code: def fc_layer(input, num_input, num_output, seed=None):
      weights = tf.Variable(
          tf.truncated_normal(
              [num_input, num_output], stddev=0.05, seed=seed
          )
      )
      biases = tf.Variable(tf.constant(0.05, shape=[num_output]))
      layer = tf.matmul(input, weights) + biases
      layer = tf.nn.tanh(layer)
      return layer
  
imports: import tensorflow.compat.v1
label_desc: Use image node_id 3 for calling a global function with example usage: fc_layer(input, num_input, num_output, seed) and returns: layer