code: def lstm_fwd(
      x: Array,
      h_0: Array,
      c_0: Array,
      w: Array,
      seq_lengths: Array,
      input_size: int,
      hidden_size: int,
      num_layers: int,
      dropout: float,
      bidirectional: bool,
      precision: lax.PrecisionLike,
  ):
      if seq_lengths.dtype != jnp.dtype("int32"):
          raise NotImplementedError("`seq_lengths` can only be int32.")
      cudnn_allow_tf32 = _lstm_cudnn_allow_tf32(precision)
      y, h_n, c_n, reserve_space = rnn_fwd_p.bind(
          x,
          h_0,
          c_0,
          w,
          seq_lengths,
          input_size=input_size,
          hidden_size=hidden_size,
          num_layers=num_layers,
          dropout=dropout,
          bidirectional=bidirectional,
          cudnn_allow_tf32=cudnn_allow_tf32,
      )
      return (y, h_n, c_n), (
          x,
          h_0,
          c_0,
          w,
          seq_lengths,
          y,
          reserve_space,
      )
  
imports: from functools import partial
  import math
  from typing import Any
  import jax
  import numpy
  from jax._src import core
  from jax.interpreters import mlir
  from jax.interpreters import xla
  from jax._src.custom_derivatives import custom_vjp
  from jax._src.typing import Array, Shape
  from jax._src.lax import lax
  import jax.numpy
label_desc: Use image node_id 15 for calling a global function with example usage: lstm_fwd(x, h_0, c_0, w, seq_lengths, input_size, hidden_size, num_layers, dropout, bidirectional, precision) and returns: y,  h_n,  c_n,  x,  h_0,  c_0,  w,  seq_lengths,  y,  reserve_space