tensorflow-helpers/tensor.js

Helper functions to use tensorflow in nodejs for transfer learning, image classification, and more

"use strict";
var __createBinding = (this && this.__createBinding) || (Object.create ? (function(o, m, k, k2) {
    if (k2 === undefined) k2 = k;
    var desc = Object.getOwnPropertyDescriptor(m, k);
    if (!desc || ("get" in desc ? !m.__esModule : desc.writable || desc.configurable)) {
      desc = { enumerable: true, get: function() { return m[k]; } };
    }
    Object.defineProperty(o, k2, desc);
}) : (function(o, m, k, k2) {
    if (k2 === undefined) k2 = k;
    o[k2] = m[k];
}));
var __setModuleDefault = (this && this.__setModuleDefault) || (Object.create ? (function(o, v) {
    Object.defineProperty(o, "default", { enumerable: true, value: v });
}) : function(o, v) {
    o["default"] = v;
});
var __importStar = (this && this.__importStar) || (function () {
    var ownKeys = function(o) {
        ownKeys = Object.getOwnPropertyNames || function (o) {
            var ar = [];
            for (var k in o) if (Object.prototype.hasOwnProperty.call(o, k)) ar[ar.length] = k;
            return ar;
        };
        return ownKeys(o);
    };
    return function (mod) {
        if (mod && mod.__esModule) return mod;
        var result = {};
        if (mod != null) for (var k = ownKeys(mod), i = 0; i < k.length; i++) if (k[i] !== "default") __createBinding(result, mod, k[i]);
        __setModuleDefault(result, mod);
        return result;
    };
})();
Object.defineProperty(exports, "__esModule", { value: true });
exports.disposeTensor = disposeTensor;
exports.toOneTensor = toOneTensor;
exports.toTensor4D = toTensor4D;
exports.toTensor3D = toTensor3D;
const tf = __importStar(require("@tensorflow/tfjs-core"));
function disposeTensor(tensor) {
    if (Array.isArray(tensor)) {
        for (let t of tensor) {
            t.dispose();
        }
    }
    else {
        tensor.dispose();
    }
}
function toOneTensor(tensor) {
    if (!Array.isArray(tensor)) {
        return tensor;
    }
    if (tensor.length == 0) {
        throw new Error('expect at least one tensor');
    }
    let result = tf.concat(tensor);
    disposeTensor(tensor);
    return result;
}
function toTensor4D(tensor) {
    if (tensor.rank == 4) {
        return tensor;
    }
    let tensor4D = tf.expandDims(tensor, 0);
    tensor.dispose();
    return tensor4D;
}
function toTensor3D(tensor) {
    if (tensor.rank == 3) {
        return tensor;
    }
    let tensor3D = tensor.squeeze([0]);
    tensor.dispose();
    return tensor3D;
}