chore: update node_modules with new binary files and dependencies
- Add new binary files for nodemon, onnxruntime-web, and xenova/transformers - Update various JavaScript and TypeScript files in node_modules - Remove unused files and dependencies - Add new test fixtures and documentation files
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357
node_modules/onnxruntime-common/lib/tensor.ts
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node_modules/onnxruntime-common/lib/tensor.ts
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// Copyright (c) Microsoft Corporation. All rights reserved.
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// Licensed under the MIT License.
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import {Tensor as TensorImpl} from './tensor-impl';
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import {TypedTensorUtils} from './tensor-utils';
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/* eslint-disable @typescript-eslint/no-redeclare */
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/**
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* represent a basic tensor with specified dimensions and data type.
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*/
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interface TypedTensorBase<T extends Tensor.Type> {
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/**
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* Get the dimensions of the tensor.
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*/
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readonly dims: readonly number[];
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/**
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* Get the data type of the tensor.
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*/
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readonly type: T;
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/**
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* Get the buffer data of the tensor.
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*/
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readonly data: Tensor.DataTypeMap[T];
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}
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export declare namespace Tensor {
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interface DataTypeMap {
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float32: Float32Array;
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uint8: Uint8Array;
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int8: Int8Array;
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uint16: Uint16Array;
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int16: Int16Array;
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int32: Int32Array;
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int64: BigInt64Array;
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string: string[];
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bool: Uint8Array;
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float16: never; // hold on using Uint16Array before we have a concrete solution for float 16
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float64: Float64Array;
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uint32: Uint32Array;
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uint64: BigUint64Array;
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// complex64: never;
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// complex128: never;
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// bfloat16: never;
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}
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interface ElementTypeMap {
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float32: number;
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uint8: number;
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int8: number;
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uint16: number;
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int16: number;
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int32: number;
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int64: bigint;
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string: string;
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bool: boolean;
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float16: never; // hold on before we have a concret solution for float 16
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float64: number;
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uint32: number;
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uint64: bigint;
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// complex64: never;
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// complex128: never;
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// bfloat16: never;
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}
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type DataType = DataTypeMap[Type];
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type ElementType = ElementTypeMap[Type];
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/**
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* represent the data type of a tensor
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*/
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export type Type = keyof DataTypeMap;
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}
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/**
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* Represent multi-dimensional arrays to feed to or fetch from model inferencing.
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*/
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export interface TypedTensor<T extends Tensor.Type> extends TypedTensorBase<T>, TypedTensorUtils<T> {}
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/**
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* Represent multi-dimensional arrays to feed to or fetch from model inferencing.
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*/
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export interface Tensor extends TypedTensorBase<Tensor.Type>, TypedTensorUtils<Tensor.Type> {}
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export interface TensorConstructor {
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// #region specify element type
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/**
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* Construct a new string tensor object from the given type, data and dims.
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*
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* @param type - Specify the element type.
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* @param data - Specify the tensor data
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new(type: 'string', data: Tensor.DataTypeMap['string']|readonly string[],
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dims?: readonly number[]): TypedTensor<'string'>;
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/**
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* Construct a new bool tensor object from the given type, data and dims.
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*
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* @param type - Specify the element type.
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* @param data - Specify the tensor data
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new(type: 'bool', data: Tensor.DataTypeMap['bool']|readonly boolean[], dims?: readonly number[]): TypedTensor<'bool'>;
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/**
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* Construct a new numeric tensor object from the given type, data and dims.
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*
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* @param type - Specify the element type.
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* @param data - Specify the tensor data
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new<T extends Exclude<Tensor.Type, 'string'|'bool'>>(
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type: T, data: Tensor.DataTypeMap[T]|readonly number[], dims?: readonly number[]): TypedTensor<T>;
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// #endregion
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// #region infer element types
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/**
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* Construct a new float32 tensor object from the given data and dims.
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*
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* @param data - Specify the tensor data
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new(data: Float32Array, dims?: readonly number[]): TypedTensor<'float32'>;
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/**
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* Construct a new int8 tensor object from the given data and dims.
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*
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* @param data - Specify the tensor data
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new(data: Int8Array, dims?: readonly number[]): TypedTensor<'int8'>;
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/**
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* Construct a new uint8 tensor object from the given data and dims.
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*
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* @param data - Specify the tensor data
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new(data: Uint8Array, dims?: readonly number[]): TypedTensor<'uint8'>;
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/**
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* Construct a new uint16 tensor object from the given data and dims.
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*
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* @param data - Specify the tensor data
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new(data: Uint16Array, dims?: readonly number[]): TypedTensor<'uint16'>;
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/**
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* Construct a new int16 tensor object from the given data and dims.
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*
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* @param data - Specify the tensor data
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new(data: Int16Array, dims?: readonly number[]): TypedTensor<'int16'>;
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/**
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* Construct a new int32 tensor object from the given data and dims.
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*
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* @param data - Specify the tensor data
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new(data: Int32Array, dims?: readonly number[]): TypedTensor<'int32'>;
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/**
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* Construct a new int64 tensor object from the given data and dims.
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*
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* @param data - Specify the tensor data
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new(data: BigInt64Array, dims?: readonly number[]): TypedTensor<'int64'>;
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/**
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* Construct a new string tensor object from the given data and dims.
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*
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* @param data - Specify the tensor data
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new(data: readonly string[], dims?: readonly number[]): TypedTensor<'string'>;
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/**
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* Construct a new bool tensor object from the given data and dims.
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*
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* @param data - Specify the tensor data
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new(data: readonly boolean[], dims?: readonly number[]): TypedTensor<'bool'>;
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/**
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* Construct a new float64 tensor object from the given data and dims.
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*
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* @param data - Specify the tensor data
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new(data: Float64Array, dims?: readonly number[]): TypedTensor<'float64'>;
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/**
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* Construct a new uint32 tensor object from the given data and dims.
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*
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* @param data - Specify the tensor data
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new(data: Uint32Array, dims?: readonly number[]): TypedTensor<'uint32'>;
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/**
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* Construct a new uint64 tensor object from the given data and dims.
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*
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* @param data - Specify the tensor data
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new(data: BigUint64Array, dims?: readonly number[]): TypedTensor<'uint64'>;
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// #endregion
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// #region fall back to non-generic tensor type declaration
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/**
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* Construct a new tensor object from the given type, data and dims.
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*
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* @param type - Specify the element type.
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* @param data - Specify the tensor data
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new(type: Tensor.Type, data: Tensor.DataType|readonly number[]|readonly boolean[], dims?: readonly number[]): Tensor;
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/**
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* Construct a new tensor object from the given data and dims.
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*
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* @param data - Specify the tensor data
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new(data: Tensor.DataType, dims?: readonly number[]): Tensor;
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// #endregion
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}
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/**
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* Specify the image format. Assume 'RGBA' if omitted.
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*/
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export type ImageFormat = 'RGB'|'RGBA'|'BGR'|'RBG';
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/**
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* Describes Tensor configuration to an image data.
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*/
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export interface TensorToImageDataOptions {
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/**
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* Describes Tensor channels order.
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*/
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format?: ImageFormat;
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/**
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* Tensor channel layout - default is 'NHWC'
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*/
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tensorLayout?: 'NHWC'|'NCHW';
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/**
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* Describes Tensor Height - can be accessed via tensor dimensions as well
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*/
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height?: number;
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/**
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* Describes Tensor Width - can be accessed via tensor dimensions as well
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*/
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width?: number;
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/**
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* Describes normalization parameters to ImageData conversion from tensor - default values - Bias: 0, Mean: 255
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*/
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norm?: {
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bias?: number; // Todo add support - |[number,number,number]|[number,number,number,number];
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mean?: number; // Todo add support - |[number,number,number]|[number,number,number,number];
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};
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}
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/**
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* Describes Tensor and Image configuration to an image data.
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*/
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export interface TensorFromImageOptions {
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/**
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* Describes image data format - will be used only in the case of ImageBitMap
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*/
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bitmapFormat?: ImageFormat;
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/**
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* Describes Tensor channels order - can differ from original image
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*/
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tensorFormat?: ImageFormat;
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/**
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* Tensor data type - default is 'float32'
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*/
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dataType?: 'float32'|'uint8';
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/**
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* Tensor channel layout - default is 'NHWC'
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*/
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tensorLayout?: 'NHWC'|'NCHW';
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/**
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* Describes Image Height - Required only in the case of ImageBitMap
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*/
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height?: number;
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/**
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* Describes Image Width - Required only in the case of ImageBitMap
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*/
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width?: number;
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/**
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* Describes resized height - can be accessed via tensor dimensions as well
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*/
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resizedHeight?: number;
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/**
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* Describes resized width - can be accessed via tensor dimensions as well
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*/
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resizedWidth?: number;
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/**
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* Describes normalization parameters to tensor conversion from image data - default values - Bias: 0, Mean: 255
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*/
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norm?: {
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bias?: number; // Todo add support - |[number,number,number]|[number,number,number,number];
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mean?: number; // Todo add support - |[number,number,number]|[number,number,number,number];
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};
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}
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export interface TensorFactory {
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/**
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* create a tensor from image object - HTMLImageElement, ImageData, ImageBitmap, URL
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*
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* @param imageData - {ImageData} - composed of: Uint8ClampedArray, width. height - uses known pixel format RGBA
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* @param options - Optional - Interface describing input image & output tensor -
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* Input Defaults: RGBA, 3 channels, 0-255, NHWC - Output Defaults: same as input parameters
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* @returns A promise that resolves to a tensor object
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*/
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fromImage(imageData: ImageData, options?: TensorFromImageOptions): Promise<Tensor>;
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/**
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* create a tensor from image object - HTMLImageElement, ImageData, ImageBitmap, URL
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*
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* @param imageElement - {HTMLImageElement} - since the data is stored as ImageData no need for format parameter
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* @param options - Optional - Interface describing input image & output tensor -
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* Input Defaults: RGBA, 3 channels, 0-255, NHWC - Output Defaults: same as input parameters
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* @returns A promise that resolves to a tensor object
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*/
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fromImage(imageElement: HTMLImageElement, options?: TensorFromImageOptions): Promise<Tensor>;
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/**
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* create a tensor from image object - HTMLImageElement, ImageData, ImageBitmap, URL
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*
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* @param url - {string} - Assuming the string is a URL to an image
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* @param options - Optional - Interface describing input image & output tensor -
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* Input Defaults: RGBA, 3 channels, 0-255, NHWC - Output Defaults: same as input parameters
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* @returns A promise that resolves to a tensor object
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*/
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fromImage(url: string, options?: TensorFromImageOptions): Promise<Tensor>;
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/**
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* create a tensor from image object - HTMLImageElement, ImageData, ImageBitmap, URL
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*
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* @param bitMap - {ImageBitmap} - since the data is stored as ImageData no need for format parameter
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* @param options - NOT Optional - Interface describing input image & output tensor -
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* Output Defaults: same as input parameters
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* @returns A promise that resolves to a tensor object
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*/
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fromImage(bitmap: ImageBitmap, options: TensorFromImageOptions): Promise<Tensor>;
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}
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// eslint-disable-next-line @typescript-eslint/naming-convention
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export const Tensor = TensorImpl as TensorConstructor;
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