code: def attn(
      x,
      scope,
      n_state,
      n_head,
      resid_pdrop,
      attn_pdrop,
      train=False,
      scale=False,
      mask=True,
      explain=False,
      lengths=None,
  ):
      assert n_state % n_head == 0
      with tf.compat.v1.variable_scope(scope):
          q, k, v = multihead_qkv(x, n_state, n_head, train, explain)
          w = attn_weights(
              q,
              k,
              v,
              scale=scale,
              mask=mask,
              explain=explain,
              lengths=lengths,
          )
          w = dropout(w, attn_pdrop, train)
          a = tf.matmul(w, v)
          a = merge_heads(a)
          a = conv1d(a, "c_proj", n_state, 1, train=train)
          a = dropout(a, resid_pdrop, train)
          return a
  
imports: import functools
  import numpy
  import tensorflow
  from finetune.optimizers.recompute_grads import recompute_grad
  from finetune.util.shapes import shape_list, lengths_from_eos_idx
  from finetune.nn.activations import act_fns
  from finetune.nn.nn_utils import dropout, norm
label_desc: Use image node_id 11 for calling a global function with example usage: attn(x, scope, n_state, n_head, resid_pdrop, attn_pdrop, train, scale, mask, explain, lengths) and returns: a