level1_model.py 文件源码

def _project_features(self, features):
        with tf.variable_scope('level1/project_features'):
            # features_proj --> proj_ctx
            # todo: features_proj = tf.matmul(features_flat, w) + b

            w1_ = np.transpose(self.model_load['/core/context_proj1/weight'][:], (1, 0))
            b1_ = self.model_load['/core/context_proj1/bias'][:]
            w2_ = np.transpose(self.model_load['/core/context_proj2/weight'][:], (1, 0))
            b2_ = self.model_load['/core/context_proj2/bias'][:]

            w1 = tf.get_variable('w1', initializer=w1_)
            b1 = tf.get_variable('b1', initializer=b1_)
            w2 = tf.get_variable('w2', initializer=w2_)
            b2 = tf.get_variable('b2', initializer=b2_)

            features_flat = tf.reshape(features, [-1, self.D])
            features_proj1 = tf.nn.tanh(tf.matmul(features_flat, w1) + b1)
            features_proj = tf.matmul(features_proj1, w2) + b2
            features_proj = tf.reshape(features_proj, [-1, self.L, self.D])
            return features_proj