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Update tensorflow-probability requirement from <0.20.0,>=0.8.0 to >=0.8.0,<0.21.0 #785
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Update tensorflow-probability requirement from <0.20.0,>=0.8.0 to >=0.8.0,<0.21.0 #785
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Updates the requirements on [tensorflow-probability](https://github.com/tensorflow/probability) to permit the latest version. - [Release notes](https://github.com/tensorflow/probability/releases) - [Commits](tensorflow/probability@0.8.0...v0.20.0) --- updated-dependencies: - dependency-name: tensorflow-probability dependency-type: direct:development ... Signed-off-by: dependabot[bot] <[email protected]>
Blocked because following occurs on Python 3.7:
|
FYI this will also require updates to the Stack-trace of error: 2023-05-23 10:09:49.031457: W tensorflow/tsl/framework/cpu_allocator_impl.cc:83] Allocation of 614400000 exceeds 10% of free system memory.
2023-05-23 10:09:49.132659: W tensorflow/tsl/framework/cpu_allocator_impl.cc:83] Allocation of 614400000 exceeds 10% of free system memory.
2023-05-23 10:09:49.408856: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'Placeholder/_0' with dtype float and shape [50000,32,32,3]
[[{{node Placeholder/_0}}]]
2023-05-23 10:09:49.409059: I tensorflow/core/common_runtime/executor.cc:1197] [/device:CPU:0] (DEBUG INFO) Executor start aborting (this does not indicate an error and you can ignore this message): INVALID_ARGUMENT: You must feed a value for placeholder tensor 'Placeholder/_0' with dtype float and shape [50000,32,32,3]
[[{{node Placeholder/_0}}]]
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
Cell In[4], line 37
30 od = OutlierVAE(threshold=.015, # threshold for outlier score
31 score_type='mse', # use MSE of reconstruction error for outlier detection
32 encoder_net=encoder_net, # can also pass VAE model instead
33 decoder_net=decoder_net, # of separate encoder and decoder
34 latent_dim=latent_dim,
35 samples=2)
36 # train
---> 37 od.fit(X_train,
38 loss_fn=elbo,
39 cov_elbo=dict(sim=.05),
40 epochs=50,
41 verbose=False)
43 # save the trained outlier detector
44 save_detector(od, filepath)
File ~/PycharmProjects/alibi-detect/alibi_detect/od/vae.py:136, in OutlierVAE.fit(self, X, loss_fn, optimizer, cov_elbo, epochs, batch_size, verbose, log_metric, callbacks)
133 kwargs['loss_fn_kwargs'] = {cov_elbo_type: tf.dtypes.cast(cov, tf.float32)}
135 # train
--> 136 trainer(*args, **kwargs)
File ~/PycharmProjects/alibi-detect/alibi_detect/models/tensorflow/trainer.py:87, in trainer(model, loss_fn, x_train, y_train, dataset, optimizer, loss_fn_kwargs, preprocess_fn, epochs, reg_loss_fn, batch_size, buffer_size, verbose, log_metric, callbacks)
85 if isinstance(loss_fn, Callable): # type: ignore
86 args = [y, y_hat] if tf.is_tensor(y_hat) else [y] + list(y_hat)
---> 87 loss = loss_fn(*args)
88 else:
89 loss = 0.
File ~/PycharmProjects/alibi-detect/alibi_detect/models/tensorflow/losses.py:41, in elbo(y_true, y_pred, cov_full, cov_diag, sim)
38 y_mn = tfp.distributions.MultivariateNormalFullCovariance(Flatten()(y_pred),
39 covariance_matrix=cov_full)
40 else:
---> 41 y_mn = tfp.distributions.MultivariateNormalDiag(Flatten()(y_pred),
42 scale_diag=cov_diag,
43 scale_identity_multiplier=sim)
44 loss = -tf.reduce_mean(y_mn.log_prob(Flatten()(y_true)))
45 return loss
File ~/.conda/envs/py310/lib/python3.10/site-packages/decorator.py:231, in decorate.<locals>.fun(*args, **kw)
229 def fun(*args, **kw):
230 if not kwsyntax:
--> 231 args, kw = fix(args, kw, sig)
232 return caller(func, *(extras + args), **kw)
File ~/.conda/envs/py310/lib/python3.10/site-packages/decorator.py:203, in fix(args, kwargs, sig)
199 def fix(args, kwargs, sig):
200 """
201 Fix args and kwargs to be consistent with the signature
202 """
--> 203 ba = sig.bind(*args, **kwargs)
204 ba.apply_defaults() # needed for test_dan_schult
205 return ba.args, ba.kwargs
File ~/.conda/envs/py310/lib/python3.10/inspect.py:3185, in Signature.bind(self, *args, **kwargs)
3180 def bind(self, /, *args, **kwargs):
3181 """Get a BoundArguments object, that maps the passed `args`
3182 and `kwargs` to the function's signature. Raises `TypeError`
3183 if the passed arguments can not be bound.
3184 """
-> 3185 return self._bind(args, kwargs)
File ~/.conda/envs/py310/lib/python3.10/inspect.py:3174, in Signature._bind(self, args, kwargs, partial)
3172 arguments[kwargs_param.name] = kwargs
3173 else:
-> 3174 raise TypeError(
3175 'got an unexpected keyword argument {arg!r}'.format(
3176 arg=next(iter(kwargs))))
3178 return self._bound_arguments_cls(self, arguments)
TypeError: got an unexpected keyword argument 'scale_identity_multiplier' |
Blocked pending #828 |
@dependabot rebase |
Looks like tensorflow-probability is no longer updatable, so this is no longer needed. |
Done in #828. |
Updates the requirements on tensorflow-probability to permit the latest version.
Release notes
Sourced from tensorflow-probability's releases.
Commits
e81e7e8
Update version and TF version requirement for TFP 0.20.0 release.14c180b
Updateinspect.getargspec
(deleted in Python 3.11) to.getfullargspec
.04a895d
Remove pinned keras-nightly dependency.3bc2c32
Revert "Redirect all references away from targets to be deleted onto the new ...80ea3c1
Revert "Refactorcase
andcase_v2
out ofcontrol_flow_ops.py
."774c6a4
AddSymmetricMatrixSpace
andConstantDiagonalSymmetricMatrixSpace
.abc165a
Add tests for Parallel acquisition functions when usingtransform_fn
.20b3d85
Re-enable tests after fixes to graph dismantling.9bc0d1e
Have low_rank_cholesky return the diagonal of the residual, as it is useful04c1006
Redirect all references away from targets to be deleted onto the new location...You can trigger a rebase of this PR by commenting
@dependabot rebase
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