Fix an error related to collation and RNN #129
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Recurrent policies expect data collated in a tuple.
muupan
requested review from
muupan
and removed request for
prabhatnagarajan
muupan
requested changes
Feb 17, 2021
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Can you also remove @pytest.mark.skip at https://github.com/tarokiritani/pfrl/blob/284ed1f43b32654a2ec1569b16a0f6b9acbd5e79/tests/utils_tests/test_batch_states.py#L10 so that the test is run inside CI?
Omitted skipping.
The input feature type is checked better way. Co-authored-by: Yasuhiro Fujita <muupan@gmail.com>
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/test |
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Successfully created a job for commit 671b6d6: |
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It seems the test fails with gpu. Can you apply this patch so it will work with both cpu and gpu? Looks good except this failure. diff --git a/tests/utils_tests/test_batch_states.py b/tests/utils_tests/test_batch_states.py
index ba4391b3..cdfedcd8 100644
--- a/tests/utils_tests/test_batch_states.py
+++ b/tests/utils_tests/test_batch_states.py
@@ -27,7 +27,7 @@ class TestBatchStates(unittest.TestCase):
self.assertIsInstance(batch, tuple)
batch_a, batch_b, batch_c = batch
np.testing.assert_allclose(
- batch_a,
+ batch_a.cpu(),
np.asarray(
[
[[0, 2], [4, 6]],
@@ -35,9 +35,9 @@ class TestBatchStates(unittest.TestCase):
]
),
)
- np.testing.assert_allclose(batch_b, np.asarray([0, 1]))
+ np.testing.assert_allclose(batch_b.cpu(), np.asarray([0, 1]))
np.testing.assert_allclose(
- batch_c,
+ batch_c.cpu(),
np.asarray(
[
[0], |
test_gpu() now correctly uses a GPU.
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/test |
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Successfully created a job for commit b5f6907: |
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Recurrent policies expect data collated in a tuple.