code: def linear_interpolate(tensor1, tensor2, coeffs):
      """Linearly interpolate between two tensors at coeff.
  
      Args:
        tensor1: 4-D Tensor, shape=(NHWC)
        tensor2: 4-D Tensor, shape=(NHWC)
        coeffs: list of floats.
      Returns:
        interp_latents: 5-D Tensor, with interp_latents[i] representing
                        interpolations at coeffs[i].
                        shape=(len(coeffs), NHWC)
      """
      interp_tensors = []
      for coeff in coeffs:
          interp_tensor = tensor1 + coeff * (tensor2 - tensor1)
          interp_tensors.append(interp_tensor)
      return tf.concat(interp_tensors, axis=0)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import functools
  import numpy
  import scipy
  from tensor2tensor.layers import common_layers
  from tensor2tensor.layers import common_video
  from tensor2tensor.utils import contrib
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
  import tensorflow_probability
label_desc: Use image node_id 1 for calling a global function with example usage: linear_interpolate(tensor1, tensor2, coeffs) and returns: tf