code: def odeint(
      func,
      y0,
      t,
      *,
      rtol=1e-7,
      atol=1e-9,
      method=None,
      options=None,
      event_fn=None,
  ):
      """Integrate a system of ordinary differential equations.
  
      Solves the initial value problem for a non-stiff system of first order ODEs:
          ```
          dy/dt = func(t, y), y(t[0]) = y0
          ```
      where y is a Tensor or tuple of Tensors of any shape.
  
      Output dtypes and numerical precision are based on the dtypes of the inputs `y0`.
  
      Args:
          func: Function that maps a scalar Tensor `t` and a Tensor holding the state `y`
              into a Tensor of state derivatives with respect to time. Optionally, `y`
              can also be a tuple of Tensors.
          y0: N-D Tensor giving starting value of `y` at time point `t[0]`. Optionally, `y0`
              can also be a tuple of Tensors.
          t: 1-D Tensor holding a sequence of time points for which to solve for
              `y`, in either increasing or decreasing order. The first element of
              this sequence is taken to be the initial time point.
          rtol: optional float64 Tensor specifying an upper bound on relative error,
              per element of `y`.
          atol: optional float64 Tensor specifying an upper bound on absolute error,
              per element of `y`.
          method: optional string indicating the integration method to use.
          options: optional dict of configuring options for the indicated integration
              method. Can only be provided if a `method` is explicitly set.
          event_fn: Function that maps the state `y` to a Tensor. The solve terminates when
              event_fn evaluates to zero. If this is not None, all but the first elements of
              `t` are ignored.
  
      Returns:
          y: Tensor, where the first dimension corresponds to different
              time points. Contains the solved value of y for each desired time point in
              `t`, with the initial value `y0` being the first element along the first
              dimension.
  
      Raises:
          ValueError: if an invalid `method` is provided.
      """
  
      (
          shapes,
          func,
          y0,
          t,
          rtol,
          atol,
          method,
          options,
          event_fn,
          t_is_reversed,
      ) = _check_inputs(
          func, y0, t, rtol, atol, method, options, event_fn, SOLVERS
      )
  
      solver = SOLVERS[method](
          func=func, y0=y0, rtol=rtol, atol=atol, **options
      )
  
      if event_fn is None:
          solution = solver.integrate(t)
      else:
          event_t, solution = solver.integrate_until_event(
              t[0], event_fn
          )
          event_t = event_t.to(t)
          if t_is_reversed:
              event_t = -event_t
  
      if shapes is not None:
          solution = _flat_to_shape(solution, (len(t),), shapes)
  
      if event_fn is None:
          return solution
      else:
          return event_t, solution
  
file_path: torchdiffeq/torchdiffeq/_impl/odeint.py
imports: import torch
  from torch.autograd.functional import vjp
  from .dopri5 import Dopri5Solver
  from .bosh3 import Bosh3Solver
  from .adaptive_heun import AdaptiveHeunSolver
  from .fehlberg2 import Fehlberg2
  from .fixed_grid import Euler, Midpoint, Heun3, RK4
  from .fixed_adams import AdamsBashforth, AdamsBashforthMoulton
  from .dopri8 import Dopri8Solver
  from .scipy_wrapper import ScipyWrapperODESolver
  from .misc import _check_inputs, _flat_to_shape
  from .interp import _interp_evaluate
label_desc: Use image node_id 1 for calling a global function with example usage: odeint(func, y0, t) and returns: solution, event_t,  solution