code: def _tf_blur(x, w=3):
      depth = x.shape[-1]
      k = np.zeros([w, w, depth, depth])
      for ch in range(depth):
          k_ch = k[:, :, ch, ch]
          k_ch[:, :] = 0.5
          k_ch[1:-1, 1:-1] = 1.0
  
      conv_k = lambda t: tf.nn.conv2d(t, k, [1, 1, 1, 1], "SAME")
      return conv_k(x) / conv_k(tf.ones_like(x))
  
imports: from __future__ import absolute_import, division, print_function
  from decorator import decorator
  import numpy
  import tensorflow
  from lucid.optvis.objectives_util import _dot, _dot_cossim, _extract_act_pos, _make_arg_str, _T_force_NHWC, _T_handle_batch
label_desc: Use image node_id 12 for calling a global function with example usage: _tf_blur(x, w) and returns: unknown