A CNN for time-series classification
Explanation of the code at robromijnders.github.io/CNN_tsc
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View Code? Open in Web Editor NEWA CNN for time-series classification
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TypeError: Fetch argument None has invalid type <class 'NoneType'>
Thanks for the nice skeleton repo @RobRomijnders :)
When I run your code off-the-shelf after the tf_upgrades to TF 1.xx I hit the following error:
Traceback (most recent call last):
File "tsc_main.py", line 76, in <module>
cost_val, summ,acc_val = sess.run([model.cost,model.merged,model.accuracy],feed_dict = {model.input: X_batch, model.labels: y_batch, model.keep_prob:1.0})
File "/home/petteri/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 767, in run
run_metadata_ptr)
File "/home/petteri/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 952, in _run
fetch_handler = _FetchHandler(self._graph, fetches, feed_dict_string)
File "/home/petteri/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 408, in __init__
self._fetch_mapper = _FetchMapper.for_fetch(fetches)
File "/home/petteri/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 230, in for_fetch
return _ListFetchMapper(fetch)
File "/home/petteri/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 337, in __init__
self._mappers = [_FetchMapper.for_fetch(fetch) for fetch in fetches]
File "/home/petteri/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 337, in <listcomp>
self._mappers = [_FetchMapper.for_fetch(fetch) for fetch in fetches]
File "/home/petteri/anaconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 227, in for_fetch
(fetch, type(fetch)))
TypeError: Fetch argument None has invalid type <class 'NoneType'>Invalid Argument Error when classes missing
When you run the tool with a dataset with a feature class missing e.g. 4 missing below
1,1.13324,1351.0,6862.4800000000005,3338.6999999999994,6859.446551724133
2,1.132653246753247,1350.7333333333336,6859.446551724133,4640.164285714285,6858.642028985517
3,1.132447198697068,1351.0458970099692,6858.642028985517,4996.519021739133,6860.627397260285
0,1.1325953916004556,1350.2446681415893,6860.627397260285,4993.749596774188,6862.286111111106
5,1.13324,1351.0,6862.4800000000005,3338.6999999999994,6859.446551724133
It throws:
InvalidArgumentError (see above for traceback): Received a label value of 5 which is outside the valid range of [0, 5). Label values: 1 2 3 0 5 3 5 5 3 3 5 5 3 3 5 5 3 3 5 5 3 3 5 5 3 3 5 5 3 3 5 5 3 3 5 5 3 3 5 5
[[Node: SoftMax/SparseSoftmaxCrossEntropyWithLogits/SparseSoftmaxCrossEntropyWithLogits = SparseSoftmaxCrossEntropyWithLogits[T=DT_FLOAT, Tlabels=DT_INT64, _device="/job:localhost/replica:0/task:0/cpu:0"](Fully_Connected2/add, _recv_Ground_truth_0)]]
but is fine if all classes are present 1 to 5.
1,1.13324,1351.0,6862.4800000000005,3338.6999999999994,6859.446551724133
2,1.132653246753247,1350.7333333333336,6859.446551724133,4640.164285714285,6858.642028985517
3,1.132447198697068,1351.0458970099692,6858.642028985517,4996.519021739133,6860.627397260285
4,1.1325953916004556,1350.2446681415893,6860.627397260285,4993.749596774188,6862.286111111106
5,1.13324,1351.0,6862.4800000000005,3338.6999999999994,6859.446551724133
Is this expected or a bug or limitation?
How to extract predictions?
Thanks for the nice skeleton repo @RobRomijnders
I followed the given codes and was able to train a model and evaluate its accuracy.
However, the codes don't show how to make predictions given a model.
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