tinygrad/dist/index.d.cts

A JavaScript/TypeScript autograd engine with operator overloading, inspired by micrograd

declare namespace engine_d_exports {
  export { Value };
}
/**
 * Stores a single scalar value and its gradient for automatic differentiation
 */
declare class Value {
  #private;
  data: number;
  _op: string;
  grad: number;
  constructor(data: number, children?: Value[] | Set<Value>, _op?: string);
  add(other: Value | number): Value;
  mul(other: Value | number): Value;
  pow(other: number): Value;
  neg(): Value;
  sub(other: Value | number): Value;
  div(other: Value | number): Value;
  relu(): Value;
  backward(): void;
  toString(): string;
}
declare namespace nn_d_exports {
  export { Layer, MLP, Neuron };
}
declare abstract class Module {
  zeroGrad(): void;
  abstract parameters(): Value[];
}
declare class Neuron extends Module {
  w: Value[];
  b: Value;
  nonlin: boolean;
  constructor(nin: number, nonlin?: boolean);
  call(x: Value[]): Value;
  parameters(): Value[];
  toString(): string;
}
declare class Layer extends Module {
  neurons: Neuron[];
  constructor(nin: number, nout: number, nonlin?: boolean);
  call(x: Value[]): Value | Value[];
  parameters(): Value[];
  toString(): string;
}
declare class MLP extends Module {
  layers: Layer[];
  constructor(nin: number, nouts: number[]);
  call(x: Value[]): Value | Value[];
  parameters(): Value[];
  toString(): string;
}
//#endregion
export { engine_d_exports as engine, nn_d_exports as nn };
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