diviyank
commented
6 years ago Closed diviyank closed 6 years ago
diviyank
commented
6 years ago diviyank
commented
6 years ago Fix done but auto-detection of GPU is not done when $CUDA_VISIBLE_DEVICES is not set. Might have to go through nvcc or nvidia-smi.
snowde
commented
6 years ago 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
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=
[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
[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=
[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
[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=
[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
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=
[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
[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=
[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
[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=
[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'
During handling of the above exception, another exception occurred:
JoblibAttributeError Traceback (most recent call last)
at 0x10f262a50, file "/Use...3.6/site-packages/ipykernel/__main__.py", line 1>, run_globals={'__annotations__': {}, '__builtins__': , '__cached__': '/Users/dereksnow/anaconda/envs/py36/lib/python3....ges/ipykernel/__pycache__/__main__.cpython-36.pyc', '__doc__': None, '__file__': '/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py', '__loader__': <_frozen_importlib_external.SourceFileLoader object>, '__name__': '__main__', '__package__': 'ipykernel', '__spec__': ModuleSpec(name='ipykernel.__main__', loader=<_f...b/python3.6/site-packages/ipykernel/__main__.py'), 'app': }, init_globals=None, mod_name='__main__', mod_spec=ModuleSpec(name='ipykernel.__main__', loader=<_f...b/python3.6/site-packages/ipykernel/__main__.py'), pkg_name='ipykernel', script_name=None)
80 __cached__ = cached,
81 __doc__ = None,
82 __loader__ = loader,
83 __package__ = pkg_name,
84 __spec__ = mod_spec)
---> 85 exec(code, run_globals)
code = at 0x10f262a50, file "/Use...3.6/site-packages/ipykernel/__main__.py", line 1>
run_globals = {'__annotations__': {}, '__builtins__': , '__cached__': '/Users/dereksnow/anaconda/envs/py36/lib/python3....ges/ipykernel/__pycache__/__main__.cpython-36.pyc', '__doc__': None, '__file__': '/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py', '__loader__': <_frozen_importlib_external.SourceFileLoader object>, '__name__': '__main__', '__package__': 'ipykernel', '__spec__': ModuleSpec(name='ipykernel.__main__', loader=<_f...b/python3.6/site-packages/ipykernel/__main__.py'), 'app': }
86 return run_globals
87
88 def _run_module_code(code, init_globals=None,
89 mod_name=None, mod_spec=None,
...........................................................................
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/__main__.py in ()
1 if __name__ == '__main__':
2 from ipykernel import kernelapp as app
----> 3 app.launch_new_instance()
...........................................................................
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/traitlets/config/application.py in launch_instance(cls=, argv=None, **kwargs={})
653
654 If a global instance already exists, this reinitializes and starts it
655 """
656 app = cls.instance(**kwargs)
657 app.initialize(argv)
--> 658 app.start()
app.start = >
659
660 #-----------------------------------------------------------------------------
661 # utility functions, for convenience
662 #-----------------------------------------------------------------------------
...........................................................................
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/kernelapp.py in start(self=)
472 return self.subapp.start()
473 if self.poller is not None:
474 self.poller.start()
475 self.kernel.start()
476 try:
--> 477 ioloop.IOLoop.instance().start()
478 except KeyboardInterrupt:
479 pass
480
481 launch_new_instance = IPKernelApp.launch_instance
...........................................................................
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/tornado/ioloop.py in start(self=)
883 self._events.update(event_pairs)
884 while self._events:
885 fd, events = self._events.popitem()
886 try:
887 fd_obj, handler_func = self._handlers[fd]
--> 888 handler_func(fd_obj, events)
handler_func = .null_wrapper>
fd_obj =
events = 1
889 except (OSError, IOError) as e:
890 if errno_from_exception(e) == errno.EPIPE:
891 # Happens when the client closes the connection
892 pass
...........................................................................
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/tornado/stack_context.py in null_wrapper(*args=(, 1), **kwargs={})
272 # Fast path when there are no active contexts.
273 def null_wrapper(*args, **kwargs):
274 try:
275 current_state = _state.contexts
276 _state.contexts = cap_contexts[0]
--> 277 return fn(*args, **kwargs)
args = (, 1)
kwargs = {}
278 finally:
279 _state.contexts = current_state
280 null_wrapper._wrapped = True
281 return null_wrapper
...........................................................................
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py in _handle_events(self=, fd=, events=1)
445 return
446 zmq_events = self.socket.EVENTS
447 try:
448 # dispatch events:
449 if zmq_events & zmq.POLLIN and self.receiving():
--> 450 self._handle_recv()
self._handle_recv = >
451 if not self.socket:
452 return
453 if zmq_events & zmq.POLLOUT and self.sending():
454 self._handle_send()
...........................................................................
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py in _handle_recv(self=)
475 else:
476 raise
477 else:
478 if self._recv_callback:
479 callback = self._recv_callback
--> 480 self._run_callback(callback, msg)
self._run_callback = >
callback = .null_wrapper>
msg = [, , , , , , ]
481
482
483 def _handle_send(self):
484 """Handle a send event."""
...........................................................................
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py in _run_callback(self=, callback=.null_wrapper>, *args=([, , , , , , ],), **kwargs={})
427 close our socket."""
428 try:
429 # Use a NullContext to ensure that all StackContexts are run
430 # inside our blanket exception handler rather than outside.
431 with stack_context.NullContext():
--> 432 callback(*args, **kwargs)
callback = .null_wrapper>
args = ([, , , , , , ],)
kwargs = {}
433 except:
434 gen_log.error("Uncaught exception in ZMQStream callback",
435 exc_info=True)
436 # Re-raise the exception so that IOLoop.handle_callback_exception
...........................................................................
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/tornado/stack_context.py in null_wrapper(*args=([, , , , , , ],), **kwargs={})
272 # Fast path when there are no active contexts.
273 def null_wrapper(*args, **kwargs):
274 try:
275 current_state = _state.contexts
276 _state.contexts = cap_contexts[0]
--> 277 return fn(*args, **kwargs)
args = ([, , , , , , ],)
kwargs = {}
278 finally:
279 _state.contexts = current_state
280 null_wrapper._wrapped = True
281 return null_wrapper
...........................................................................
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/kernelbase.py in dispatcher(msg=[, , , , , , ])
278 if self.control_stream:
279 self.control_stream.on_recv(self.dispatch_control, copy=False)
280
281 def make_dispatcher(stream):
282 def dispatcher(msg):
--> 283 return self.dispatch_shell(stream, msg)
msg = [, , , , , , ]
284 return dispatcher
285
286 for s in self.shell_streams:
287 s.on_recv(make_dispatcher(s), copy=False)
...........................................................................
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/kernelbase.py in dispatch_shell(self=, stream=, msg={'buffers': [], 'content': {'allow_stdin': True, 'code': "# So the question is, if you only have the data ...s\npd.DataFrame(list(ugraph.edges(data='weight')))", 'silent': False, 'stop_on_error': True, 'store_history': True, 'user_expressions': {}}, 'header': {'date': datetime.datetime(2018, 6, 30, 4, 19, 48, 623932, tzinfo=tzutc()), 'msg_id': '3F664F4DF8994E9980115EFD76A70918', 'msg_type': 'execute_request', 'session': '1DCE294733F74AD0BBF17671DE4E5820', 'username': 'username', 'version': '5.2'}, 'metadata': {}, 'msg_id': '3F664F4DF8994E9980115EFD76A70918', 'msg_type': 'execute_request', 'parent_header': {}})
230 self.log.warn("Unknown message type: %r", msg_type)
231 else:
232 self.log.debug("%s: %s", msg_type, msg)
233 self.pre_handler_hook()
234 try:
--> 235 handler(stream, idents, msg)
handler = >
stream =
idents = [b'1DCE294733F74AD0BBF17671DE4E5820']
msg = {'buffers': [], 'content': {'allow_stdin': True, 'code': "# So the question is, if you only have the data ...s\npd.DataFrame(list(ugraph.edges(data='weight')))", 'silent': False, 'stop_on_error': True, 'store_history': True, 'user_expressions': {}}, 'header': {'date': datetime.datetime(2018, 6, 30, 4, 19, 48, 623932, tzinfo=tzutc()), 'msg_id': '3F664F4DF8994E9980115EFD76A70918', 'msg_type': 'execute_request', 'session': '1DCE294733F74AD0BBF17671DE4E5820', 'username': 'username', 'version': '5.2'}, 'metadata': {}, 'msg_id': '3F664F4DF8994E9980115EFD76A70918', 'msg_type': 'execute_request', 'parent_header': {}}
236 except Exception:
237 self.log.error("Exception in message handler:", exc_info=True)
238 finally:
239 self.post_handler_hook()
...........................................................................
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/kernelbase.py in execute_request(self=, stream=, ident=[b'1DCE294733F74AD0BBF17671DE4E5820'], parent={'buffers': [], 'content': {'allow_stdin': True, 'code': "# So the question is, if you only have the data ...s\npd.DataFrame(list(ugraph.edges(data='weight')))", 'silent': False, 'stop_on_error': True, 'store_history': True, 'user_expressions': {}}, 'header': {'date': datetime.datetime(2018, 6, 30, 4, 19, 48, 623932, tzinfo=tzutc()), 'msg_id': '3F664F4DF8994E9980115EFD76A70918', 'msg_type': 'execute_request', 'session': '1DCE294733F74AD0BBF17671DE4E5820', 'username': 'username', 'version': '5.2'}, 'metadata': {}, 'msg_id': '3F664F4DF8994E9980115EFD76A70918', 'msg_type': 'execute_request', 'parent_header': {}})
394 if not silent:
395 self.execution_count += 1
396 self._publish_execute_input(code, parent, self.execution_count)
397
398 reply_content = self.do_execute(code, silent, store_history,
--> 399 user_expressions, allow_stdin)
user_expressions = {}
allow_stdin = True
400
401 # Flush output before sending the reply.
402 sys.stdout.flush()
403 sys.stderr.flush()
...........................................................................
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/ipkernel.py in do_execute(self=, code="# So the question is, if you only have the data ...s\npd.DataFrame(list(ugraph.edges(data='weight')))", silent=False, store_history=True, user_expressions={}, allow_stdin=True)
191
192 self._forward_input(allow_stdin)
193
194 reply_content = {}
195 try:
--> 196 res = shell.run_cell(code, store_history=store_history, silent=silent)
res = undefined
shell.run_cell = >
code = "# So the question is, if you only have the data ...s\npd.DataFrame(list(ugraph.edges(data='weight')))"
store_history = True
silent = False
197 finally:
198 self._restore_input()
199
200 if res.error_before_exec is not None:
...........................................................................
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/ipykernel/zmqshell.py in run_cell(self=, *args=("# So the question is, if you only have the data ...s\npd.DataFrame(list(ugraph.edges(data='weight')))",), **kwargs={'silent': False, 'store_history': True})
528 )
529 self.payload_manager.write_payload(payload)
530
531 def run_cell(self, *args, **kwargs):
532 self._last_traceback = None
--> 533 return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
self.run_cell = >
args = ("# So the question is, if you only have the data ...s\npd.DataFrame(list(ugraph.edges(data='weight')))",)
kwargs = {'silent': False, 'store_history': True}
534
535 def _showtraceback(self, etype, evalue, stb):
536 # try to preserve ordering of tracebacks and print statements
537 sys.stdout.flush()
...........................................................................
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/IPython/core/interactiveshell.py in run_cell(self=, raw_cell="# So the question is, if you only have the data ...s\npd.DataFrame(list(ugraph.edges(data='weight')))", store_history=True, silent=False, shell_futures=True)
2723 self.displayhook.exec_result = result
2724
2725 # Execute the user code
2726 interactivity = "none" if silent else self.ast_node_interactivity
2727 has_raised = self.run_ast_nodes(code_ast.body, cell_name,
-> 2728 interactivity=interactivity, compiler=compiler, result=result)
interactivity = 'last_expr'
compiler =
2729
2730 self.last_execution_succeeded = not has_raised
2731 self.last_execution_result = result
2732
...........................................................................
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/IPython/core/interactiveshell.py in run_ast_nodes(self=, nodelist=[<_ast.ImportFrom object>, <_ast.Assign object>, <_ast.Assign object>, <_ast.Assign object>, <_ast.Expr object>, <_ast.Expr object>, <_ast.Expr object>, <_ast.Expr object>], cell_name='', interactivity='last', compiler=, result=)
2845
2846 try:
2847 for i, node in enumerate(to_run_exec):
2848 mod = ast.Module([node])
2849 code = compiler(mod, cell_name, "exec")
-> 2850 if self.run_code(code, result):
self.run_code = >
code = at 0x1a1f3f18a0, file "", line 8>
result =
2851 return True
2852
2853 for i, node in enumerate(to_run_interactive):
2854 mod = ast.Interactive([node])
...........................................................................
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/IPython/core/interactiveshell.py in run_code(self=, code_obj= at 0x1a1f3f18a0, file "", line 8>, result=)
2905 outflag = True # happens in more places, so it's easier as default
2906 try:
2907 try:
2908 self.hooks.pre_run_code_hook()
2909 #rprint('Running code', repr(code_obj)) # dbg
-> 2910 exec(code_obj, self.user_global_ns, self.user_ns)
code_obj = at 0x1a1f3f18a0, file "", line 8>
self.user_global_ns = {'FSGNN': , 'Fsgnn': , 'In': ['', '#Import libraries\nimport cdt\nfrom cdt import SET...pandas as pd\nfrom matplotlib import pyplot as plt', '#Import libraries\nimport cdt\nfrom cdt import SET...pandas as pd\nfrom matplotlib import pyplot as plt', '# Load data and graph solution\ndata = pd.read_cs...sualization of the graph. \nplt.show()\ndata.head()', 'solution', "# So the question is, if you only have the data ...s\npd.DataFrame(list(ugraph.edges(data='weight')))"], 'Out': {3: Allergy Anxiety Genetics Peer_Pressure ... -0.733240 -0.149308 0.854195 -0.633940 , 4: }, 'SETTINGS': , '_': , '_3': Allergy Anxiety Genetics Peer_Pressure ... -0.733240 -0.149308 0.854195 -0.633940 , '_4': , '__': Allergy Anxiety Genetics Peer_Pressure ... -0.733240 -0.149308 0.854195 -0.633940 , '___': '', ...}
self.user_ns = {'FSGNN': , 'Fsgnn': , 'In': ['', '#Import libraries\nimport cdt\nfrom cdt import SET...pandas as pd\nfrom matplotlib import pyplot as plt', '#Import libraries\nimport cdt\nfrom cdt import SET...pandas as pd\nfrom matplotlib import pyplot as plt', '# Load data and graph solution\ndata = pd.read_cs...sualization of the graph. \nplt.show()\ndata.head()', 'solution', "# So the question is, if you only have the data ...s\npd.DataFrame(list(ugraph.edges(data='weight')))"], 'Out': {3: Allergy Anxiety Genetics Peer_Pressure ... -0.733240 -0.149308 0.854195 -0.633940 , 4: }, 'SETTINGS': , '_': , '_3': Allergy Anxiety Genetics Peer_Pressure ... -0.733240 -0.149308 0.854195 -0.633940 , '_4': , '__': Allergy Anxiety Genetics Peer_Pressure ... -0.733240 -0.149308 0.854195 -0.633940 , '___': '', ...}
2911 finally:
2912 # Reset our crash handler in place
2913 sys.excepthook = old_excepthook
2914 except SystemExit as e:
...........................................................................
/Volumes/extra/FirmAI/Causal Inference/CausalDiscoveryToolbox-master/examples/ in ()
3 from cdt.independence.graph import FSGNN
4
5 Fsgnn = FSGNN()
6
7 start_time = time.time()
----> 8 ugraph = Fsgnn.predict(data, train_epochs=2000, test_epochs=1000, threshold=5e-4, l1=0.01)
9 print("--- Execution time : %4.4s seconds ---" % (time.time() - start_time))
10 nx.draw_networkx(ugraph, font_size=8) # The plot function allows for quick visualization of the graph.
11 plt.show()
12 # List results
...........................................................................
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/cdt/independence/graph/model.py in predict(self=, df_data= Allergy Anxiety Genetics Peer_Pressure...0.858699 -1.037579
[500 rows x 11 columns], threshold=0.0005, **kwargs={'l1': 0.01, 'test_epochs': 1000, 'train_epochs': 2000})
50 nb_jobs = kwargs.get("nb_jobs", SETTINGS.NB_JOBS)
51 list_nodes = list(df_data.columns.values)
52 if nb_jobs != 1:
53 result_feature_selection = Parallel(n_jobs=nb_jobs)(delayed(self.run_feature_selection)
54 (df_data, node, idx, **kwargs)
---> 55 for idx, node in enumerate(list_nodes))
idx = undefined
node = undefined
list_nodes = ['Allergy', 'Anxiety', 'Genetics', 'Peer_Pressure', 'Attention_Disorder', 'Smoking', 'Lung_Cancer', 'Yellow_Fingers', 'Coughing', 'Fatigue', 'Car_Accident']
56 else:
57 result_feature_selection = [self.run_feature_selection(df_data, node, idx, **kwargs) for idx, node in enumerate(list_nodes)]
58 for idx, i in enumerate(result_feature_selection):
59 try:
...........................................................................
/Users/dereksnow/anaconda/envs/py36/lib/python3.6/site-packages/joblib/parallel.py in __call__(self=Parallel(n_jobs=4), iterable=.>)
784 if pre_dispatch == "all" or n_jobs == 1:
785 # The iterable was consumed all at once by the above for loop.
786 # No need to wait for async callbacks to trigger to
787 # consumption.
788 self._iterating = False
--> 789 self.retrieve()
self.retrieve =
790 # Make sure that we get a last message telling us we are done
791 elapsed_time = time.time() - self._start_time
792 self._print('Done %3i out of %3i | elapsed: %s finished',
793 (len(self._output), len(self._output),
---------------------------------------------------------------------------
Sub-process traceback:
---------------------------------------------------------------------------
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=)
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 = [(>, ( 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=)
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 = >
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=, 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 = >
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=, 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=, 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'
___________________________________________________________________________`