";\n float a5 = " + erf_util.ERF_A5 + ";\n\n float t = 1.0 / (1.0 + p * x);\n return 1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x);\n";
exports.SQUARE = "return x * x;";
exports.RECIPROCAL = "return 1.0 / x;";
exports.LOGICAL_NOT = "return float(!(x >= 1.0));";
exports.TO_INT = "return float(int(x));";