In [1]:
%load_ext autoreload
%autoreload 2
from matplotlib.pyplot import imshow
import matplotlib.pyplot as plt
%matplotlib inline
import numpy as np
import sys
sys.path.append('../')
import gp
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/matplotlib/font_manager.py:273: UserWarning: Matplotlib is building the font cache using fc-list. This may take a moment.
warnings.warn('Matplotlib is building the font cache using fc-list. This may take a moment.')
INFO (theano.gof.compilelock): Waiting for existing lock by process '27726' (I am process '16778')
INFO (theano.gof.compilelock): To manually release the lock, delete /home/d/.theano/compiledir_Linux-4.2--generic-x86_64-with-debian-jessie-sid-x86_64-2.7.12-64/lock_dir
---------------------------------------------------------------------------
KeyboardInterrupt Traceback (most recent call last)
<ipython-input-1-2db8affa47eb> in <module>()
9 import sys
10 sys.path.append('../')
---> 11 import gp
/home/d/Projects/gp/gp/__init__.py in <module>()
3 import metrics
4 from patch import Patch
----> 5 from stats import Stats
6 from util import Util
/home/d/Projects/gp/gp/stats.py in <module>()
1 import collections
2 import cPickle as pickle
----> 3 import lasagne
4 import numpy as np
5 import os
/home/d/Projects/gp/src/lasagne/lasagne/__init__.py in <module>()
10 for Lasagne. See the installation docs for more details:
11 http://lasagne.readthedocs.org/en/latest/user/installation.html#theano"""
---> 12 import theano
13 except ImportError: # pragma: no cover
14 raise ImportError("Could not import Theano." + install_instr)
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/__init__.pyc in <module>()
101
102 if config.device.startswith('gpu') or config.init_gpu_device.startswith('gpu'):
--> 103 import theano.sandbox.cuda
104 # We can't test the driver during import of theano.sandbox.cuda as
105 # this cause circular import dependency. So we also test it manually
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/sandbox/cuda/__init__.py in <module>()
695 # import dependency. So we also test it in the file theano/__init__.py
696 if config.device.startswith('gpu'):
--> 697 use(device=config.device, force=config.force_device, test_driver=False)
698 elif config.init_gpu_device.startswith('gpu'):
699 assert config.device == "cpu", (
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/sandbox/cuda/__init__.py in use(device, force, default_to_move_computation_to_gpu, move_shared_float32_to_gpu, enable_cuda, test_driver)
580 warn = None
581 try:
--> 582 if dnn_available():
583 (hdr_v, runtime_v) = dnn_version()
584 cudnn_version = runtime_v
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/sandbox/cuda/__init__.py in dnn_available()
320 else:
321 # If we can compile, check that we can import and run.
--> 322 v = dnn_version()
323 if isinstance(v, tuple) and v[0] != v[1]:
324 dnn_available.avail = False
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/sandbox/cuda/__init__.py in dnn_version()
411 f = theano.function([], DnnVersion()(),
412 theano.Mode(optimizer=None),
--> 413 profile=False)
414 dnn_version.v = f()
415 return dnn_version.v
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/compile/function.pyc in function(inputs, outputs, mode, updates, givens, no_default_updates, accept_inplace, name, rebuild_strict, allow_input_downcast, profile, on_unused_input)
318 on_unused_input=on_unused_input,
319 profile=profile,
--> 320 output_keys=output_keys)
321 # We need to add the flag check_aliased inputs if we have any mutable or
322 # borrowed used defined inputs
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/compile/pfunc.pyc in pfunc(params, outputs, mode, updates, givens, no_default_updates, accept_inplace, name, rebuild_strict, allow_input_downcast, profile, on_unused_input, output_keys)
477 accept_inplace=accept_inplace, name=name,
478 profile=profile, on_unused_input=on_unused_input,
--> 479 output_keys=output_keys)
480
481
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/compile/function_module.pyc in orig_function(inputs, outputs, mode, accept_inplace, name, profile, on_unused_input, output_keys)
1775 on_unused_input=on_unused_input,
1776 output_keys=output_keys).create(
-> 1777 defaults)
1778
1779 t2 = time.time()
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/compile/function_module.pyc in create(self, input_storage, trustme, storage_map)
1639 theano.config.traceback.limit = 0
1640 _fn, _i, _o = self.linker.make_thunk(
-> 1641 input_storage=input_storage_lists, storage_map=storage_map)
1642 finally:
1643 theano.config.traceback.limit = limit_orig
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/gof/link.pyc in make_thunk(self, input_storage, output_storage, storage_map)
688 return self.make_all(input_storage=input_storage,
689 output_storage=output_storage,
--> 690 storage_map=storage_map)[:3]
691
692 def make_all(self, input_storage, output_storage):
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/gof/vm.pyc in make_all(self, profiler, input_storage, output_storage, storage_map)
1001 storage_map,
1002 compute_map,
-> 1003 no_recycling))
1004 if not hasattr(thunks[-1], 'lazy'):
1005 # We don't want all ops maker to think about lazy Ops.
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/sandbox/cuda/__init__.py in make_thunk(self, node, storage_map, compute_map, no_recycling)
254 enable_cuda=False)
255 return super(GpuOp, self).make_thunk(node, storage_map,
--> 256 compute_map, no_recycling)
257
258 theano.compile.debugmode.default_make_thunk.append(
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/gof/op.pyc in make_thunk(self, node, storage_map, compute_map, no_recycling)
968 try:
969 return self.make_c_thunk(node, storage_map, compute_map,
--> 970 no_recycling)
971 except (NotImplementedError, utils.MethodNotDefined):
972 logger.debug('Falling back on perform')
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/gof/op.pyc in make_c_thunk(self, node, storage_map, compute_map, no_recycling)
877 logger.debug('Trying CLinker.make_thunk')
878 outputs = cl.make_thunk(input_storage=node_input_storage,
--> 879 output_storage=node_output_storage)
880 fill_storage, node_input_filters, node_output_filters = outputs
881
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/gof/cc.pyc in make_thunk(self, input_storage, output_storage, storage_map, keep_lock)
1198 cthunk, in_storage, out_storage, error_storage = self.__compile__(
1199 input_storage, output_storage, storage_map,
-> 1200 keep_lock=keep_lock)
1201
1202 res = _CThunk(cthunk, init_tasks, tasks, error_storage)
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/gof/cc.pyc in __compile__(self, input_storage, output_storage, storage_map, keep_lock)
1141 output_storage,
1142 storage_map,
-> 1143 keep_lock=keep_lock)
1144 return (thunk,
1145 [link.Container(input, storage) for input, storage in
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/gof/cc.pyc in cthunk_factory(self, error_storage, in_storage, out_storage, storage_map, keep_lock)
1593 else:
1594 module = get_module_cache().module_from_key(
-> 1595 key=key, lnk=self, keep_lock=keep_lock)
1596
1597 vars = self.inputs + self.outputs + self.orphans
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/gof/cmodule.pyc in module_from_key(self, key, lnk, keep_lock)
1110 return module
1111
-> 1112 with compilelock.lock_ctx(keep_lock=keep_lock):
1113 # 1) Maybe somebody else compiled it for us while we
1114 # where waiting for the lock. Try to load it again.
/home/d/miniconda2/envs/NP/lib/python2.7/contextlib.pyc in __enter__(self)
15 def __enter__(self):
16 try:
---> 17 return self.gen.next()
18 except StopIteration:
19 raise RuntimeError("generator didn't yield")
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/gof/compilelock.pyc in lock_ctx(lock_dir, keep_lock, **kw)
36 @contextmanager
37 def lock_ctx(lock_dir=None, keep_lock=False, **kw):
---> 38 get_lock(lock_dir=lock_dir, **kw)
39 yield
40 if not keep_lock:
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/gof/compilelock.pyc in _get_lock(lock_dir, **kw)
82 # Only really try to acquire the lock if we do not have it already.
83 if get_lock.n_lock == 0:
---> 84 lock(get_lock.lock_dir, **kw)
85 atexit.register(Unlocker.unlock, get_lock.unlocker)
86 # Store time at which the lock was set.
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/gof/compilelock.pyc in lock(tmp_dir, timeout, min_wait, max_wait, verbosity)
269 no_display = True
270 nb_wait += 1
--> 271 time.sleep(random.uniform(min_wait, max_wait))
272
273 try:
KeyboardInterrupt:
In [2]:
e_p = []
p = []
In [3]:
import cPickle as pickle
with open('../nets/IPMLB_FULL.p', 'rb') as f:
cnn = pickle.load(f)
cnn.uuid = 'IPMLB'
---------------------------------------------------------------------------
KeyboardInterrupt Traceback (most recent call last)
<ipython-input-3-af2ea7676244> in <module>()
1 import cPickle as pickle
2 with open('../nets/IPMLB_FULL.p', 'rb') as f:
----> 3 cnn = pickle.load(f)
4 cnn.uuid = 'IPMLB'
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/compile/function_module.pyc in _constructor_Function(maker, input_storage, inputs_data)
1021 if not theano.config.unpickle_function:
1022 return None
-> 1023 f = maker.create(input_storage, trustme=True)
1024 assert len(f.input_storage) == len(inputs_data)
1025 for container, x in zip(f.input_storage, inputs_data):
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/compile/function_module.pyc in create(self, input_storage, trustme, storage_map)
1639 theano.config.traceback.limit = 0
1640 _fn, _i, _o = self.linker.make_thunk(
-> 1641 input_storage=input_storage_lists, storage_map=storage_map)
1642 finally:
1643 theano.config.traceback.limit = limit_orig
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/gof/link.pyc in make_thunk(self, input_storage, output_storage, storage_map)
688 return self.make_all(input_storage=input_storage,
689 output_storage=output_storage,
--> 690 storage_map=storage_map)[:3]
691
692 def make_all(self, input_storage, output_storage):
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/gof/vm.pyc in make_all(self, profiler, input_storage, output_storage, storage_map)
1001 storage_map,
1002 compute_map,
-> 1003 no_recycling))
1004 if not hasattr(thunks[-1], 'lazy'):
1005 # We don't want all ops maker to think about lazy Ops.
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/sandbox/cuda/__init__.pyc in make_thunk(self, node, storage_map, compute_map, no_recycling)
254 enable_cuda=False)
255 return super(GpuOp, self).make_thunk(node, storage_map,
--> 256 compute_map, no_recycling)
257
258 theano.compile.debugmode.default_make_thunk.append(
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/gof/op.pyc in make_thunk(self, node, storage_map, compute_map, no_recycling)
968 try:
969 return self.make_c_thunk(node, storage_map, compute_map,
--> 970 no_recycling)
971 except (NotImplementedError, utils.MethodNotDefined):
972 logger.debug('Falling back on perform')
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/gof/op.pyc in make_c_thunk(self, node, storage_map, compute_map, no_recycling)
877 logger.debug('Trying CLinker.make_thunk')
878 outputs = cl.make_thunk(input_storage=node_input_storage,
--> 879 output_storage=node_output_storage)
880 fill_storage, node_input_filters, node_output_filters = outputs
881
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/gof/cc.pyc in make_thunk(self, input_storage, output_storage, storage_map, keep_lock)
1198 cthunk, in_storage, out_storage, error_storage = self.__compile__(
1199 input_storage, output_storage, storage_map,
-> 1200 keep_lock=keep_lock)
1201
1202 res = _CThunk(cthunk, init_tasks, tasks, error_storage)
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/gof/cc.pyc in __compile__(self, input_storage, output_storage, storage_map, keep_lock)
1141 output_storage,
1142 storage_map,
-> 1143 keep_lock=keep_lock)
1144 return (thunk,
1145 [link.Container(input, storage) for input, storage in
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/gof/cc.pyc in cthunk_factory(self, error_storage, in_storage, out_storage, storage_map, keep_lock)
1593 else:
1594 module = get_module_cache().module_from_key(
-> 1595 key=key, lnk=self, keep_lock=keep_lock)
1596
1597 vars = self.inputs + self.outputs + self.orphans
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/gof/cmodule.pyc in module_from_key(self, key, lnk, keep_lock)
1140 try:
1141 location = dlimport_workdir(self.dirname)
-> 1142 module = lnk.compile_cmodule(location)
1143 name = module.__file__
1144 assert name.startswith(location)
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/gof/cc.pyc in compile_cmodule(self, location)
1504 lib_dirs=self.lib_dirs(),
1505 libs=libs,
-> 1506 preargs=preargs)
1507 except Exception as e:
1508 e.args += (str(self.fgraph),)
/home/d/miniconda2/envs/NP/lib/python2.7/site-packages/theano/sandbox/cuda/nvcc_compiler.pyc in compile_str(module_name, src_code, location, include_dirs, lib_dirs, libs, preargs, rpaths, py_module, hide_symbols)
360 p = subprocess.Popen(
361 cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
--> 362 nvcc_stdout, nvcc_stderr = decode_iter(p.communicate()[:2])
363 finally:
364 os.chdir(orig_dir)
/home/d/miniconda2/envs/NP/lib/python2.7/subprocess.pyc in communicate(self, input)
798 return (stdout, stderr)
799
--> 800 return self._communicate(input)
801
802
/home/d/miniconda2/envs/NP/lib/python2.7/subprocess.pyc in _communicate(self, input)
1415
1416 if _has_poll:
-> 1417 stdout, stderr = self._communicate_with_poll(input)
1418 else:
1419 stdout, stderr = self._communicate_with_select(input)
/home/d/miniconda2/envs/NP/lib/python2.7/subprocess.pyc in _communicate_with_poll(self, input)
1469 while fd2file:
1470 try:
-> 1471 ready = poller.poll()
1472 except select.error, e:
1473 if e.args[0] == errno.EINTR:
KeyboardInterrupt: (KeyboardInterrupt(), <function _constructor_Function at 0x7f59b8e81848>, (<theano.compile.function_module.FunctionMaker object at 0x7f596e55f050>, [<None>, <None>, <CudaNdarray([[[[ 0.83101124 -0.45216268 -0.92241758]
[ 0.44926044 -0.79137021 -0.85471934]
[ 0.62316829 -0.22166604 -0.5351423 ]]
[[ 0.74415201 0.76112461 0.14936428]
[ 1.26601923 1.12129915 0.54457217]
[ 0.73289531 0.6029588 0.08996633]]
[[-0.20223477 -0.05420067 -0.5176177 ]
[-0.16366521 0.24429148 0.12103456]
[ 0.43135822 0.11404235 0.20076309]]
[[ 0.01085452 -0.14073524 0.35528407]
[ 0.1014398 -0.21538898 -0.13963255]
[-0.17260572 0.19859107 0.22175764]]]
[[[-0.42160168 -0.33796558 -0.10554801]
[-0.55112571 -0.89287311 -0.78223509]
[-0.5099296 -0.8778429 -1.06378591]]
[[-0.62700075 -0.55552375 -0.26756749]
[-0.1141824 -0.10648482 -0.13077492]
[ 0.03338762 0.01803556 0.15733203]]
[[-0.28123182 0.08279371 0.06133154]
[-0.26863402 -0.42603293 0.01725472]
[ 0.3666476 -0.98386133 -0.54569435]]
[[-0.13484271 -0.26526099 0.2911244 ]
[ 0.42529172 0.04707859 -0.48821592]
[ 0.33630458 0.67504847 0.016005 ]]]
[[[ 1.25536573 1.61147332 1.61617768]
[-0.24261695 0.25609356 0.25410226]
[-1.48116505 -1.34126687 -0.99922913]]
[[ 0.44626012 0.21863577 0.56172657]
[-0.30303037 -0.54896152 -0.37504318]
[-0.06397472 -0.29694691 -0.4180465 ]]
[[-0.47834331 -0.21126686 0.49019 ]
[-0.84692895 0.37767103 0.10543503]
[-0.61730427 0.64444244 0.62144709]]
[[ 0.05778688 0.1833781 -0.08520789]
[ 0.57905042 0.06180374 0.47970474]
[ 0.34884197 -0.1029463 0.36515298]]]
...,
[[[-0.07212126 0.41497627 0.32952008]
[ 0.04437019 0.89016879 0.54262209]
[-0.09697887 0.26709726 -0.0759009 ]]
[[-0.34860247 -0.3188796 -0.0791292 ]
[-0.20706786 -0.51325405 -0.45413423]
[ 0.49233451 0.18315828 -0.11095257]]
[[ 0.30043569 0.13640419 -0.07883039]
[ 0.09435701 -0.06755543 -0.10842759]
[-0.22471718 0.11327182 0.12290932]]
[[ 0.85377574 0.54417753 0.2029732 ]
[-0.3245388 -0.04117646 0.41804892]
[ 0.45198494 0.05717055 0.64358526]]]
[[[ 0.27808616 -0.05840755 -0.99811262]
[ 0.91650122 0.59587646 -0.42878583]
[ 1.38801038 0.84957308 -0.27346233]]
[[-0.30557671 0.67243505 1.05331039]
[-0.75939018 0.08055729 0.8877579 ]
[-0.99525791 -0.68197203 0.3973839 ]]
[[-0.46158257 0.79644388 0.22149633]
[-1.11750543 -0.05984045 -0.88105267]
[ 1.00280964 0.97050434 0.44936067]]
[[ 0.03072515 0.42680386 -0.50137824]
[-0.43645719 -0.27598628 -0.25353488]
[ 0.73373896 -0.48743752 0.14143114]]]
[[[-0.29113311 -0.2968657 -0.76124632]
[-0.41352701 -0.20361485 -0.76195771]
[-0.37231886 -0.47130078 -0.59065205]]
[[-0.4317973 -0.30489215 -0.16632286]
[ 0.19728214 0.07837477 0.30107018]
[ 0.47553018 0.43354931 0.45248222]]
[[-0.19242385 -0.02724457 0.59242481]
[-0.08976278 -0.04668926 -0.17313901]
[-0.51755637 -0.39758518 -0.17454609]]
[[ 0.24901141 -0.17936386 -0.91408461]
[ 0.25167441 -0.33444363 0.00344374]
[ 0.02630736 0.04460052 -0.24195156]]]])>, <CudaNdarray([-2.74057388 -1.13451767 -0.69347119 -0.65855223 -1.45420063 -1.3963747
-2.58478141 -0.86258739 -1.56950152 -2.0154295 -0.83600777 -1.19224346
-1.30910766 -1.30014694 -1.0975548 -1.19868994 -1.06602192 -1.18646228
-0.86395139 -1.08066916 -1.09416664 -1.34036589 -0.67637753 -1.17393482
-1.296646 -1.93042874 -2.02995753 -1.09843004 -0.55103594 -3.11809063
-2.84745932 -1.39242232 -1.19986606 -0.82428789 -1.02349043 -6.47628355
-1.57731855 -1.24140286 -1.23123968 -2.36973405 -3.52481961 -1.45581758
-3.06090808 -0.98896873 -0.66302234 -1.20765138 -0.81468683 -1.02941835
-2.59137821 -1.0085454 -1.76855326 -1.561041 -2.17170954 -0.9072175
-1.88578737 -1.28662634 -1.43275952 -0.84804511 -1.40974557 -1.03664601
-3.44133472 -0.92853475 -1.34622431 -1.69780052])>, <CudaNdarray([[[[ -1.03899086e+00 -7.07712948e-01 -2.11633012e-01]
[ -7.01015055e-01 -5.49534857e-01 -4.23155546e-01]
[ -4.74046022e-01 -6.90073490e-01 -3.20720673e-01]]
[[ -2.84042004e-02 7.65760913e-02 1.68639973e-01]
[ 1.55218923e-02 -5.14774360e-02 1.02452047e-01]
[ -1.79808512e-01 1.20908879e-02 1.63017139e-01]]
[[ 3.20427001e-01 1.84102327e-01 -7.90930837e-02]
[ -9.83949155e-02 -7.94056952e-02 4.98850755e-02]
[ 8.11649710e-02 -3.69171977e-01 1.64390311e-01]]
...,
[[ -8.31661522e-02 3.43939334e-01 -7.62134641e-02]
[ -1.26789913e-01 7.70685002e-02 1.37099728e-01]
[ -2.34002825e-02 -7.41033182e-02 -4.06539366e-02]]
[[ 8.17659050e-02 3.09216175e-02 2.24263132e-01]
[ 1.50205746e-01 -1.83322132e-01 2.37460360e-02]
[ 9.91108567e-02 4.93976139e-02 -2.59389788e-01]]
[[ 9.94211063e-02 -1.39090121e-01 1.03914693e-01]
[ -3.89624611e-02 -2.44604453e-01 1.40192807e-01]
[ -1.02255931e-02 -1.08521447e-01 -5.45864552e-02]]]
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[-0.03578002 0.24260777 0.19972987]]
[[-0.07895266 0.19871186 0.05674917]
[ 0.06790239 -0.0385462 -0.24463423]
[ 0.01233307 -0.45919096 -0.24354298]]
[[ 0.19116873 0.09023892 0.08200169]
[-0.27167848 -0.07721376 -0.13123474]
[ 0.2535713 0.14867975 -0.23826264]]]
[[[ 0.19106571 0.02854091 0.06139765]
[ 0.30297297 0.14660056 -0.07580548]
[ 0.21287966 -0.08717956 0.26693073]]
[[-0.55640596 -0.66656661 -0.66886538]
[ 0.04251923 -0.4210366 0.19398862]
[ 0.23728853 0.22951351 0.16600609]]
[[ 0.25252715 -0.07036147 -0.01103672]
[-0.01437161 -0.08905008 -0.15794489]
[ 0.06510416 -0.20819385 -0.23607792]]
...,
[[-0.11612321 0.197984 -0.06423724]
[ 0.04049082 0.20648503 0.23354927]
[ 0.06491268 -0.11354759 -0.0466683 ]]
[[ 0.0721854 -0.1971247 -0.02225072]
[-0.32230574 -0.32425833 0.42623046]
[-0.75231457 -0.25579238 0.28591195]]
[[ 0.15298374 0.04932999 0.34639147]
[ 0.17260227 0.03551251 0.05287162]
[ 0.15045966 -0.17068471 -0.40324107]]]
[[[-0.15075611 0.11353582 0.07292648]
[-0.34331554 -0.06689552 -0.1733899 ]
[-0.15645373 -0.31936792 -0.2078416 ]]
[[-0.08005071 -0.13809991 -0.12880091]
[ 0.06236064 -0.02503674 -0.43043342]
[-0.31823993 -0.16109647 -0.5239132 ]]
[[ 0.05150248 -0.12936625 -0.25815621]
[ 0.24772477 -0.01911427 -0.35052732]
[ 0.21586443 0.14792195 0.15761676]]
...,
[[ 0.01544535 -0.31117681 0.21648997]
[-0.46108755 -0.34196696 -0.13508414]
[-0.5066644 -0.05267448 -0.3300153 ]]
[[-0.11529198 -0.00449779 0.21895851]
[-0.09709139 0.04266135 0.15187022]
[ 0.10297898 0.19023524 0.01521488]]
[[ 0.08442704 0.33765978 0.47518468]
[-0.08595871 0.1405237 0.03329588]
[-0.49468771 -0.16239651 0.13497087]]]]), CudaNdarray([-0.85461867 -1.86372256 -1.83810806 -1.30129552 -2.25499082 -1.58926201
-1.27909851 0.11986187 -0.01122112 -0.73687857 -1.83246195 -1.48389208
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-1.85402608 -0.16982625 -0.01069263 1.64269364 -0.73218721 -0.82166547]), CudaNdarray([[-0.06848672 -0.33572665 -0.07107727 ..., -0.17395231 -0.09427123
-0.15778545]
[-0.1053133 -0.12989189 -0.11146113 ..., -0.05436127 -0.04165371
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[-0.07607694 0.1937665 -0.08325466 ..., -0.0128378 -0.06449713
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...,
[-0.08130579 0.08930684 0.0105402 ..., -0.12867884 -0.25652361
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[ 0.07619429 -0.01234148 0.02239468 ..., -0.11565392 -0.07549141
-0.1699619 ]
[-0.0517144 -0.08033436 -0.1534216 ..., -0.16262934 0.04459566
-0.01990528]]), CudaNdarray([ 0.52357852 -0.01783111 0.07731287 -0.00364406 -0.35613233 -0.32693422
-0.12796393 -0.29243365 -0.31510758 -0.06928634 0.2329455 -0.11234906
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-0.44453838 -0.30344915 -0.36679229 -0.13879441 -0.46136782 -0.20684598
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-0.53769571 -0.28196073 0.1393282 -0.27473903 -0.38637713 -0.40029821
-0.24811952 0.2693747 -0.40213484 0.0591583 0.27540344 0.17569894
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-0.47666857 -0.33413064 0.34239367 -0.34059665 0.76573247 0.3221353
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0.09930992 -0.42003098 -0.12762159 -0.00608147 0.00643839 -0.50780487
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-0.58055836 -0.24480104 -0.40828323 -0.2001816 -0.28481776 -0.32080147
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-0.21326819 -0.40349117 -0.47873637 -0.29913801 -0.18927744 -0.30986848
-0.18622714 -0.0474378 -0.37858048 0.16422316 -0.02008451 -0.21538948
-0.4574129 0.00652995 -0.1200077 -0.20264925 -0.15487912 -0.13973069
-0.02296904 -0.27035806 -0.42095849 -0.3561379 -0.19328526 -0.0071193
-0.53268999 -0.38141188]), CudaNdarray([[ 0.02255613 -0.02403588]
[-0.10956398 -0.02643624]
[ 0.01040248 0.05602583]
...,
[-0.09703961 0.09959773]
[ 0.0451781 -0.08670858]
[ 0.01042011 -0.07449926]]), CudaNdarray([-0.43991706 0.4402543 ])]))
In [34]:
# for z in range(0,1):
e_p = []
p = []
image, prob, gold, rhoana, bb = gp.Legacy.read_dojo_data()
for z in range(0,10):
error_patches, patches = gp.Patch.patchify_maxoverlap(image[z], prob[z], np.zeros((image[0].shape[0], image[0].shape[1])), rhoana[z], gold[z], sample_rate=1, clamp_result=False)
e_p.append(error_patches)
p.append(patches)
a
In [5]:
# cconvert to FP format with target
import neuroproof
import neuroproof.FocusedProofreading as fp
print 'a'
a
In [52]:
g_n = graph.find_close_bodies(5,0,0.)
zn = []
for n in g_n:
zn.append(n[1])
In [53]:
np.max(zn)
Out[53]:
0.71764704585075378
In [7]:
graphs = []
for z in range(250,299):
g = fp.Graph('/home/d/FP/cylinder/graph_'+str(z)+'.json')
graphs.append(g)
In [ ]:
In [8]:
import cPickle as pickle
with open('/home/d/data/CYLPATCHES_CLAMPED/e_p.p', 'rb') as f:
e_p = pickle.load(f)
with open('/home/d/data/CYLPATCHES_CLAMPED/p.p', 'rb') as f:
p = pickle.load(f)
In [13]:
len(p)
Out[13]:
50
In [15]:
fp_y_test_proba = []
fp_y_test = []
gt_y_test = []
for z in range(49):
cur_e_p = e_p[z]
cur_p = p[z]
g = graphs[z]
for pa in cur_e_p:
# print pa['l'], pa['n']
label1 = pa['l']
label2 = pa['n']
graph_neighbors = sorted(g.find_close_bodies(label1,0,0.))
pred = [ne[1] for ne in graph_neighbors if ne[0] == label2]
fp_y_test.append(np.round(pred))
fp_y_test_proba.append(pred)
gt_y_test.append(1)
for pa in cur_p:
# print pa['l'], pa['n']
label1 = pa['l']
label2 = pa['n']
graph_neighbors = sorted(g.find_close_bodies(label1,0,0.))
pred = [ne[1] for ne in graph_neighbors if ne[0] == label2]
fp_y_test.append(np.round(pred))
fp_y_test_proba.append(pred)
gt_y_test.append(0)
In [ ]:
from sklearn.metrics import classification_report, accuracy_score, roc_curve, auc, precision_recall_fscore_support, f1_score, precision_recall_curve, average_precision_score, zero_one_loss
In [17]:
print 'Precision/Recall:'
print classification_report(np.array(gt_y_test), np.array(fp_y_test))
Precision/Recall:
precision recall f1-score support
0 0.61 0.34 0.43 9164
1 0.54 0.79 0.64 9164
avg / total 0.58 0.56 0.54 18328
In [91]:
acc_score = accuracy_score(np.array(gt_y_test), np.array(fp_y_test))
print 'Accuracy Score:', acc_score
Accuracy Score: 0.677486910995
In [ ]:
In [ ]:
In [31]:
Out[31]:
3820
In [92]:
gp_y_test_proba = []
gp_y_test = []
gt_y_test = []
for z in range(10):
cur_e_p = e_p[z]
cur_p = p[z]
for pa in cur_e_p:
# print pa['l'], pa['n']
label1 = pa['l']
label2 = pa['n']
pred = gp.Patch.test_and_unify([pa], cnn)
gp_y_test.append(np.round(pred))
gp_y_test_proba.append(pred)
gt_y_test.append(1)
for pa in cur_p:
# print pa['l'], pa['n']
label1 = pa['l']
label2 = pa['n']
pred = gp.Patch.test_and_unify([pa], cnn)
gp_y_test.append(np.round(pred))
gp_y_test_proba.append(pred)
gt_y_test.append(0)
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
<ipython-input-92-1fa747454865> in <module>()
13 label2 = pa['n']
14
---> 15 pred = gp.Patch.test_and_unify([pa], cnn)
16
17 gp_y_test.append(np.round(pred))
NameError: name 'cnn' is not defined
In [36]:
print classification_report(np.array(gt_y_test), np.array(gp_y_test))
precision recall f1-score support
0 1.00 0.92 0.96 3488
1 0.54 0.95 0.69 332
avg / total 0.96 0.92 0.93 3820
In [38]:
acc_score = accuracy_score(np.array(gt_y_test), np.array(gp_y_test))
print 'Accuracy Score:', acc_score
Accuracy Score: 0.924607329843
In [ ]:
In [ ]:
Content source: VCG/gp
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