code: def separable_conv(
      inputs,
      depthwise_kernel,
      pointwise_kernel,
      strides=1,
      padding="valid",
      data_format=None,
      dilation_rate=1,
  ):
      data_format = standardize_data_format(data_format)
      depthwise_conv_output = depthwise_conv(
          inputs,
          depthwise_kernel,
          strides,
          padding,
          data_format,
          dilation_rate,
      )
      return conv(
          depthwise_conv_output,
          pointwise_kernel,
          strides=1,
          padding="valid",
          data_format=data_format,
          dilation_rate=dilation_rate,
      )
  
imports: import jax
  import numpy
  from jax import lax
  from jax import numpy
  from keras.backend import standardize_data_format
  from keras.backend import standardize_dtype
  from keras.backend.common.backend_utils import compute_conv_transpose_padding_args_for_jax
  from keras.backend.config import epsilon
  from keras.backend.numpy.core import cast
  from keras.backend.numpy.core import convert_to_tensor
  from keras.backend.numpy.core import is_tensor
  from keras.utils.module_utils import scipy
label_desc: Use image node_id 24 for calling a global function with example usage: separable_conv(inputs, depthwise_kernel, pointwise_kernel, strides, padding, data_format, dilation_rate) and returns: conv