code: def _conv_general_vjp_lhs_padding(
      in_shape,
      window_dimensions,
      window_strides,
      out_shape,
      padding,
      lhs_dilation,
      rhs_dilation,
  ) -> list[tuple[int, int]]:
      lhs_dilated_shape = lax._dilate_shape(in_shape, lhs_dilation)
      rhs_dilated_shape = lax._dilate_shape(
          window_dimensions, rhs_dilation
      )
      out_dilated_shape = lax._dilate_shape(out_shape, window_strides)
      pad_before = (
          np.subtract(rhs_dilated_shape, [lo for lo, _ in padding]) - 1
      )
      pad_after = (
          np.add(lhs_dilated_shape, rhs_dilated_shape)
          - 1
          - out_dilated_shape
          - pad_before
      )
      return util.safe_zip(pad_before, pad_after)
  
imports: from __future__ import annotations
  from collections.abc import Sequence
  from functools import partial
  import operator
  from typing import NamedTuple, Union
  import numpy
  from jax._src import core
  from jax._src import dtypes
  from jax._src import util
  from jax._src.interpreters import ad
  from jax._src.interpreters import batching
  from jax._src.interpreters import mlir
  from jax._src.lax import lax
  from jax._src.lib.mlir.dialects import hlo
  from jax._src.typing import Array, DTypeLike
label_desc: Use image node_id 21 for calling a global function with example usage: _conv_general_vjp_lhs_padding(in_shape, window_dimensions, window_strides, out_shape, padding, lhs_dilation, rhs_dilation) and returns: util