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Cleanup dataset UT: remove num_parallel_workers=1 in test_exception

This commit is contained in:
Cathy Wong 2020-05-22 09:28:17 -04:00
parent 46949fc327
commit 702005d403
2 changed files with 3 additions and 4 deletions
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6
tests/ut/python/dataset/test_datasets_sharding.py
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@ -35,9 +35,9 @@ def test_imagefolder_shardings(print_res=False):
assert (sharding_config(4, 0, 5, False, dict()) == [0, 0, 0, 1, 1]) # 5 rows
assert (sharding_config(4, 0, 12, False, dict()) == [0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3]) # 11 rows
assert (sharding_config(4, 3, None, False, dict()) == [0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3]) # 11 rows
assert (sharding_config(1, 0, 55, False, dict()) == [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3] ) # 44 rows
assert (sharding_config(2, 0, 55, False, dict()) == [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3] ) # 22 rows
assert (sharding_config(2, 1, 55, False, dict()) == [0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3] ) # 22 rows
assert (sharding_config(1, 0, 55, False, dict()) == [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3]) # 44 rows
assert (sharding_config(2, 0, 55, False, dict()) == [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3]) # 22 rows
assert (sharding_config(2, 1, 55, False, dict()) == [0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3]) # 22 rows
# total 22 in dataset rows because of class indexing which takes only 2 folders
assert (len(sharding_config(4, 0, None, True, {"class1": 111, "class2": 999})) == 6)
assert (len(sharding_config(4, 2, 3, True, {"class1": 111, "class2": 999})) == 3)

1
tests/ut/python/dataset/test_exceptions.py
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@ -27,7 +27,6 @@ def test_exception_01():
Test single exception with invalid input
"""
logger.info("test_exception_01")
ds.config.set_num_parallel_workers(1)
data = ds.TFRecordDataset(DATA_DIR, columns_list=["image"])
with pytest.raises(ValueError) as info:
data = data.map(input_columns=["image"], operations=vision.Resize(100, 100))