tensorflow全链接层

1 dense
logits = tf.layers.dense(sent_feature,
                         clf_params["class_num"],
                         name="softmax")

2 matmul和bias

hidden_size = output_layer.shape[-1].value

output_weights = tf.get_variable(
    "output_weights", [num_labels, hidden_size],
    initializer=tf.truncated_normal_initializer(stddev=0.02), trainable=False)

output_bias = tf.get_variable(
    "output_bias", [num_labels], initializer=tf.zeros_initializer())

with tf.variable_scope("loss"):
  if is_training:
    # I.e., 0.1 dropout
    output_layer = tf.nn.dropout(output_layer, keep_prob=0.9)

  logits = tf.matmul(output_layer, output_weights, transpose_b=True)
  logits = tf.nn.bias_add(logits, output_bias)
  probabilities = tf.nn.softmax(logits, axis=-1)
  log_probs = tf.nn.log_softmax(logits, axis=-1)