From 0f334529534cc23347abc0465d7bfc85e3f06e23 Mon Sep 17 00:00:00 2001 From: Peter Hawkins Date: Wed, 21 Dec 2022 06:41:52 -0800 Subject: [PATCH] [NumPy] Remove references to deprecated NumPy type aliases. This change replaces references to a number of deprecated NumPy type aliases (np.bool, np.int, np.float, np.complex, np.object, np.str) with their recommended replacement (bool, int, float, complex, object, str). NumPy 1.24 drops the deprecated aliases, so we must remove uses before updating NumPy. PiperOrigin-RevId: 496908874 Change-Id: I7ee2af3bc548c4bbe6069defc3f3d143ba7eb88a --- tf_agents/agents/ppo/ppo_policy_test.py | 2 +- .../bandits/environments/dataset_utilities.py | 2 +- .../environments/ranking_environment_test.py | 4 ++-- tf_agents/environments/gym_wrapper_test.py | 24 +++++++++---------- tf_agents/typing/types.py | 2 +- 5 files changed, 17 insertions(+), 17 deletions(-) diff --git a/tf_agents/agents/ppo/ppo_policy_test.py b/tf_agents/agents/ppo/ppo_policy_test.py index 51f3311df..af4512d11 100644 --- a/tf_agents/agents/ppo/ppo_policy_test.py +++ b/tf_agents/agents/ppo/ppo_policy_test.py @@ -326,7 +326,7 @@ def splitter_fn(observation_and_mask): clip=False) # Take a step. - mask = np.array([True, False, True, False, True], dtype=np.bool) + mask = np.array([True, False, True, False, True], dtype=bool) self.assertLen(mask, num_categories) time_step = ts.TimeStep( step_type=tf.constant([1], dtype=tf.int32), diff --git a/tf_agents/bandits/environments/dataset_utilities.py b/tf_agents/bandits/environments/dataset_utilities.py index d674021ac..9be201754 100644 --- a/tf_agents/bandits/environments/dataset_utilities.py +++ b/tf_agents/bandits/environments/dataset_utilities.py @@ -141,7 +141,7 @@ def mushroom_reward_distribution(r_noeat, r_eat_safe, r_eat_poison_bad, def convert_covertype_dataset(file_path, buffer_size=40000): with tf.io.gfile.GFile(file_path, 'r') as infile: - data_array = np.genfromtxt(infile, dtype=np.int, delimiter=',') + data_array = np.genfromtxt(infile, dtype=int, delimiter=',') contexts = data_array[:, :-1] context_tensor = tf.cast(contexts, tf.float32) labels = data_array[:, -1] - 1 # Classes are from [1, 7]. diff --git a/tf_agents/bandits/environments/ranking_environment_test.py b/tf_agents/bandits/environments/ranking_environment_test.py index 725b9b089..edf940b23 100644 --- a/tf_agents/bandits/environments/ranking_environment_test.py +++ b/tf_agents/bandits/environments/ranking_environment_test.py @@ -76,7 +76,7 @@ def _item_sampling_fn(): return np.random.randint(-2, 3, [item_dim]) scores_weight_matrix = (np.reshape( - np.arange(global_dim * item_dim, dtype=np.float), + np.arange(global_dim * item_dim, dtype=float), newshape=[item_dim, global_dim]) - 10) / 5 env = ranking_environment.RankingPyEnvironment( @@ -127,7 +127,7 @@ def _global_sampling_fn(): def _item_sampling_fn(): return np.random.randint(-2, 3, [item_dim]) scores_weight_matrix = (np.reshape( - np.arange(global_dim * item_dim, dtype=np.float), + np.arange(global_dim * item_dim, dtype=float), newshape=[item_dim, global_dim]) - 10) / 5 env = ranking_environment.RankingPyEnvironment( _global_sampling_fn, diff --git a/tf_agents/environments/gym_wrapper_test.py b/tf_agents/environments/gym_wrapper_test.py index 57c0f0b26..822c4636d 100644 --- a/tf_agents/environments/gym_wrapper_test.py +++ b/tf_agents/environments/gym_wrapper_test.py @@ -46,9 +46,9 @@ def test_spec_from_gym_space_multi_discrete(self): self.assertEqual((4,), spec.shape) self.assertEqual(np.int32, spec.dtype) - np.testing.assert_array_equal(np.array([0], dtype=np.int), spec.minimum) + np.testing.assert_array_equal(np.array([0], dtype=int), spec.minimum) np.testing.assert_array_equal( - np.array([0, 1, 2, 3], dtype=np.int), spec.maximum) + np.array([0, 1, 2, 3], dtype=int), spec.maximum) def test_spec_from_gym_space_multi_binary(self): multi_binary_space = gym.spaces.MultiBinary(4) @@ -56,8 +56,8 @@ def test_spec_from_gym_space_multi_binary(self): self.assertEqual((4,), spec.shape) self.assertEqual(np.int32, spec.dtype) - np.testing.assert_array_equal(np.array([0], dtype=np.int), spec.minimum) - np.testing.assert_array_equal(np.array([1], dtype=np.int), spec.maximum) + np.testing.assert_array_equal(np.array([0], dtype=int), spec.minimum) + np.testing.assert_array_equal(np.array([1], dtype=int), spec.maximum) def test_spec_from_gym_space_multi_binary_2d(self): multi_binary_space = gym.spaces.MultiBinary((8, 8)) @@ -65,8 +65,8 @@ def test_spec_from_gym_space_multi_binary_2d(self): self.assertEqual((8, 8), spec.shape) self.assertEqual(np.int32, spec.dtype) - np.testing.assert_array_equal(np.array([0], dtype=np.int), spec.minimum) - np.testing.assert_array_equal(np.array([1], dtype=np.int), spec.maximum) + np.testing.assert_array_equal(np.array([0], dtype=int), spec.minimum) + np.testing.assert_array_equal(np.array([1], dtype=int), spec.maximum) def test_spec_from_gym_space_box_scalars(self): for dtype in (np.float32, np.float64): @@ -84,8 +84,8 @@ def test_spec_from_gym_space_box_scalars_simplify_bounds(self): self.assertEqual((3, 4), spec.shape) self.assertEqual(np.float32, spec.dtype) - np.testing.assert_array_equal(np.array([-1], dtype=np.int), spec.minimum) - np.testing.assert_array_equal(np.array([1], dtype=np.int), spec.maximum) + np.testing.assert_array_equal(np.array([-1], dtype=int), spec.minimum) + np.testing.assert_array_equal(np.array([1], dtype=int), spec.maximum) def test_spec_from_gym_space_when_simplify_box_bounds_false(self): # testing on gym.spaces.Dict which makes recursive calls to @@ -101,13 +101,13 @@ def test_spec_from_gym_space_when_simplify_box_bounds_false(self): self.assertEqual(np.float32, spec['box2'].dtype) self.assertEqual('box1', spec['box1'].name) self.assertEqual('box2', spec['box2'].name) - np.testing.assert_array_equal(np.array([-1, -1], dtype=np.int), + np.testing.assert_array_equal(np.array([-1, -1], dtype=int), spec['box1'].minimum) - np.testing.assert_array_equal(np.array([1, 1], dtype=np.int), + np.testing.assert_array_equal(np.array([1, 1], dtype=int), spec['box1'].maximum) - np.testing.assert_array_equal(np.array([-1, -1], dtype=np.int), + np.testing.assert_array_equal(np.array([-1, -1], dtype=int), spec['box2'].minimum) - np.testing.assert_array_equal(np.array([1, 1], dtype=np.int), + np.testing.assert_array_equal(np.array([1, 1], dtype=int), spec['box2'].maximum) def test_spec_from_gym_space_box_array(self): diff --git a/tf_agents/typing/types.py b/tf_agents/typing/types.py index bd296d7fc..6d8907d0b 100644 --- a/tf_agents/typing/types.py +++ b/tf_agents/typing/types.py @@ -78,7 +78,7 @@ NestedSpecTensorOrArray = Union[NestedSpec, NestedTensor, NestedArray] Int = Union[int, np.int16, np.int32, np.int64, Tensor, Array] -Bool = Union[bool, np.bool, Tensor, Array] +Bool = Union[bool, bool, Tensor, Array] Float = Union[float, np.float16, np.float32, np.float64, Tensor, Array] FloatOrReturningFloat = Union[Float, Callable[[], Float]]