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apache-arrow

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"use strict"; // automatically generated by the FlatBuffers compiler, do not modify Object.defineProperty(exports, "__esModule", { value: true }); exports.Tensor = void 0; const tslib_1 = require("tslib"); const flatbuffers = tslib_1.__importStar(require("flatbuffers")); const buffer_js_1 = require("./buffer.js"); const tensor_dim_js_1 = require("./tensor-dim.js"); const type_js_1 = require("./type.js"); class Tensor { constructor() { this.bb = null; this.bb_pos = 0; } __init(i, bb) { this.bb_pos = i; this.bb = bb; return this; } static getRootAsTensor(bb, obj) { return (obj || new Tensor()).__init(bb.readInt32(bb.position()) + bb.position(), bb); } static getSizePrefixedRootAsTensor(bb, obj) { bb.setPosition(bb.position() + flatbuffers.SIZE_PREFIX_LENGTH); return (obj || new Tensor()).__init(bb.readInt32(bb.position()) + bb.position(), bb); } typeType() { const offset = this.bb.__offset(this.bb_pos, 4); return offset ? this.bb.readUint8(this.bb_pos + offset) : type_js_1.Type.NONE; } /** * The type of data contained in a value cell. Currently only fixed-width * value types are supported, no strings or nested types */ // @ts-ignore type(obj) { const offset = this.bb.__offset(this.bb_pos, 6); return offset ? this.bb.__union(obj, this.bb_pos + offset) : null; } /** * The dimensions of the tensor, optionally named */ shape(index, obj) { const offset = this.bb.__offset(this.bb_pos, 8); return offset ? (obj || new tensor_dim_js_1.TensorDim()).__init(this.bb.__indirect(this.bb.__vector(this.bb_pos + offset) + index * 4), this.bb) : null; } shapeLength() { const offset = this.bb.__offset(this.bb_pos, 8); return offset ? this.bb.__vector_len(this.bb_pos + offset) : 0; } /** * Non-negative byte offsets to advance one value cell along each dimension * If omitted, default to row-major order (C-like). */ strides(index) { const offset = this.bb.__offset(this.bb_pos, 10); return offset ? this.bb.readInt64(this.bb.__vector(this.bb_pos + offset) + index * 8) : this.bb.createLong(0, 0); } stridesLength() { const offset = this.bb.__offset(this.bb_pos, 10); return offset ? this.bb.__vector_len(this.bb_pos + offset) : 0; } /** * The location and size of the tensor's data */ data(obj) { const offset = this.bb.__offset(this.bb_pos, 12); return offset ? (obj || new buffer_js_1.Buffer()).__init(this.bb_pos + offset, this.bb) : null; } static startTensor(builder) { builder.startObject(5); } static addTypeType(builder, typeType) { builder.addFieldInt8(0, typeType, type_js_1.Type.NONE); } static addType(builder, typeOffset) { builder.addFieldOffset(1, typeOffset, 0); } static addShape(builder, shapeOffset) { builder.addFieldOffset(2, shapeOffset, 0); } static createShapeVector(builder, data) { builder.startVector(4, data.length, 4); for (let i = data.length - 1; i >= 0; i--) { builder.addOffset(data[i]); } return builder.endVector(); } static startShapeVector(builder, numElems) { builder.startVector(4, numElems, 4); } static addStrides(builder, stridesOffset) { builder.addFieldOffset(3, stridesOffset, 0); } static createStridesVector(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 startStridesVector(builder, numElems) { builder.startVector(8, numElems, 8); } static addData(builder, dataOffset) { builder.addFieldStruct(4, dataOffset, 0); } static endTensor(builder) { const offset = builder.endObject(); builder.requiredField(offset, 6); // type builder.requiredField(offset, 8); // shape builder.requiredField(offset, 12); // data return offset; } static finishTensorBuffer(builder, offset) { builder.finish(offset); } static finishSizePrefixedTensorBuffer(builder, offset) { builder.finish(offset, undefined, true); } } exports.Tensor = Tensor; //# sourceMappingURL=tensor.js.map