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Keras Progress Bar broken when importing kerastuner

See original GitHub issue

Looks like importing kerastuner into a trivial keras proj causes the progress bar to not overwrite each update:-

`import tensorflow as tf import tensorflow_addons as tfa

from tensorflow.keras.datasets import mnist from tensorflow.keras.models import Sequential from tensorflow.keras.layers import Dense from tensorflow.keras.optimizers import SGD

#import kerastuner as kt

(x_train, y_train), (x_test, y_test) = mnist.load_data() x_train, x_test = x_train / 255.0, x_test / 255.0

model_keras_static = Sequential()
model_keras_static.add(Dense(512, input_dim=784, activation=‘sigmoid’)) model_keras_static.add(Dense(128, activation=‘sigmoid’)) model_keras_static.add(Dense(10, activation=‘softmax’))

model_keras_static.compile(loss=‘sparse_categorical_crossentropy’, metrics=[‘accuracy’], optimizer=SGD(learning_rate=0.1)) model_keras_static.fit(x_train.reshape(x_train.shape[0], 784), y_train, batch_size=1000, epochs=2, verbose=1)`

Train on 60000 samples Epoch 1/2 60000/60000 [==============================] - 2s 29us/sample - loss: 2.2526 - accuracy: 0.2699 Epoch 2/2 60000/60000 [==============================] - 1s 25us/sample - loss: 2.1220 - accuracy: 0.5087 <tensorflow.python.keras.callbacks.History at 0x1eb9e9f9408>

However if I uncomment the kerastuner import the output no longer overwrites

Train on 60000 samples Epoch 1/2 60000/60000 [==============================] - ETA: 12s - loss: 2.6233 - accuracy: 0.115 - ETA: 2s - loss: 2.3653 - accuracy: 0.102 - ETA: 1s - loss: 2.3288 - accuracy: 0.12 - ETA: 0s - loss: 2.3130 - accuracy: 0.12 - ETA: 0s - loss: 2.3037 - accuracy: 0.14 - ETA: 0s - loss: 2.2962 - accuracy: 0.17 - ETA: 0s - loss: 2.2882 - accuracy: 0.18 - ETA: 0s - loss: 2.2811 - accuracy: 0.20 - ETA: 0s - loss: 2.2743 - accuracy: 0.21 - ETA: 0s - loss: 2.2680 - accuracy: 0.23 - ETA: 0s - loss: 2.2618 - accuracy: 0.24 - 1s 13us/sample - loss: 2.2607 - accuracy: 0.2506 Epoch 2/2 60000/60000 [==============================] - ETA: 0s - loss: 2.1928 - accuracy: 0.40 - ETA: 0s - loss: 2.1914 - accuracy: 0.44 - ETA: 0s - loss: 2.1852 - accuracy: 0.42 - ETA: 0s - loss: 2.1791 - accuracy: 0.45 - ETA: 0s - loss: 2.1721 - accuracy: 0.45 - ETA: 0s - loss: 2.1650 - accuracy: 0.46 - ETA: 0s - loss: 2.1577 - accuracy: 0.47 - ETA: 0s - loss: 2.1507 - accuracy: 0.48 - ETA: 0s - loss: 2.1420 - accuracy: 0.48 - ETA: 0s - loss: 2.1332 - accuracy: 0.49 - 1s 9us/sample - loss: 2.1293 - accuracy: 0.4950 <tensorflow.python.keras.callbacks.History at 0x196d7342408>

Any suggestions ?

absl-py==0.9.0 argon2-cffi @ file:///C:/ci/argon2-cffi_1596828549974/work astor==0.8.0 attrs==19.3.0 backcall==0.2.0 bleach==3.1.5 blinker==1.4 brotlipy==0.7.0 cachetools @ file:///tmp/build/80754af9/cachetools_1596822027882/work certifi==2020.6.20 cffi==1.14.0 chardet==3.0.4 click==7.1.2 colorama==0.4.3 cryptography==2.9.2 cycler==0.10.0 decorator==4.4.2 defusedxml==0.6.0 entrypoints==0.3 future==0.18.2 gast==0.2.2 google-auth @ file:///tmp/build/80754af9/google-auth_1596863485713/work google-auth-oauthlib==0.4.1 google-pasta==0.2.0 grpcio==1.27.2 h5py==2.10.0 idna @ file:///tmp/build/80754af9/idna_1593446292537/work importlib-metadata @ file:///C:/ci/importlib-metadata_1593446525189/work ipykernel @ file:///C:/ci/ipykernel_1596208728219/work/dist/ipykernel-5.3.4-py3-none-any.whl ipython @ file:///C:/ci/ipython_1596868620883/work ipython-genutils==0.2.0 ipywidgets==7.5.1 jedi==0.15.2 Jinja2==2.11.2 joblib @ file:///home/conda/feedstock_root/build_artifacts/joblib_1593624380152/work json5==0.9.5 jsonschema @ file:///C:/ci/jsonschema_1594363671836/work jupyter-client @ file:///tmp/build/80754af9/jupyter_client_1594826976318/work jupyter-core==4.6.3 jupyterlab==2.1.5 jupyterlab-server @ file:///tmp/build/80754af9/jupyterlab_server_1594164409481/work Keras-Applications @ file:///tmp/build/80754af9/keras-applications_1594366238411/work Keras-Preprocessing==1.1.0 keras-tuner==1.0.1 kiwisolver==1.2.0 Markdown==3.1.1 MarkupSafe @ file:///C:/ci/markupsafe_1594405949945/work matplotlib @ file:///C:/ci/matplotlib-base_1592846084747/work mistune @ file:///C:/ci/mistune_1594373272338/work mkl-fft==1.1.0 mkl-random==1.1.1 mkl-service==2.3.0 nbconvert @ file:///C:/ci/nbconvert_1594372737468/work nbformat==5.0.7 notebook @ file:///C:/ci/notebook_1596837179121/work numpy @ file:///C:/ci/numpy_and_numpy_base_1596233945180/work oauthlib==3.1.0 opt-einsum==3.1.0 packaging==20.4 pandas @ file:///D:/bld/pandas_1595958729109/work pandocfilters==1.4.2 parso @ file:///tmp/build/80754af9/parso_1596826841367/work pickleshare @ file:///C:/ci/pickleshare_1594374056827/work prometheus-client==0.8.0 prompt-toolkit==3.0.5 protobuf==3.12.3 pyasn1==0.4.8 pyasn1-modules==0.2.7 pycparser @ file:///tmp/build/80754af9/pycparser_1594388511720/work Pygments==2.6.1 PyJWT==1.7.1 pyOpenSSL @ file:///tmp/build/80754af9/pyopenssl_1594392929924/work pyparsing==2.4.7 pyreadline==2.1 pyrsistent==0.16.0 PySocks @ file:///C:/ci/pysocks_1594394709107/work python-dateutil==2.8.1 pytz==2020.1 pywin32==227 pywinpty==0.5.7 pyzmq==19.0.1 requests @ file:///tmp/build/80754af9/requests_1592841827918/work requests-oauthlib==1.3.0 rsa @ file:///tmp/build/80754af9/rsa_1596998415516/work scikit-learn @ file:///D:/bld/scikit-learn_1596546337481/work scipy @ file:///C:/ci/scipy_1592916958183/work seaborn==0.10.1 Send2Trash==1.5.0 six==1.15.0 tabulate==0.8.7 tensorboard==2.2.1 tensorboard-plugin-wit==1.6.0 tensorflow==2.1.0 tensorflow-addons==0.9.1 tensorflow-estimator==2.1.0 termcolor==1.1.0 terminado==0.8.3 terminaltables==3.1.0 testpath==0.4.4 threadpoolctl @ file:///tmp/tmp79xdzxkt/threadpoolctl-2.1.0-py3-none-any.whl tornado==6.0.4 tqdm @ file:///home/conda/feedstock_root/build_artifacts/tqdm_1596476591553/work traitlets==4.3.3 typeguard==2.9.1 urllib3==1.25.9 wcwidth @ file:///tmp/build/80754af9/wcwidth_1593447189090/work webencodings==0.5.1 Werkzeug==0.14.1 widgetsnbextension @ file:///D:/bld/widgetsnbextension_1594164533747/work win-inet-pton==1.1.0 wincertstore==0.2 wrapt==1.12.1 zipp==3.1.0

Issue Analytics

State:
Created 3 years ago
Comments:10 (5 by maintainers)

Top GitHub Comments

4reactions

msaad1311commented, Aug 19, 2020

I am facing the similar issue. Im running my code on Jupyter Notebook. The versions which i am using are TF=2.2.0 and Keras=2.3.1

0reactions

jpodivincommented, May 2, 2021

The tensorflow API version 2.1 doesn’t seem to have that member in its namespace. https://www.tensorflow.org/versions/r2.1/api_docs/python/tf/keras/layers/experimental/preprocessing

The easiest fix would be updating your TF to a version that does. For example the 2.2. https://www.tensorflow.org/versions/r2.2/api_docs/python/tf/keras/layers/experimental/preprocessing

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