@tensorflow/tfjs-core/dist/ops/ops.js

Hardware-accelerated JavaScript library for machine intelligence

"use strict";
function __export(m) {
    for (var p in m) if (!exports.hasOwnProperty(p)) exports[p] = m[p];
}
Object.defineProperty(exports, "__esModule", { value: true });
__export(require("./batchnorm"));
__export(require("./complex_ops"));
__export(require("./concat_split"));
__export(require("./conv"));
__export(require("./matmul"));
__export(require("./reverse"));
__export(require("./pool"));
__export(require("./slice"));
__export(require("./unary_ops"));
__export(require("./reduction_ops"));
__export(require("./compare"));
__export(require("./binary_ops"));
__export(require("./relu_ops"));
__export(require("./logical_ops"));
__export(require("./array_ops"));
__export(require("./tensor_ops"));
__export(require("./transpose"));
__export(require("./softmax"));
__export(require("./lrn"));
__export(require("./norm"));
__export(require("./segment_ops"));
__export(require("./lstm"));
__export(require("./moving_average"));
__export(require("./strided_slice"));
__export(require("./topk"));
__export(require("./scatter_nd"));
__export(require("./spectral_ops"));
__export(require("./sparse_to_dense"));
__export(require("./gather_nd"));
var operation_1 = require("./operation");
exports.op = operation_1.op;
var losses = require("./loss_ops");
exports.losses = losses;
var linalg = require("./linalg_ops");
exports.linalg = linalg;
var image = require("./image_ops");
exports.image = image;
var spectral = require("./spectral_ops");
exports.spectral = spectral;
//# sourceMappingURL=ops.js.map