Bump libdeeplake version. #12227
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failed
Apr 26, 2024 in 0s
1608 tests run, 481 passed, 1125 skipped, 2 failed.
Annotations
Check failure on line 948 in deeplake/enterprise/test_pytorch.py
github-actions / JUnit Test Report
test_pytorch.test_pytorch_data_decode
UnicodeDecodeError: 'utf-8' codec can't decode byte 0xb1 in position 3: invalid start byte
Raw output
local_auth_ds = Dataset(path='./hub_pytest/test_pytorch/test_pytorch_data_decode', tensors=['generic', 'text', 'json', 'list', 'class_label', 'image'])
cat_path = '/home/runner/work/deeplake/deeplake/deeplake/tests/dummy_data/images/cat.jpeg'
@requires_libdeeplake
@requires_torch
@pytest.mark.flaky
@pytest.mark.slow
def test_pytorch_data_decode(local_auth_ds, cat_path):
with local_auth_ds as ds:
ds.create_tensor("generic")
for i in range(10):
ds.generic.append(i)
ds.create_tensor("text", htype="text")
for i in range(10):
ds.text.append(f"hello {i}")
ds.create_tensor("json", htype="json")
for i in range(10):
ds.json.append({"x": i})
ds.create_tensor("list", htype="list")
for i in range(10):
ds.list.append([i, i + 1])
ds.create_tensor("class_label", htype="class_label")
animals = [
"cat",
"dog",
"bird",
"fish",
"horse",
"cow",
"pig",
"sheep",
"goat",
"chicken",
]
ds.class_label.extend(animals)
ds.create_tensor("image", htype="image", sample_compression="jpeg")
for i in range(10):
ds.image.append(deeplake.read(cat_path))
decode_method = {tensor: "data" for tensor in list(ds.tensors.keys())}
ptds = (
ds.dataloader()
.transform(identity)
.pytorch(decode_method=decode_method, collate_fn=identity_collate)
)
> for i, batch in enumerate(ptds):
deeplake/enterprise/test_pytorch.py:948:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
deeplake/enterprise/dataloader.py:881: in __next__
return next(self._iterator)
/opt/hostedtoolcache/Python/3.10.14/x64/lib/python3.10/site-packages/indra/pytorch/loader.py:156: in __next__
return next(self._iterator)
/opt/hostedtoolcache/Python/3.10.14/x64/lib/python3.10/site-packages/indra/pytorch/single_process_iterator.py:80: in __next__
return self.get_data()
/opt/hostedtoolcache/Python/3.10.14/x64/lib/python3.10/site-packages/indra/pytorch/single_process_iterator.py:117: in get_data
batch = self._next_data()
/opt/hostedtoolcache/Python/3.10.14/x64/lib/python3.10/site-packages/indra/pytorch/single_process_iterator.py:102: in _next_data
sample[tensor] = bytes_to_text(sample[tensor], "json")
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
buffer = b'\x12YT\xb1\xd2\x7f\x00\x00', htype = 'json'
def bytes_to_text(buffer, htype):
buffer = bytes(buffer)
if htype == "json":
arr = np.empty(1, dtype=object)
> arr[0] = json.loads(bytes.decode(buffer), cls=HubJsonDecoder)
E UnicodeDecodeError: 'utf-8' codec can't decode byte 0xb1 in position 3: invalid start byte
deeplake/core/serialize.py:481: UnicodeDecodeError
Check failure on line 340 in deeplake/enterprise/test_tensorflow.py
github-actions / JUnit Test Report
test_tensorflow.test_groups
AssertionError:
Arrays are not equal
Mismatched elements: 2423881 / 2430000 (99.7%)
Max absolute difference: 128
Max relative difference: 127.
x: array([[[128, 127, 133],
[128, 127, 133],
[129, 128, 133],...
y: array([[[40, 41, 45],
[38, 39, 43],
[36, 37, 41],...
Raw output
local_auth_ds = Dataset(path='./hub_pytest/test_tensorflow/test_groups', tensors=['images/jpegs/cats', 'images/pngs/flowers'])
compressed_image_paths = {'bmp': ['/home/runner/work/deeplake/deeplake/deeplake/tests/dummy_data/images/car.bmp'], 'dib': ['/home/runner/work/d...ata/images/hopper.fli'], 'gif': ['/home/runner/work/deeplake/deeplake/deeplake/tests/dummy_data/images/boat.gif'], ...}
@requires_tensorflow
@requires_libdeeplake
@pytest.mark.slow
@pytest.mark.flaky
def test_groups(local_auth_ds, compressed_image_paths):
img1 = deeplake.read(compressed_image_paths["jpeg"][0])
img2 = deeplake.read(compressed_image_paths["png"][0])
with local_auth_ds as ds:
ds.create_tensor("images/jpegs/cats", htype="image", sample_compression="jpeg")
ds.create_tensor("images/pngs/flowers", htype="image", sample_compression="png")
for _ in range(10):
ds.images.jpegs.cats.append(img1)
ds.images.pngs.flowers.append(img2)
another_ds = deeplake.dataset(
ds.path,
token=ds.token,
)
dl = another_ds.dataloader().tensorflow(return_index=False)
for i, (cat, flower) in enumerate(dl):
assert cat[0].shape == another_ds.images.jpegs.cats[i].numpy().shape
assert flower[0].shape == another_ds.images.pngs.flowers[i].numpy().shape
dl = another_ds.images.dataloader().tensorflow(return_index=False)
for sample in dl:
cat = sample["images/jpegs/cats"]
flower = sample["images/pngs/flowers"]
> np.testing.assert_array_equal(cat[0], img1.array)
deeplake/enterprise/test_tensorflow.py:340:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
args = (<built-in function eq>, <tf.Tensor: shape=(900, 900, 3), dtype=uint8, numpy=
array([[[128, 127, 133],
[128, 1...],
[87, 71, 58],
...,
[19, 20, 22],
[19, 20, 22],
[19, 20, 22]]], dtype=uint8))
kwds = {'err_msg': '', 'header': 'Arrays are not equal', 'strict': False, 'verbose': True}
@wraps(func)
def inner(*args, **kwds):
with self._recreate_cm():
> return func(*args, **kwds)
E AssertionError:
E Arrays are not equal
E
E Mismatched elements: 2423881 / 2430000 (99.7%)
E Max absolute difference: 128
E Max relative difference: 127.
E x: array([[[128, 127, 133],
E [128, 127, 133],
E [129, 128, 133],...
E y: array([[[40, 41, 45],
E [38, 39, 43],
E [36, 37, 41],...
/opt/hostedtoolcache/Python/3.10.14/x64/lib/python3.10/contextlib.py:79: AssertionError
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