yt-spam-classifier
yt-spam-classifier copied to clipboard
Published
20 hours ago •
Savjee
Savjee
CancelledError on M1 Macbook Air Big Sur 12.0
Hi,
I'm trying to recreate your steps and run into the following issue when running this step: All previous steps work fine. I'm using your dataset.
early_stop = EarlyStopping(monitor='val_loss', mode='min', verbose=1, patience=10)
model.compile(optimizer='rmsprop', loss='binary_crossentropy', metrics=['accuracy'])
# fit the model
model.fit(X_train,
y_train,
epochs=40,
batch_size=512,
validation_data=(X_test, y_test),
verbose=1,
callbacks=[early_stop]
)
Which leads to the following issue:
CancelledError Traceback (most recent call last)
/var/folders/7t/tgrdz77j2r93smmw74pd9ny40000gn/T/ipykernel_4079/1037202941.py in <module>
4
5 # fit the model
----> 6 model.fit(X_train,
7 y_train,
8 epochs=10,
~/miniforge3/envs/apple_tf/lib/python3.9/site-packages/tensorflow/python/keras/engine/training_v1.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_freq, max_queue_size, workers, use_multiprocessing, **kwargs)
793
794 func = self._select_training_loop(x)
--> 795 return func.fit(
796 self,
797 x=x,
~/miniforge3/envs/apple_tf/lib/python3.9/site-packages/tensorflow/python/keras/engine/training_arrays_v1.py in fit(self, model, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_freq, **kwargs)
642 val_x, val_y, val_sample_weights = None, None, None
643
--> 644 return fit_loop(
645 model,
646 inputs=x,
~/miniforge3/envs/apple_tf/lib/python3.9/site-packages/tensorflow/python/keras/engine/training_arrays_v1.py in model_iteration(model, inputs, targets, sample_weights, batch_size, epochs, verbose, callbacks, val_inputs, val_targets, val_sample_weights, shuffle, initial_epoch, steps_per_epoch, validation_steps, validation_freq, mode, validation_in_fit, prepared_feed_values_from_dataset, steps_name, **kwargs)
378
379 # Get outputs.
--> 380 batch_outs = f(ins_batch)
381 if not isinstance(batch_outs, list):
382 batch_outs = [batch_outs]
~/miniforge3/envs/apple_tf/lib/python3.9/site-packages/tensorflow/python/keras/backend.py in __call__(self, inputs)
4052 self._make_callable(feed_arrays, feed_symbols, symbol_vals, session)
4053
-> 4054 fetched = self._callable_fn(*array_vals,
4055 run_metadata=self.run_metadata)
4056 self._call_fetch_callbacks(fetched[-len(self._fetches):])
~/miniforge3/envs/apple_tf/lib/python3.9/site-packages/tensorflow/python/client/session.py in __call__(self, *args, **kwargs)
1478 try:
1479 run_metadata_ptr = tf_session.TF_NewBuffer() if run_metadata else None
-> 1480 ret = tf_session.TF_SessionRunCallable(self._session._session,
1481 self._handle, args,
1482 run_metadata_ptr)
CancelledError: [_Derived_]RecvAsync is cancelled.
[[{{node keras_layer/StatefulPartitionedCall}}]]
Conda List:
# Name Version Build Channel
absl-py 0.10.0 pyhd8ed1ab_1 conda-forge
aiohttp 3.7.4.post0 py39h5161555_0 conda-forge
appnope 0.1.2 py39h2804cbe_1 conda-forge
argon2-cffi 20.1.0 py39h5161555_2 conda-forge
astunparse 1.6.3 pyhd8ed1ab_0 conda-forge
async-timeout 3.0.1 py_1000 conda-forge
async_generator 1.10 py_0 conda-forge
attrs 21.2.0 pyhd8ed1ab_0 conda-forge
backcall 0.2.0 pyh9f0ad1d_0 conda-forge
backports 1.0 py_2 conda-forge
backports.functools_lru_cache 1.6.4 pyhd8ed1ab_0 conda-forge
bleach 4.1.0 pyhd8ed1ab_0 conda-forge
blinker 1.4 py_1 conda-forge
brotlipy 0.7.0 py39h5161555_1001 conda-forge
c-ares 1.17.2 h3422bc3_0 conda-forge
ca-certificates 2021.5.30 h4653dfc_0 conda-forge
cached-property 1.5.2 hd8ed1ab_1 conda-forge
cached_property 1.5.2 pyha770c72_1 conda-forge
cachetools 4.2.2 pyhd8ed1ab_0 conda-forge
certifi 2021.5.30 py39h2804cbe_0 conda-forge
cffi 1.14.6 py39h52b1de0_1 conda-forge
chardet 4.0.0 py39h2804cbe_1 conda-forge
charset-normalizer 2.0.0 pyhd8ed1ab_0 conda-forge
click 8.0.1 py39h2804cbe_0 conda-forge
cryptography 3.4.7 py39h73257c9_0 conda-forge
cycler 0.10.0 py_2 conda-forge
dataclasses 0.8 pyhc8e2a94_3 conda-forge
debugpy 1.4.1 py39hfb83b0d_0 conda-forge
decorator 5.1.0 pyhd8ed1ab_0 conda-forge
defusedxml 0.7.1 pyhd8ed1ab_0 conda-forge
entrypoints 0.3 pyhd8ed1ab_1003 conda-forge
flatbuffers 1.12 pypi_0 pypi
freetype 2.10.4 h17b34a0_1 conda-forge
gast 0.4.0 pyh9f0ad1d_0 conda-forge
google-auth 1.35.0 pyh6c4a22f_0 conda-forge
google-auth-oauthlib 0.4.6 pyhd8ed1ab_0 conda-forge
google-pasta 0.2.0 pyh8c360ce_0 conda-forge
grpcio 1.34.1 py39h1eaaf2b_0 conda-forge
h5py 3.1.0 nompi_py39h99babb8_100 conda-forge
hdf5 1.10.6 nompi_h0fc092c_1114 conda-forge
idna 3.1 pyhd3deb0d_0 conda-forge
importlib-metadata 4.8.1 py39h2804cbe_0 conda-forge
ipykernel 6.4.1 py39h32adebf_0 conda-forge
ipython 7.28.0 py39h32adebf_0 conda-forge
ipython_genutils 0.2.0 py_1 conda-forge
jbig 2.1 h3422bc3_2003 conda-forge
jedi 0.18.0 py39h2804cbe_2 conda-forge
jinja2 3.0.1 pyhd8ed1ab_0 conda-forge
joblib 1.0.1 pyhd8ed1ab_0 conda-forge
jpeg 9d h27ca646_0 conda-forge
jsonschema 3.2.0 pyhd8ed1ab_3 conda-forge
jupyter_client 7.0.4 pyhd8ed1ab_0 conda-forge
jupyter_core 4.8.1 py39h2804cbe_0 conda-forge
jupyterlab_pygments 0.1.2 pyh9f0ad1d_0 conda-forge
keras 2.6.0 pyhd8ed1ab_0 conda-forge
keras-nightly 2.5.0.dev2021032900 pypi_0 pypi
keras-preprocessing 1.1.2 pyhd8ed1ab_0 conda-forge
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libcblas 3.9.0 11_osxarm64_openblas conda-forge
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libcxx 12.0.1 h168391b_0 conda-forge
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libedit 3.1.20191231 hc8eb9b7_2 conda-forge
libev 4.33 h642e427_1 conda-forge
libffi 3.4.2 hbdafb3b_4 conda-forge
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liblapack 3.9.0 11_osxarm64_openblas conda-forge
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libprotobuf 3.18.0 hccf11d3_1 conda-forge
libsodium 1.0.18 h27ca646_1 conda-forge
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libtiff 4.3.0 hc6122e1_1 conda-forge
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llvm-openmp 12.0.1 hf3c4609_1 conda-forge
lz4-c 1.9.3 hbdafb3b_1 conda-forge
markdown 3.3.4 pyhd8ed1ab_0 conda-forge
markupsafe 2.0.1 py39h5161555_0 conda-forge
matplotlib-base 3.4.3 py39h5aa4fe7_1 conda-forge
matplotlib-inline 0.1.3 pyhd8ed1ab_0 conda-forge
mistune 0.8.4 py39h5161555_1004 conda-forge
multidict 5.1.0 py39h5161555_1 conda-forge
nbclient 0.5.4 pyhd8ed1ab_0 conda-forge
nbconvert 6.2.0 py39h2804cbe_0 conda-forge
nbformat 5.1.3 pyhd8ed1ab_0 conda-forge
ncurses 6.2 h9aa5885_4 conda-forge
nest-asyncio 1.5.1 pyhd8ed1ab_0 conda-forge
notebook 6.4.4 pyha770c72_0 conda-forge
numpy 1.19.5 py39h1f3b974_2 conda-forge
oauthlib 3.1.1 pyhd8ed1ab_0 conda-forge
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protobuf 3.18.0 py39hfb83b0d_0 conda-forge
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pyasn1 0.4.8 py_0 conda-forge
pyasn1-modules 0.2.7 py_0 conda-forge
pycparser 2.20 pyh9f0ad1d_2 conda-forge
pygments 2.10.0 pyhd8ed1ab_0 conda-forge
pyjwt 2.1.0 pyhd8ed1ab_0 conda-forge
pyopenssl 20.0.1 pyhd8ed1ab_0 conda-forge
pyparsing 2.4.7 pyh9f0ad1d_0 conda-forge
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pysocks 1.7.1 py39h2804cbe_3 conda-forge
python 3.9.7 h54d631c_2_cpython conda-forge
python-dateutil 2.8.2 pyhd8ed1ab_0 conda-forge
python_abi 3.9 2_cp39 conda-forge
pytz 2021.1 pyhd8ed1ab_0 conda-forge
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pyzmq 22.3.0 py39h02c6a76_0 conda-forge
readline 8.1 hedafd6a_0 conda-forge
requests 2.26.0 pyhd8ed1ab_0 conda-forge
requests-oauthlib 1.3.0 pyh9f0ad1d_0 conda-forge
rsa 4.7.2 pyh44b312d_0 conda-forge
scikit-learn 1.0 py39h12ba089_1 conda-forge
scipy 1.7.0 py39h5060c3b_0 conda-forge
seaborn 0.11.2 hd8ed1ab_0 conda-forge
seaborn-base 0.11.2 pyhd8ed1ab_0 conda-forge
send2trash 1.8.0 pyhd8ed1ab_0 conda-forge
setuptools 58.0.4 py39h2804cbe_2 conda-forge
six 1.15.0 pyh9f0ad1d_0 conda-forge
sqlite 3.36.0 h72a2b83_2 conda-forge
statsmodels 0.12.2 py39h20ef057_0 conda-forge
tensorboard 2.6.0 pyhd8ed1ab_1 conda-forge
tensorboard-data-server 0.6.0 py39hfb8cd70_0 conda-forge
tensorboard-plugin-wit 1.8.0 pyh44b312d_0 conda-forge
tensorflow-deps 2.5.0 0 <unknown>
tensorflow-estimator 2.5.0 pypi_0 pypi
tensorflow-hub 0.12.0 pypi_0 pypi
tensorflow-macos 2.5.0 pypi_0 pypi
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termcolor 1.1.0 py_2 conda-forge
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wrapt 1.12.1 py39h5161555_3 conda-forge
xz 5.2.5 h642e427_1 conda-forge
yarl 1.6.3 py39h5161555_2 conda-forge
zeromq 4.3.4 hbdafb3b_1 conda-forge
zipp 3.5.0 pyhd8ed1ab_0 conda-forge
zlib 1.2.11 h31e879b_1009 conda-forge
zstd 1.5.0 h861e0a7_0 conda-forge