playground.ipynb of OWL-ViT starts having dependency and import error on Google Colab since Nov. 15
XiangY-Q opened this issue · comments
I was able to run the playground demo as late as last Friday, although at the time, there was also dependency conflicts as I run first code block to install libraries (as shown below)
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
lida 0.0.10 requires fastapi, which is not installed.
lida 0.0.10 requires kaleido, which is not installed.
lida 0.0.10 requires python-multipart, which is not installed.
lida 0.0.10 requires uvicorn, which is not installed.
Starting as early as this morning, the playground demo script would fail to import owl_vit models at this line
from scenic.projects.owl_vit import models
due to following error
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
[<ipython-input-2-732db45ee9f0>](https://x9qogj82r87-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20231114-060201_RC00_582258937#) in <cell line: 10>()
8 import numpy as np
9 from scenic.projects.owl_vit import configs
---> 10 from scenic.projects.owl_vit import models
11
12 from scenic.projects.owl_vit.notebooks import inference
14 frames
[/content/scenic/projects/owl_vit/models.py](https://x9qogj82r87-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20231114-060201_RC00_582258937#) in <module>
9 import jax.numpy as jnp
10 import ml_collections
---> 11 from scenic.projects.owl_vit import layers
12 from scenic.projects.owl_vit import matching_base_models
13 from scenic.projects.owl_vit import utils
[/content/scenic/projects/owl_vit/layers.py](https://x9qogj82r87-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20231114-060201_RC00_582258937#) in <module>
15 import numpy as np
16 from scenic.model_lib.base_models import box_utils
---> 17 from scenic.projects.owl_vit import utils
18 from scenic.projects.owl_vit.clip import layers as clip_layers
19 from scenic.projects.owl_vit.clip import model as clip_model
[/content/scenic/projects/owl_vit/utils.py](https://x9qogj82r87-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20231114-060201_RC00_582258937#) in <module>
8 import jax.numpy as jnp
9 import numpy as np
---> 10 from scenic.train_lib import train_utils
11 import scipy
12
[/content/scenic/train_lib/train_utils.py](https://x9qogj82r87-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20231114-060201_RC00_582258937#) in <module>
34 import ml_collections
35 import numpy as np
---> 36 import optax
37 from scenic.common_lib import debug_utils
38 from scenic.dataset_lib import dataset_utils
[/usr/local/lib/python3.10/dist-packages/optax/__init__.py](https://x9qogj82r87-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20231114-060201_RC00_582258937#) in <module>
15 """Optax: composable gradient processing and optimization, in JAX."""
16
---> 17 from optax import contrib
18 from optax import losses
19 from optax import monte_carlo
[/usr/local/lib/python3.10/dist-packages/optax/contrib/__init__.py](https://x9qogj82r87-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20231114-060201_RC00_582258937#) in <module>
19 from optax.contrib.complex_valued import split_real_and_imaginary
20 from optax.contrib.complex_valued import SplitRealAndImaginaryState
---> 21 from optax.contrib.mechanic import MechanicState
22 from optax.contrib.mechanic import mechanize
23 from optax.contrib.privacy import differentially_private_aggregate
[/usr/local/lib/python3.10/dist-packages/optax/contrib/mechanic.py](https://x9qogj82r87-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20231114-060201_RC00_582258937#) in <module>
36 import jax.numpy as jnp
37 from optax._src import base
---> 38 from optax._src import utils
39
40
[/usr/local/lib/python3.10/dist-packages/optax/_src/utils.py](https://x9qogj82r87-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20231114-060201_RC00_582258937#) in <module>
20 import jax
21 import jax.numpy as jnp
---> 22 import jax.scipy.stats.norm as multivariate_normal
23
24 from optax._src import linear_algebra
[/usr/local/lib/python3.10/dist-packages/jax/scipy/stats/__init__.py](https://x9qogj82r87-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20231114-060201_RC00_582258937#) in <module>
16 # See PEP 484 & https://github.com/google/jax/issues/7570
17
---> 18 from jax.scipy.stats import bernoulli as bernoulli
19 from jax.scipy.stats import beta as beta
20 from jax.scipy.stats import binom as binom
[/usr/local/lib/python3.10/dist-packages/jax/scipy/stats/bernoulli.py](https://x9qogj82r87-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20231114-060201_RC00_582258937#) in <module>
16 # See PEP 484 & https://github.com/google/jax/issues/7570
17
---> 18 from jax._src.scipy.stats.bernoulli import (
19 logpmf as logpmf,
20 pmf as pmf,
[/usr/local/lib/python3.10/dist-packages/jax/_src/scipy/stats/bernoulli.py](https://x9qogj82r87-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20231114-060201_RC00_582258937#) in <module>
14
15
---> 16 import scipy.stats as osp_stats
17
18 from jax import lax
[/usr/local/lib/python3.10/dist-packages/scipy/stats/__init__.py](https://x9qogj82r87-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20231114-060201_RC00_582258937#) in <module>
606 from ._warnings_errors import (ConstantInputWarning, NearConstantInputWarning,
607 DegenerateDataWarning, FitError)
--> 608 from ._stats_py import *
609 from ._variation import variation
610 from .distributions import *
[/usr/local/lib/python3.10/dist-packages/scipy/stats/_stats_py.py](https://x9qogj82r87-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20231114-060201_RC00_582258937#) in <module>
35 from numpy import array, asarray, ma
36 from numpy.lib import NumpyVersion
---> 37 from numpy.testing import suppress_warnings
38
39 from scipy.spatial.distance import cdist
[/usr/local/lib/python3.10/dist-packages/numpy/testing/__init__.py](https://x9qogj82r87-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20231114-060201_RC00_582258937#) in <module>
9
10 from . import _private
---> 11 from ._private.utils import *
12 from ._private.utils import (_assert_valid_refcount, _gen_alignment_data)
13 from ._private import extbuild
[/usr/local/lib/python3.10/dist-packages/numpy/testing/_private/utils.py](https://x9qogj82r87-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20231114-060201_RC00_582258937#) in <module>
55 IS_PYSTON = hasattr(sys, "pyston_version_info")
56 HAS_REFCOUNT = getattr(sys, 'getrefcount', None) is not None and not IS_PYSTON
---> 57 HAS_LAPACK64 = numpy.linalg._umath_linalg._ilp64
58
59 _OLD_PROMOTION = lambda: np._get_promotion_state() == 'legacy'
AttributeError: module 'numpy.linalg._umath_linalg' has no attribute '_ilp64'
It appears that the imported numpyhas version 1.23.5 (numpy.__version__ is 1.23.5), although the installed version shown by pip is 1.26.2 (shown by !python -m pip show numpy)
The running instance was T4GPU Python 3 Google Compute Engine backend (GPU)
Found that numpy 1.24.1 works.