onnxruntime-web
Version:
A Javascript library for running ONNX models on browsers
110 lines (109 loc) • 3.7 kB
JavaScript
;
// automatically generated by the FlatBuffers compiler, do not modify
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 (mod) {
if (mod && mod.__esModule) return mod;
var result = {};
if (mod != null)
for (var k in mod)
if (k !== 'default' && Object.prototype.hasOwnProperty.call(mod, k)) __createBinding(result, mod, k);
__setModuleDefault(result, mod);
return result;
};
Object.defineProperty(exports, '__esModule', { value: true });
exports.SparseTensor = void 0;
/* eslint-disable @typescript-eslint/no-unused-vars, @typescript-eslint/no-explicit-any, @typescript-eslint/no-non-null-assertion */
const flatbuffers = __importStar(require('flatbuffers'));
const tensor_js_1 = require('../../onnxruntime/fbs/tensor.js');
class SparseTensor {
constructor() {
this.bb = null;
this.bb_pos = 0;
}
__init(i, bb) {
this.bb_pos = i;
this.bb = bb;
return this;
}
static getRootAsSparseTensor(bb, obj) {
return (obj || new SparseTensor()).__init(bb.readInt32(bb.position()) + bb.position(), bb);
}
static getSizePrefixedRootAsSparseTensor(bb, obj) {
bb.setPosition(bb.position() + flatbuffers.SIZE_PREFIX_LENGTH);
return (obj || new SparseTensor()).__init(bb.readInt32(bb.position()) + bb.position(), bb);
}
values(obj) {
const offset = this.bb.__offset(this.bb_pos, 4);
return offset ? (obj || new tensor_js_1.Tensor()).__init(this.bb.__indirect(this.bb_pos + offset), this.bb) : null;
}
indices(obj) {
const offset = this.bb.__offset(this.bb_pos, 6);
return offset ? (obj || new tensor_js_1.Tensor()).__init(this.bb.__indirect(this.bb_pos + offset), this.bb) : null;
}
dims(index) {
const offset = this.bb.__offset(this.bb_pos, 8);
return offset ? this.bb.readInt64(this.bb.__vector(this.bb_pos + offset) + index * 8) : BigInt(0);
}
dimsLength() {
const offset = this.bb.__offset(this.bb_pos, 8);
return offset ? this.bb.__vector_len(this.bb_pos + offset) : 0;
}
static startSparseTensor(builder) {
builder.startObject(3);
}
static addValues(builder, valuesOffset) {
builder.addFieldOffset(0, valuesOffset, 0);
}
static addIndices(builder, indicesOffset) {
builder.addFieldOffset(1, indicesOffset, 0);
}
static addDims(builder, dimsOffset) {
builder.addFieldOffset(2, dimsOffset, 0);
}
static createDimsVector(builder, data) {
builder.startVector(8, data.length, 8);
for (let i = data.length - 1; i >= 0; i--) {
builder.addInt64(data[i]);
}
return builder.endVector();
}
static startDimsVector(builder, numElems) {
builder.startVector(8, numElems, 8);
}
static endSparseTensor(builder) {
const offset = builder.endObject();
return offset;
}
}
exports.SparseTensor = SparseTensor;
//# sourceMappingURL=sparse-tensor.js.map