Closed Dvdgg closed 1 year ago
@Dvdgg,
This issue looks more like an environment error. I suspect the issue is that one Tensorflow is installed directly and other by anaconda environment which results in conflict. The suggested workaround would be to create a new conda environment, activate it and install Tensorflow and TF-Hub. Please let us know if this resolves the issue. Thanks.
Hello singhniraj08, i tried to create a new environment with the same packages and the problem still remain ;
(new conda environment, with a new kernel for jupyter notebook)
is it possible to find and add a file called "path_helpers" to avoid this error, or a procedure to replace the folder in AppData / roaming, in order to avoid some conflicts or other types of errors ?
sincerely yours, David
ImportError Traceback (most recent call last) Cell In[3], line 3 1 #from absl import logging ----> 3 import tensorflow_hub as hub
File ~\anaconda3\envs\p6\lib\site-packages\tensorflow_hub__init__.py:88 76 raise ImportError( 77 "\n\nThis version of tensorflow_hub requires tensorflow " 78 "version >= {required}; Detected an installation of version {present}. " (...) 82 required=required_tensorflow_version, 83 present=tf.version)) 85 _ensure_tf_install() ---> 88 from tensorflow_hub.estimator import LatestModuleExporter 89 from tensorflow_hub.estimator import register_module_for_export 90 from tensorflow_hub.feature_column import image_embedding_column
File ~\anaconda3\envs\p6\lib\site-packages\tensorflow_hub\estimator.py:62 55 raise ValueError( 56 "There is already a module registered to be exported as %r" 57 % export_name) 58 tf.compat.v1.add_to_collection(_EXPORT_MODULES_COLLECTION, 59 (export_name, module)) ---> 62 class LatestModuleExporter(tf.compat.v1.estimator.Exporter): 63 """Regularly exports registered modules into timestamped directories. 64 65 Warning: Deprecated. This belongs to the hub.Module API and TF1 Hub format. (...) 88 THIS FUNCTION IS DEPRECATED. 89 """ 91 def init(self, name, serving_input_fn, exports_to_keep=5):
File ~\anaconda3\envs\p6\lib\site-packages\tensorflow\python\util\lazy_loader.py:58, in LazyLoader.getattr(self, item) 57 def getattr(self, item): ---> 58 module = self._load() 59 return getattr(module, item)
File ~\anaconda3\envs\p6\lib\site-packages\tensorflow\python\util\lazy_loader.py:41, in LazyLoader._load(self) 39 """Load the module and insert it into the parent's globals.""" 40 # Import the target module and insert it into the parent's namespace ---> 41 module = importlib.import_module(self.name) 42 self._parent_module_globals[self._local_name] = module 44 # Emit a warning if one was specified
File ~\anaconda3\envs\p6\lib\importlib__init__.py:126, in import_module(name, package) 124 break 125 level += 1 --> 126 return _bootstrap._gcd_import(name[level:], package, level)
File ~\AppData\Roaming\Python\Python310\site-packages\tensorflow_estimator\python\estimator\api__init__.py:8 3 """Public API for tf. namespace. 4 """ 6 import sys as _sys ----> 8 from tensorflow_estimator.python.estimator.api._v1 import estimator 9 from tensorflow.python.util import module_wrapper as _module_wrapper 11 if not isinstance(_sys.modules[name], _module_wrapper.TFModuleWrapper):
File ~\AppData\Roaming\Python\Python310\site-packages\tensorflow_estimator\python\estimator\api_v1\estimator__init__.py:8 3 """Estimator: High level tools for working with models. 4 """ 6 import sys as _sys ----> 8 from tensorflow_estimator.python.estimator.api._v1.estimator import experimental 9 from tensorflow_estimator.python.estimator.api._v1.estimator import export 10 from tensorflow_estimator.python.estimator.api._v1.estimator import inputs
File ~\AppData\Roaming\Python\Python310\site-packages\tensorflow_estimator\python\estimator\api_v1\estimator\experimental__init__.py:8 3 """Public API for tf.estimator.experimental namespace. 4 """ 6 import sys as _sys ----> 8 from tensorflow_estimator.python.estimator.canned.dnn import dnn_logit_fn_builder 9 from tensorflow_estimator.python.estimator.canned.kmeans import KMeansClustering as KMeans 10 from tensorflow_estimator.python.estimator.canned.linear import LinearSDCA
File ~\AppData\Roaming\Python\Python310\site-packages\tensorflow_estimator\python\estimator\canned\dnn.py:26 24 from tensorflow.python.feature_column import feature_column_lib 25 from tensorflow.python.framework import ops ---> 26 from tensorflow_estimator.python.estimator import estimator 27 from tensorflow_estimator.python.estimator.canned import head as head_lib 28 from tensorflow_estimator.python.estimator.canned import optimizers
File ~\AppData\Roaming\Python\Python310\site-packages\tensorflow_estimator\python\estimator\estimator.py:39 37 from tensorflow.python.framework import ops 38 from tensorflow.python.profiler import trace ---> 39 from tensorflow.python.saved_model import path_helpers 40 from tensorflow.python.summary import summary 41 from tensorflow.python.training import basic_session_run_hooks
ImportError: cannot import name 'path_helpers' from 'tensorflow.python.saved_model' (C:\Users\raoul\anaconda3\envs\p6\lib\site-packages\tensorflow\python\saved_model__init__.py)
@Dvdgg,
I was unable to replicate this issue. Please find attached the below screenshot. TF-Hub works with Tensorflow 2.12 and Python 3.10. I would suggest you to update the Tensorflow packages and make sure multiple Tensorflow packages are not installed in your machine using pip and conda. Thanks.
Hello singhniraj08, thanks , i have passed many days to search a solution ; i have removed conda, python, the files. Remove and reinstall the driver, cudnn, cuda...
finally, i have tested this :
thanks to this tutorial , it worked
windows 10 famille version 22H2 / win-64 NVIDIA GeForce GTX 1050
with this kind of environment, it worked :
absl-py 0.15.0 pypi_0 pypi astunparse 1.6.3 pypi_0 pypi attrs 23.1.0 pypi_0 pypi backcall 0.2.0 pypi_0 pypi ca-certificates 2023.5.7 h56e8100_0 conda-forge cachetools 4.2.4 pypi_0 pypi certifi 2023.5.7 pypi_0 pypi charset-normalizer 3.1.0 pypi_0 pypi clang 5.0 pypi_0 pypi click 8.1.3 pypi_0 pypi colorama 0.4.6 pypi_0 pypi cudatoolkit 11.2.2 h933977f_10 conda-forge cudnn 8.1.0.77 h3e0f4f4_0 conda-forge cycler 0.11.0 pypi_0 pypi cython 0.29.23 pypi_0 pypi debugpy 1.6.7 pypi_0 pypi decorator 5.1.1 pypi_0 pypi dill 0.3.6 pypi_0 pypi entrypoints 0.4 pypi_0 pypi filelock 3.12.0 pypi_0 pypi flatbuffers 1.12 pypi_0 pypi fsspec 2023.5.0 pypi_0 pypi gast 0.4.0 pypi_0 pypi gensim 4.1.2 pypi_0 pypi google-auth 1.35.0 pypi_0 pypi google-auth-oauthlib 0.4.6 pypi_0 pypi google-pasta 0.2.0 pypi_0 pypi grpcio 1.54.2 pypi_0 pypi h5py 3.1.0 pypi_0 pypi huggingface-hub 0.14.1 pypi_0 pypi idna 3.4 pypi_0 pypi importlib-metadata 6.6.0 pypi_0 pypi ipykernel 6.4.2 pypi_0 pypi ipython 7.34.0 pypi_0 pypi ipython-genutils 0.2.0 pypi_0 pypi jedi 0.18.2 pypi_0 pypi jinja2 3.0.2 pypi_0 pypi joblib 1.2.0 pypi_0 pypi jsonschema 4.17.3 pypi_0 pypi jupyter-client 7.4.9 pypi_0 pypi jupyter-core 5.3.0 pypi_0 pypi keras 2.6.0 pypi_0 pypi keras-preprocessing 1.1.2 pypi_0 pypi kiwisolver 1.4.4 pypi_0 pypi markdown 3.4.3 pypi_0 pypi markupsafe 2.1.2 pypi_0 pypi matplotlib 3.4.3 pypi_0 pypi matplotlib-inline 0.1.6 pypi_0 pypi nbformat 5.1.3 pypi_0 pypi nest-asyncio 1.5.6 pypi_0 pypi nltk 3.6.5 pypi_0 pypi numpy 1.19.5 pypi_0 pypi oauthlib 3.2.2 pypi_0 pypi opencv-python 4.5.4.58 pypi_0 pypi openssl 1.1.1q h8ffe710_0 conda-forge opt-einsum 3.3.0 pypi_0 pypi packaging 23.1 pypi_0 pypi pandas 1.3.4 pypi_0 pypi parso 0.8.3 pypi_0 pypi pickleshare 0.7.5 pypi_0 pypi pillow 9.5.0 pypi_0 pypi pip 23.0.1 py39haa95532_0 platformdirs 3.5.1 pypi_0 pypi plotly 5.3.1 pypi_0 pypi prompt-toolkit 3.0.38 pypi_0 pypi protobuf 3.19.6 pypi_0 pypi pyasn1 0.5.0 pypi_0 pypi pyasn1-modules 0.3.0 pypi_0 pypi pygments 2.15.1 pypi_0 pypi pyparsing 3.0.9 pypi_0 pypi pyrsistent 0.19.3 pypi_0 pypi python 3.9.0 h6244533_2 python-dateutil 2.8.2 pypi_0 pypi pytz 2023.3 pypi_0 pypi pywin32 306 pypi_0 pypi pyyaml 6.0 pypi_0 pypi pyzmq 25.0.2 pypi_0 pypi regex 2023.5.5 pypi_0 pypi requests 2.30.0 pypi_0 pypi requests-oauthlib 1.3.1 pypi_0 pypi rsa 4.9 pypi_0 pypi sacremoses 0.0.53 pypi_0 pypi scikit-learn 1.2.0 pypi_0 pypi scipy 1.10.1 pypi_0 pypi seaborn 0.11.2 pypi_0 pypi setuptools 66.0.0 py39haa95532_0 six 1.15.0 pypi_0 pypi smart-open 6.3.0 pypi_0 pypi sqlite 3.41.2 h2bbff1b_0 tenacity 8.2.2 pypi_0 pypi tensorboard 2.6.0 pypi_0 pypi tensorboard-data-server 0.6.1 pypi_0 pypi tensorboard-plugin-wit 1.8.1 pypi_0 pypi tensorflow 2.6.5 pypi_0 pypi tensorflow-estimator 2.6.0 pypi_0 pypi tensorflow-hub 0.12.0 pypi_0 pypi termcolor 1.1.0 pypi_0 pypi threadpoolctl 3.1.0 pypi_0 pypi tokenizers 0.10.3 pypi_0 pypi tornado 6.3.2 pypi_0 pypi tqdm 4.65.0 pypi_0 pypi traitlets 5.9.0 pypi_0 pypi transformers 4.12.2 pypi_0 pypi typing-extensions 3.10.0.2 pypi_0 pypi tzdata 2023c h04d1e81_0 urllib3 2.0.2 pypi_0 pypi vc 14.2 h21ff451_1 vs2015_runtime 14.27.29016 h5e58377_2 wcwidth 0.2.6 pypi_0 pypi werkzeug 2.3.4 pypi_0 pypi wheel 0.38.4 py39haa95532_0 wrapt 1.12.1 pypi_0 pypi zipp 3.15.0 pypi_0 pypi
but now....
i have another problem:
keras VGG16() doesn't worked when i use the pre-trained model and apply the line model.predict() ; the kernel died.
i feel the tears on my skin...no message, just the kernel is died when the code line is applied
from tensorflow.keras.models import Model, Sequential from tensorflow.keras.applications.vgg16 import VGG16
base_model = VGG16(weights='imagenet', include_top=True)
from tensorflow.keras.preprocessing.image import load_img, img_to_array from keras.preprocessing import image from tensorflow.keras.applications.vgg16 import preprocess_input
images_features = [] i=0 for image_file in dataFull_vf["image_path"] : if i%20 == 0 : print(i) i +=1 imge = load_img(image_file, target_size=(224, 224)) imge_b = image.img_to_array(imge) # Convertit une instance d'image PIL en un tableau Numpy
imge_c = np.expand_dims(imge_b, axis=0) # augmente le nombre de dimension du tableau numpy représentant l'image
imge_d = preprocess_input(imge_c)
prepared_images_np = np.array(imge_d)
#features = base_model.predict(prepared_images_np) #----> fait mourir le kernel
#images_features.append(features)
it was just a test, in order to see if something happen and then try to understand, improve...
but i don't know what to do, and my version of tensorflow is adapted for windows 10..if i upgrade, the risk is to lose the detection and possibility to use my gpu...i don't want that
@Dvdgg,
I am able to make predictions using VGG16. Can you try the similar code in your environment and see if that works. Ref: gist
I can understand getting a perfect environment to run your code is frustrating. However, I have a suggestion to install linux with WSL2 on your windows and there you can make a conda environment and try to install latest release of tensorflow. Ref: Install TensorFlow with GPU Acceleration Simultaneously for Windows and WSL Linux (2) Let us know if this works for you. Thank you!
Hello singhniraj08,
thanks for your answer, and for the example.
unfortunately, the problem still remind on my config , as you can see below : kernel die when we call the keras model vgg16 to predict ;
if i have enough time, i will try the alternative with wsl linux but i have never do this before.
If i remember what i have seen on this kind of solution, it's necessary to use docker , isn't it ?
sincerely,
just in case, i have also tested this :
https://docs.nvidia.com/deeplearning/cudnn/install-guide/index.html#install-windows
not worked with my version of tensorflow (in the list of packages i have posted in this in this chat, there is 4 days ago
sincerely, Dav
@Dvdgg, This issue seems to be with your environment and Tensorflow rather than TF-Hub. I would request you to close this issue and follow this issue with Tensorflow repo by creating new issue. Thanks.
What happened?
hello, i'm trying to import tensorflow_hub and I can't. The issue seems to be unique (i have not found a similar issue). If someone may help me, please ?
It's like there is a problem between a file in "roaming" and the file of anaconda environment (base, in anaconda3 ) ? I don't understand the problem.
sincerely yours,
Relevant code
Relevant log output
tensorflow_hub Version
0.12.0 (latest stable release)
TensorFlow Version
other (please specify)
Other libraries
conda environment tensorflow 2.10.1 cudatoolkit 11.2.2 cudnn 8.1.0.77
system windows 10 famille version 22H2 / win-64 physical_device GPU_desc: "device: 0, name: NVIDIA GeForce GTX 1050, compute capability: 6.1"
version anaconda , python conda version : 23.3.1 conda-build version : 3.24.0 python version : 3.10.9.final.0 virtual packages : __archspec=1=x86_64 cuda=12.1=0 win=0=0
Python Version
3.x
OS
Windows