Example #7

snowde · 2018-06-30T04:35:21Z

Hey man in trying your example, I have run into an error. I am not sure what to make of it, as it might be device related. I will include the message here and the file link.

https://github.com/snowde/firmai.github.io/blob/master/Discovery_LUCAS.ipynb


# So the question is, if you only have the data can you find the
# structure of the graph
from cdt.independence.graph import FSGNN

Fsgnn = FSGNN()

start_time = time.time()
ugraph = Fsgnn.predict(data, train_epochs=2000, test_epochs=1000, threshold=5e-4, l1=0.01)
print("--- Execution time : %4.4s seconds ---" % (time.time() - start_time))
nx.draw_networkx(ugraph, font_size=8) # The plot function allows for quick visualization of the graph.
plt.show()
# List results
pd.DataFrame(list(ugraph.edges(data='weight')))

`---------------------------------------------------------------------------
RemoteTraceback Traceback (most recent call last)
RemoteTraceback:
"""
Traceback (most recent call last):
File "/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/joblib/_parallel_backends.py", line 350, in call
return self.func(*args, **kwargs)
File "/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/joblib/parallel.py", line 131, in call
return [func(*args, **kwargs) for func, args, kwargs in self.items]
File "/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/joblib/parallel.py", line 131, in
return [func(*args, **kwargs) for func, args, kwargs in self.items]
File "/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/cdt/independence/graph/model.py", line 43, in run_feature_selection
return self.predict_features(df_features, df_target, **kwargs)
File "/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/cdt/independence/graph/FSGNN.py", line 79, in predict_features
x = th.FloatTensor(scale(df_features.as_matrix())).to(device)
AttributeError: 'torch.FloatTensor' object has no attribute 'to'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "/Users/dereksnow/anaconda/envs/py36/lib/python3.6/multiprocessing/pool.py", line 119, in worker
result = (True, func(*args, **kwds))
File "/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/joblib/_parallel_backends.py", line 359, in call
raise TransportableException(text, e_type)
joblib.my_exceptions.TransportableException: TransportableException

AttributeError Sat Jun 30 16:19:48 2018
PID: 92373 Python 3.6.3: /Users/dereksnow/anaconda/envs/py36/bin/python
...........................................................................
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/joblib/parallel.py in call(self=<joblib.parallel.BatchedCalls object>)
126 def init(self, iterator_slice):
127 self.items = list(iterator_slice)
128 self.size = len(self.items)
129
130 def call(self):
--> 131 return [func(*args, **kwargs) for func, args, kwargs in self.items]
self.items = [(<bound method FeatureSelectionModel.run_feature...n of <cdt.independence.graph.FSGNN.FSGNN object>>, ( Allergy Anxiety Genetics Peer_Pressure...0.858699 -1.037579

[500 rows x 11 columns], 'Allergy', 0), {'l1': 0.01, 'test_epochs': 1000, 'train_epochs': 2000})]
132
133 def len(self):
134 return self._size
135

...........................................................................
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/joblib/parallel.py in (.0=<list_iterator object>)
126 def init(self, iterator_slice):
127 self.items = list(iterator_slice)
128 self.size = len(self.items)
129
130 def call(self):
--> 131 return [func(*args, **kwargs) for func, args, kwargs in self.items]
func = <bound method FeatureSelectionModel.run_feature...n of <cdt.independence.graph.FSGNN.FSGNN object>>
args = ( Allergy Anxiety Genetics Peer_Pressure...0.858699 -1.037579

[500 rows x 11 columns], 'Allergy', 0)
kwargs = {'l1': 0.01, 'test_epochs': 1000, 'train_epochs': 2000}
132
133 def len(self):
134 return self._size
135

...........................................................................
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/cdt/independence/graph/model.py in run_feature_selection(self=<cdt.independence.graph.FSGNN.FSGNN object>, df_data= Allergy Anxiety Genetics Peer_Pressure...0.858699 -1.037579

[500 rows x 11 columns], target='Allergy', idx=0, **kwargs={'l1': 0.01, 'test_epochs': 1000, 'train_epochs': 2000})
38 list_features = list(df_data.columns.values)
39 list_features.remove(target)
40 df_target = pd.DataFrame(df_data[target], columns=[target])
41 df_features = df_data[list_features]
42
---> 43 return self.predict_features(df_features, df_target, **kwargs)
self.predict_features = <bound method FSGNN.predict_features of <cdt.independence.graph.FSGNN.FSGNN object>>
df_features = Anxiety Genetics Peer_Pressure Attentio...0.858699 -1.037579

[500 rows x 10 columns]
df_target = Allergy
0 -0.266076
1 -0.579084
2 -0...8 -0.064685
499 -0.638704

[500 rows x 1 columns]
kwargs = {'l1': 0.01, 'test_epochs': 1000, 'train_epochs': 2000}
44
45 def predict(self, df_data, threshold=0.05, **kwargs):
46 """Get the skeleton of the graph from raw data.
47

...........................................................................
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/cdt/independence/graph/FSGNN.py in predict_features(self=<cdt.independence.graph.FSGNN.FSGNN object>, df_features= Anxiety Genetics Peer_Pressure Attentio...0.858699 -1.037579

[500 rows x 10 columns], df_target= Allergy
0 -0.266076
1 -0.579084
2 -0...8 -0.064685
499 -0.638704

[500 rows x 1 columns], nh=20, idx=0, dropout=0.0, activation_function=<class 'torch.nn.modules.activation.ReLU'>, lr=0.01, l1=0.01, train_epochs=2000, test_epochs=1000, device='cpu', verbose=False, nb_runs=3)
74 activation_function=th.nn.ReLU, lr=0.01, l1=0.1, # batch_size=-1,
75 train_epochs=1000, test_epochs=1000, device=None,
76 verbose=None, nb_runs=3):
77 """For one variable, predict its neighbours."""
78 device, verbose = SETTINGS.get_default(('device', device), ('verbose', verbose))
---> 79 x = th.FloatTensor(scale(df_features.as_matrix())).to(device)
x = undefined
df_features.as_matrix.to = undefined
device = 'cpu'
80 y = th.FloatTensor(scale(df_target.as_matrix())).to(device)
81 out = []
82 for i in range(nb_runs):
83 model = FSGNN_model([x.size()[1], nh, 1],

AttributeError: 'torch.FloatTensor' object has no attribute 'to'

"""

The above exception was the direct cause of the following exception:

TransportableException Traceback (most recent call last)
~/anaconda/envs/py36/lib/python3.6/site-packages/joblib/parallel.py in retrieve(self)
698 if getattr(self._backend, 'supports_timeout', False):
--> 699 self._output.extend(job.get(timeout=self.timeout))
700 else:

~/anaconda/envs/py36/lib/python3.6/multiprocessing/pool.py in get(self, timeout)
643 else:
--> 644 raise self._value
645

TransportableException: TransportableException