From a24ce89f0692e122260eb983912187ef76b51efd Mon Sep 17 00:00:00 2001 From: jessechancy Date: Tue, 12 Jul 2022 15:53:21 -0700 Subject: [PATCH 1/2] set global seed fix --- keras_nlp/utils/text_generation_test.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/keras_nlp/utils/text_generation_test.py b/keras_nlp/utils/text_generation_test.py index 1731fb4ef8..08fbc24474 100644 --- a/keras_nlp/utils/text_generation_test.py +++ b/keras_nlp/utils/text_generation_test.py @@ -348,7 +348,7 @@ def token_probability_fn(inputs): batch_size = 10 inputs = 3 * tf.ones([batch_size, 1], dtype=tf.int32) max_length = 3 - tf.random.set_seed(42) + tf.keras.utils.set_random_seed(42) outputs = random_search( token_probability_fn, inputs, max_length=max_length, seed=42 ) @@ -514,7 +514,7 @@ def token_probability_fn(inputs): batch_size = 10 inputs = 3 * tf.ones([batch_size, 1], dtype=tf.int32) max_length = 3 - tf.random.set_seed(42) + tf.keras.utils.set_random_seed(42) outputs = top_k_search( token_probability_fn, inputs, max_length=max_length, k=2, seed=42 ) @@ -696,7 +696,7 @@ def token_probability_fn(inputs): batch_size = 10 inputs = 3 * tf.ones([batch_size, 1], dtype=tf.int32) max_length = 3 - tf.random.set_seed(42) + tf.keras.utils.set_random_seed(42) outputs = top_p_search( token_probability_fn, inputs, max_length=max_length, p=0.91, seed=42 ) From 4c8f685b082d896df3d2a40e631c28bb053b82cf Mon Sep 17 00:00:00 2001 From: jessechancy Date: Tue, 12 Jul 2022 16:08:21 -0700 Subject: [PATCH 2/2] remove seeded generation --- keras_nlp/utils/text_generation_test.py | 53 ------------------------- 1 file changed, 53 deletions(-) diff --git a/keras_nlp/utils/text_generation_test.py b/keras_nlp/utils/text_generation_test.py index 08fbc24474..6030ce44fb 100644 --- a/keras_nlp/utils/text_generation_test.py +++ b/keras_nlp/utils/text_generation_test.py @@ -339,23 +339,6 @@ def test_generate_with_ragged_prompt(self): with self.assertRaises(ValueError): random_search(self.token_probability_fn, inputs, max_length=5) - def test_assert_seeded_generation_is_correct(self): - def token_probability_fn(inputs): - batch_size = inputs.shape[0] - prob = tf.constant([[0.01, 0.01, 0.08, 0.9]]) - return tf.repeat(prob, batch_size, axis=0) - - batch_size = 10 - inputs = 3 * tf.ones([batch_size, 1], dtype=tf.int32) - max_length = 3 - tf.keras.utils.set_random_seed(42) - outputs = random_search( - token_probability_fn, inputs, max_length=max_length, seed=42 - ) - # Random sampling result with seed 42. - seeded_result = 3 * np.ones(shape=[batch_size, max_length]) - self.assertAllEqual(outputs, seeded_result) - def test_assert_probability_distribution_generation_is_correct(self): def token_probability_fn(inputs): batch_size = inputs.shape[0] @@ -505,23 +488,6 @@ def test_generate_with_ragged_prompt(self): with self.assertRaises(ValueError): top_k_search(self.token_probability_fn, inputs, max_length=5, k=2) - def test_assert_seeded_generation_is_correct(self): - def token_probability_fn(inputs): - batch_size = inputs.shape[0] - prob = tf.constant([[0.01, 0.01, 0.08, 0.9]]) - return tf.repeat(prob, batch_size, axis=0) - - batch_size = 10 - inputs = 3 * tf.ones([batch_size, 1], dtype=tf.int32) - max_length = 3 - tf.keras.utils.set_random_seed(42) - outputs = top_k_search( - token_probability_fn, inputs, max_length=max_length, k=2, seed=42 - ) - # Top-k sampling result with seed 42. - seeded_result = 3 * np.ones(shape=[batch_size, max_length]) - self.assertAllEqual(outputs, seeded_result) - def test_assert_probability_distribution_generation_is_correct(self): def token_probability_fn(inputs): batch_size = inputs.shape[0] @@ -687,25 +653,6 @@ def test_generate_with_ragged_prompt(self): with self.assertRaises(ValueError): top_p_search(self.token_probability_fn, inputs, max_length=5, p=0.8) - def test_assert_seeded_generation_is_correct(self): - def token_probability_fn(inputs): - batch_size = inputs.shape[0] - prob = tf.constant([[0.01, 0.01, 0.08, 0.9]]) - return tf.repeat(prob, batch_size, axis=0) - - batch_size = 10 - inputs = 3 * tf.ones([batch_size, 1], dtype=tf.int32) - max_length = 3 - tf.keras.utils.set_random_seed(42) - outputs = top_p_search( - token_probability_fn, inputs, max_length=max_length, p=0.91, seed=42 - ) - # Top-p sampling result with seed 42. - seeded_result = 3 * np.ones(shape=[batch_size, max_length]) - seeded_result[3][1] = 2 - seeded_result[7][1] = 2 - self.assertAllEqual(outputs, seeded_result) - def test_assert_probability_distribution_generation_is_correct(self): def token_probability_fn(inputs): batch_size = inputs.shape[0]