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torch.AutogradConfig

export interface AutogradConfig<Op extends OpName> {
  /**
   * The operation name.
   */
  readonly op: Op;

  /**
   * Optional dtype restriction.
   * If specified, this autograd only applies to the given dtype.
   * Use '*' for wildcard to match any dtype.
   * If omitted, applies to all dtypes.
   */
  readonly dtype?: AutogradDType;

  /**
   * Device restriction.
   * Use '*' for wildcard to match any device.
   * This is useful for composed backwards that use tensor operations
   * which auto-dispatch to the correct kernel.
   */
  readonly device: AutogradDevice;

  /**
   * Setup context during forward pass.
   * Called after forward computation to save tensors for backward.
   *
   * @param ctx - The gradient context
   * @param inputs - The input tensors
   * @param output - The output tensor
   * @param meta - Optional metadata from forward pass
   */
  setup_context?(
    ctx: GradContext<Op>,
    inputs: InputsFor<Op>,
    output: TensorLike,
    meta?: unknown
  ): void;

  /**
   * Compute gradients during backward pass.
   *
   * @param ctx - The gradient context with saved tensors
   * @param grad_output - Gradient of the loss with respect to output
   * @returns Gradients for each input
   */
  backward(ctx: GradContext<Op>, grad_output: TensorLike): GradientsFor<Op>;
}

Opextends OpName

readonlyop(Op): – The operation name.
readonlydtype(AutogradDType)optional: – Optional dtype restriction. If specified, this autograd only applies to the given dtype. Use '*' for wildcard to match any dtype. If omitted, applies to all dtypes.
readonlydevice(AutogradDevice): – Device restriction. Use '*' for wildcard to match any device. This is useful for composed backwards that use tensor operations which auto-dispatch to the correct kernel.
setup_context((ctx: GradContext<Op>, inputs: InputsFor<Op>, output: TensorLike, meta?: unknown) => void)optional: – Setup context during forward pass. Called after forward computation to save tensors for backward.
backward((ctx: GradContext<Op>, grad_output: TensorLike) => GradientsFor<Op>): – Compute gradients during backward pass.

Autograd configuration for an operation.

autograd_not_registered_error