Python transformer_supervised_attentionの例

コード例 #1

ファイル: transformer_test.py プロジェクト: sid7954/T2T-Transformer

 def testTransformerWithEncoderDecoderAttentionLoss(self):
   model, features = get_model(
       transformer.transformer_supervised_attention())
   expected_attention_weights = np.random.random_sample(
       size=(BATCH_SIZE, TARGET_LENGTH, INPUT_LENGTH))
   features["expected_attentions"] = tf.constant(
       expected_attention_weights, dtype=tf.float32)
   _, extra_loss = model(features)
   with self.test_session() as session:
     session.run(tf.global_variables_initializer())
     res = session.run(extra_loss["attention_loss"])
   self.assertEqual(res.shape, ())

コード例 #2

ファイル: transformer_test.py プロジェクト: qixiuai/tensor2tensor

 def testTransformerWithEncoderDecoderAttentionLoss(self):
   model, features = get_model(
       transformer.transformer_supervised_attention())
   expected_attention_weights = np.random.random_sample(
       size=(BATCH_SIZE, TARGET_LENGTH, INPUT_LENGTH))
   features["expected_attentions"] = tf.constant(
       expected_attention_weights, dtype=tf.float32)
   _, extra_loss = model(features)
   with self.test_session() as session:
     session.run(tf.global_variables_initializer())
     res = session.run(extra_loss["attention_loss"])
   self.assertEqual(res.shape, ())