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KeyError: 'classification_head_1/spatial_reduction_1/reduction_type'

See original GitHub issue

AutoKeras version: master KerasTuner version: master TensorFlow version: 2.2.0

I am running a multi label image classifier based on the example code here: https://autokeras.com/tutorial/image_classification/

I was able to get the example code working with these dependency versions.

Now I am trying to modify the code to run on my own dataset. I have loaded in my own images and labels. I have set multi_label=True since my dataset can have more than one label per image.

My process seems to be pretty standard. After loading in the data and labels, I transform them into numpy arrays, then use MultiLabelBinarizer to pre-process, split into test and train sets, and run the image classiifer. Code is here:

data = np.array(data, dtype="float") / 255.0
labels = np.array(labels)

# binarize the labels using scikit-learn's special multi-label
# binarizer implementation
print("[INFO] class labels:")
mlb = MultiLabelBinarizer()
labels = mlb.fit_transform(labels)
# loop over each of the possible class labels and show them
for (i, label) in enumerate(mlb.classes_):
    print("{}. {}".format(i + 1, label))

(x_train, x_test, y_train, y_test) = train_test_split(data, labels, test_size=0.2, random_state=42)
print(x_train.shape)  # (60000, 28, 28)
print(y_train.shape)  # (60000,)
print(y_train[:3])  # array([7, 2, 1], dtype=uint8)

Afterwards, code is straight from the example, except setting multi_label=True:

# Initialize the image classifier.
clf = ak.ImageClassifier(max_trials=3, multi_label=True)  # It tries 10 different models.
# Feed the image classifier with training data.
clf.fit(x_train, y_train, epochs=3)


# Predict with the best model.
predicted_y = clf.predict(x_test)
print(predicted_y)


# Evaluate the best model with testing data.
print(clf.evaluate(x_test, y_test))

The code runs fine for a few trials. Then, I get this error:

KeyError: 'classification_head_1/spatial_reduction_1/reduction_type'
[Warning] Invalid model 0/5

Here is the full stack trace:

Starting new trial
Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py", line 105, in build
    model = self.hypermodel.build(hp)
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py", line 65, in _build_wrapper
    return self._build(hp, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/autokeras/graph.py", line 235, in build
    outputs = block.build(hp, inputs=temp_inputs)
  File "/usr/local/lib/python3.6/dist-packages/autokeras/engine/block.py", line 34, in _build_wrapper
    return super()._build_wrapper(hp, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py", line 65, in _build_wrapper
    return self._build(hp, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/autokeras/blocks/heads.py", line 82, in build
    output_node = reduction.SpatialReduction().build(hp, output_node)
  File "/usr/local/lib/python3.6/dist-packages/autokeras/engine/block.py", line 34, in _build_wrapper
    return super()._build_wrapper(hp, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py", line 65, in _build_wrapper
    return self._build(hp, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/autokeras/blocks/reduction.py", line 106, in build
    default='global_avg')
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hyperparameters.py", line 691, in Choice
    return self._retrieve(hp)
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hyperparameters.py", line 619, in _retrieve
    return self.values[hp.name]
KeyError: 'classification_head_1/spatial_reduction_1/reduction_type'
[Warning] Invalid model 0/5
Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py", line 105, in build
    model = self.hypermodel.build(hp)
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py", line 65, in _build_wrapper
    return self._build(hp, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/autokeras/graph.py", line 235, in build
    outputs = block.build(hp, inputs=temp_inputs)
  File "/usr/local/lib/python3.6/dist-packages/autokeras/engine/block.py", line 34, in _build_wrapper
    return super()._build_wrapper(hp, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py", line 65, in _build_wrapper
    return self._build(hp, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/autokeras/blocks/heads.py", line 82, in build
    output_node = reduction.SpatialReduction().build(hp, output_node)
  File "/usr/local/lib/python3.6/dist-packages/autokeras/engine/block.py", line 34, in _build_wrapper
    return super()._build_wrapper(hp, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py", line 65, in _build_wrapper
    return self._build(hp, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/autokeras/blocks/reduction.py", line 106, in build
    default='global_avg')
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hyperparameters.py", line 691, in Choice
    return self._retrieve(hp)
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hyperparameters.py", line 619, in _retrieve
    return self.values[hp.name]
KeyError: 'classification_head_1/spatial_reduction_1/reduction_type'
[Warning] Invalid model 1/5
Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py", line 105, in build
    model = self.hypermodel.build(hp)
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py", line 65, in _build_wrapper
    return self._build(hp, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/autokeras/graph.py", line 235, in build
    outputs = block.build(hp, inputs=temp_inputs)
  File "/usr/local/lib/python3.6/dist-packages/autokeras/engine/block.py", line 34, in _build_wrapper
    return super()._build_wrapper(hp, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py", line 65, in _build_wrapper
    return self._build(hp, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/autokeras/blocks/heads.py", line 82, in build
    output_node = reduction.SpatialReduction().build(hp, output_node)
  File "/usr/local/lib/python3.6/dist-packages/autokeras/engine/block.py", line 34, in _build_wrapper
    return super()._build_wrapper(hp, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py", line 65, in _build_wrapper
    return self._build(hp, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/autokeras/blocks/reduction.py", line 106, in build
    default='global_avg')
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hyperparameters.py", line 691, in Choice
    return self._retrieve(hp)
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hyperparameters.py", line 619, in _retrieve
    return self.values[hp.name]
KeyError: 'classification_head_1/spatial_reduction_1/reduction_type'
[Warning] Invalid model 2/5
Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py", line 105, in build
    model = self.hypermodel.build(hp)
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py", line 65, in _build_wrapper
    return self._build(hp, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/autokeras/graph.py", line 235, in build
    outputs = block.build(hp, inputs=temp_inputs)
  File "/usr/local/lib/python3.6/dist-packages/autokeras/engine/block.py", line 34, in _build_wrapper
    return super()._build_wrapper(hp, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py", line 65, in _build_wrapper
    return self._build(hp, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/autokeras/blocks/heads.py", line 82, in build
    output_node = reduction.SpatialReduction().build(hp, output_node)
  File "/usr/local/lib/python3.6/dist-packages/autokeras/engine/block.py", line 34, in _build_wrapper
    return super()._build_wrapper(hp, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py", line 65, in _build_wrapper
    return self._build(hp, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/autokeras/blocks/reduction.py", line 106, in build
    default='global_avg')
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hyperparameters.py", line 691, in Choice
    return self._retrieve(hp)
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hyperparameters.py", line 619, in _retrieve
    return self.values[hp.name]
KeyError: 'classification_head_1/spatial_reduction_1/reduction_type'
[Warning] Invalid model 3/5
Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py", line 105, in build
    model = self.hypermodel.build(hp)
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py", line 65, in _build_wrapper
    return self._build(hp, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/autokeras/graph.py", line 235, in build
    outputs = block.build(hp, inputs=temp_inputs)
  File "/usr/local/lib/python3.6/dist-packages/autokeras/engine/block.py", line 34, in _build_wrapper
    return super()._build_wrapper(hp, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py", line 65, in _build_wrapper
    return self._build(hp, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/autokeras/blocks/heads.py", line 82, in build
    output_node = reduction.SpatialReduction().build(hp, output_node)
  File "/usr/local/lib/python3.6/dist-packages/autokeras/engine/block.py", line 34, in _build_wrapper
    return super()._build_wrapper(hp, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py", line 65, in _build_wrapper
    return self._build(hp, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/autokeras/blocks/reduction.py", line 106, in build
    default='global_avg')
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hyperparameters.py", line 691, in Choice
    return self._retrieve(hp)
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hyperparameters.py", line 619, in _retrieve
    return self.values[hp.name]
KeyError: 'classification_head_1/spatial_reduction_1/reduction_type'
[Warning] Invalid model 4/5
Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py", line 105, in build
    model = self.hypermodel.build(hp)
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py", line 65, in _build_wrapper
    return self._build(hp, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/autokeras/graph.py", line 235, in build
    outputs = block.build(hp, inputs=temp_inputs)
  File "/usr/local/lib/python3.6/dist-packages/autokeras/engine/block.py", line 34, in _build_wrapper
    return super()._build_wrapper(hp, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py", line 65, in _build_wrapper
    return self._build(hp, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/autokeras/blocks/heads.py", line 82, in build
    output_node = reduction.SpatialReduction().build(hp, output_node)
  File "/usr/local/lib/python3.6/dist-packages/autokeras/engine/block.py", line 34, in _build_wrapper
    return super()._build_wrapper(hp, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py", line 65, in _build_wrapper
    return self._build(hp, *args, **kwargs)
  File "/usr/local/lib/python3.6/dist-packages/autokeras/blocks/reduction.py", line 106, in build
    default='global_avg')
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hyperparameters.py", line 691, in Choice
    return self._retrieve(hp)
  File "/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hyperparameters.py", line 619, in _retrieve
    return self.values[hp.name]
KeyError: 'classification_head_1/spatial_reduction_1/reduction_type'
[Warning] Invalid model 5/5
---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py in build(self, hp)
    104                 with maybe_distribute(self.distribution_strategy):
--> 105                     model = self.hypermodel.build(hp)
    106             except:

17 frames
KeyError: 'classification_head_1/spatial_reduction_1/reduction_type'

During handling of the above exception, another exception occurred:

RuntimeError                              Traceback (most recent call last)
/usr/local/lib/python3.6/dist-packages/kerastuner/engine/hypermodel.py in build(self, hp)
    113                 if i == self._max_fail_streak:
    114                     raise RuntimeError(
--> 115                         'Too many failed attempts to build model.')
    116                 continue
    117 

RuntimeError: Too many failed attempts to build model.

How can I resolve this?

Issue Analytics

  • State:closed
  • Created 3 years ago
  • Comments:12 (3 by maintainers)

github_iconTop GitHub Comments

1reaction
dahlocommented, Jul 19, 2020

@castrovictor Sure thing. I’m running using the following Dockerfile:

FROM nvidia/cuda:10.1-cudnn7-devel-ubuntu18.04

# install apt packages
RUN apt update && apt upgrade -y && apt install -y \
        curl \
        git \
        python3 \
        python3-pip \
        vim \
        wget

# install pip packages
RUN pip3 install --no-cache-dir -U pip
RUN pip3 install --no-cache-dir -U setuptools six
RUN pip3 install --no-cache-dir \
        scipy==1.4.1 \
        tensorflow-gpu==2.2.0 \
        git+https://github.com/keras-team/autokeras.git@7db2afd \
        git+https://github.com/keras-team/keras-tuner.git@fa84eb2

# clean the cache
RUN rm -rf /var/lib/apt/lists/* && rm -rf ~/.cache/pip/*

Running pip3 freeze inside the container gives the following:

$ pip3 freeze 
absl-py==0.9.0
asn1crypto==0.24.0
astunparse==1.6.3
autokeras @ git+https://github.com/keras-team/autokeras.git@7db2afde4af83ca113841a979e218d775a04eb40
backcall==0.2.0
cachetools==4.1.1
certifi==2020.6.20
chardet==3.0.4
colorama==0.4.3
cryptography==2.1.4
decorator==4.4.2
future==0.18.2
gast==0.3.3
google-auth==1.19.2
google-auth-oauthlib==0.4.1
google-pasta==0.2.0
grpcio==1.30.0
h5py==2.10.0
idna==2.6
importlib-metadata==1.7.0
ipython==7.16.1
ipython-genutils==0.2.0
jedi==0.17.2
joblib==0.16.0
Keras-Preprocessing==1.1.2
keras-tuner @ git+https://github.com/keras-team/keras-tuner.git@fa84eb29446f6234aea243a73cef85de4bbdb642
keyring==10.6.0
keyrings.alt==3.0
Markdown==3.2.2
numpy==1.19.0
oauthlib==3.1.0
opt-einsum==3.2.1
packaging==20.4
pandas==1.0.5
parso==0.7.0
pexpect==4.8.0
pickleshare==0.7.5
prompt-toolkit==3.0.5
protobuf==3.12.2
ptyprocess==0.6.0
pyasn1==0.4.8
pyasn1-modules==0.2.8
pycrypto==2.6.1
Pygments==2.6.1
pygobject==3.26.1
pyparsing==2.4.7
python-dateutil==2.8.1
pytz==2020.1
pyxdg==0.25
requests==2.24.0
requests-oauthlib==1.3.0
rsa==4.6
scikit-learn==0.23.1
scipy==1.4.1
SecretStorage==2.3.1
six==1.15.0
tabulate==0.8.7
tensorboard==2.2.2
tensorboard-plugin-wit==1.7.0
tensorflow==2.2.0
tensorflow-estimator==2.2.0
tensorflow-gpu==2.2.0
termcolor==1.1.0
terminaltables==3.1.0
threadpoolctl==2.1.0
tqdm==4.48.0
traitlets==4.3.3
urllib3==1.25.9
wcwidth==0.2.5
Werkzeug==1.0.1
wrapt==1.12.1
zipp==3.1.0

and python version:

$ python3 --version
Python 3.6.9
0reactions
castrovictorcommented, Jul 19, 2020

@dahlo would you mind posting your configuration? Installing the versions you mention I get this error:

ImportError: dlopen: cannot load any more object with static TLS

Contents of /mnt/sdd/vicastro/envs/ak4/lib/python3.8/site-packages/sklearn/__check_build: pycache setup.py _check_build.cpython-38-x86_64-linux-gnu.so init.py

It seems that scikit-learn has not been built correctly.

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