Python warnings.warn() Examples
The following are 30 code examples for showing how to use warnings.warn(). These examples are extracted from open source projects. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example.
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Example 1
Project: cherrypy Author: cherrypy File: _cpchecker.py License: BSD 3-Clause "New" or "Revised" License | 6 votes |
def check_app_config_entries_dont_start_with_script_name(self): """Check for App config with sections that repeat script_name.""" for sn, app in cherrypy.tree.apps.items(): if not isinstance(app, cherrypy.Application): continue if not app.config: continue if sn == '': continue sn_atoms = sn.strip('/').split('/') for key in app.config.keys(): key_atoms = key.strip('/').split('/') if key_atoms[:len(sn_atoms)] == sn_atoms: warnings.warn( 'The application mounted at %r has config ' 'entries that start with its script name: %r' % (sn, key))
Example 2
Project: cherrypy Author: cherrypy File: _cpchecker.py License: BSD 3-Clause "New" or "Revised" License | 6 votes |
def check_site_config_entries_in_app_config(self): """Check for mounted Applications that have site-scoped config.""" for sn, app in cherrypy.tree.apps.items(): if not isinstance(app, cherrypy.Application): continue msg = [] for section, entries in app.config.items(): if section.startswith('/'): for key, value in entries.items(): for n in ('engine.', 'server.', 'tree.', 'checker.'): if key.startswith(n): msg.append('[%s] %s = %s' % (section, key, value)) if msg: msg.insert(0, 'The application mounted at %r contains the ' 'following config entries, which are only allowed ' 'in site-wide config. Move them to a [global] ' 'section and pass them to cherrypy.config.update() ' 'instead of tree.mount().' % sn) warnings.warn(os.linesep.join(msg))
Example 3
Project: cherrypy Author: cherrypy File: helper.py License: BSD 3-Clause "New" or "Revised" License | 6 votes |
def get_app(self, app=None): """Obtain a new (decorated) WSGI app to hook into the origin server.""" if app is None: app = cherrypy.tree if self.validate: try: from wsgiref import validate except ImportError: warnings.warn( 'Error importing wsgiref. The validator will not run.') else: # wraps the app in the validator app = validate.validator(app) return app
Example 4
Project: kaldi-python-io Author: funcwj File: inst.py License: Apache License 2.0 | 6 votes |
def pipe_fopen(command, mode, background=True): if mode not in ["rb", "r"]: raise RuntimeError("Now only support input from pipe") p = subprocess.Popen(command, shell=True, stdout=subprocess.PIPE) def background_command_waiter(command, p): p.wait() if p.returncode != 0: warnings.warn("Command \"{0}\" exited with status {1}".format( command, p.returncode)) _thread.interrupt_main() if background: thread = threading.Thread(target=background_command_waiter, args=(command, p)) # exits abnormally if main thread is terminated . thread.daemon = True thread.start() else: background_command_waiter(command, p) return p.stdout
Example 5
Project: neural-fingerprinting Author: StephanZheng File: loss.py License: BSD 3-Clause "New" or "Revised" License | 6 votes |
def fprop(self, x, y, **kwargs): if self.attack is not None: x = x, self.attack(x) else: x = x, # Catching RuntimeError: Variable -= value not supported by tf.eager. try: y -= self.smoothing * (y - 1. / tf.cast(y.shape[-1], tf.float32)) except RuntimeError: y.assign_sub(self.smoothing * (y - 1. / tf.cast(y.shape[-1], tf.float32))) logits = [self.model.get_logits(x, **kwargs) for x in x] loss = sum( softmax_cross_entropy_with_logits(labels=y, logits=logit) for logit in logits) warnings.warn("LossCrossEntropy is deprecated, switch to " "CrossEntropy. LossCrossEntropy may be removed on " "or after 2019-03-06.") return loss
Example 6
Project: neural-fingerprinting Author: StephanZheng File: loss.py License: BSD 3-Clause "New" or "Revised" License | 6 votes |
def fprop(self, x, y, **kwargs): x_adv = self.attack(x) d1 = self.model.fprop(x, **kwargs) d2 = self.model.fprop(x_adv, **kwargs) pairing_loss = [tf.reduce_mean(tf.square(a - b)) for a, b in zip(d1[Model.O_FEATURES], d2[Model.O_FEATURES])] pairing_loss = tf.reduce_mean(pairing_loss) loss = softmax_cross_entropy_with_logits( labels=y, logits=d1[Model.O_LOGITS]) loss += softmax_cross_entropy_with_logits( labels=y, logits=d2[Model.O_LOGITS]) warnings.warn("LossFeaturePairing is deprecated, switch to " "FeaturePairing. LossFeaturePairing may be removed " "on or after 2019-03-06.") return loss + self.weight * pairing_loss
Example 7
Project: neural-fingerprinting Author: StephanZheng File: utils.py License: BSD 3-Clause "New" or "Revised" License | 6 votes |
def to_categorical(y, num_classes=None): """ Converts a class vector (integers) to binary class matrix. This is adapted from the Keras function with the same name. :param y: class vector to be converted into a matrix (integers from 0 to num_classes). :param num_classes: num_classes: total number of classes. :return: A binary matrix representation of the input. """ y = np.array(y, dtype='int').ravel() if not num_classes: num_classes = np.max(y) + 1 warnings.warn("FutureWarning: the default value of the second" "argument in function \"to_categorical\" is deprecated." "On 2018-9-19, the second argument" "will become mandatory.") n = y.shape[0] categorical = np.zeros((n, num_classes)) categorical[np.arange(n), y] = 1 return categorical
Example 8
Project: neural-fingerprinting Author: StephanZheng File: utils_keras.py License: BSD 3-Clause "New" or "Revised" License | 6 votes |
def _get_logits_name(self): """ Looks for the name of the layer producing the logits. :return: name of layer producing the logits """ softmax_name = self._get_softmax_name() softmax_layer = self.model.get_layer(softmax_name) if not isinstance(softmax_layer, Activation): # In this case, the activation is part of another layer return softmax_name if hasattr(softmax_layer, 'inbound_nodes'): warnings.warn( "Please update your version to keras >= 2.1.3; " "support for earlier keras versions will be dropped on " "2018-07-22") node = softmax_layer.inbound_nodes[0] else: node = softmax_layer._inbound_nodes[0] logits_name = node.inbound_layers[0].name return logits_name
Example 9
Project: neural-fingerprinting Author: StephanZheng File: utils_tf.py License: BSD 3-Clause "New" or "Revised" License | 6 votes |
def model_loss(y, model, mean=True): """ Define loss of TF graph :param y: correct labels :param model: output of the model :param mean: boolean indicating whether should return mean of loss or vector of losses for each input of the batch :return: return mean of loss if True, otherwise return vector with per sample loss """ warnings.warn('This function is deprecated.') op = model.op if op.type == "Softmax": logits, = op.inputs else: logits = model out = softmax_cross_entropy_with_logits(logits=logits, labels=y) if mean: out = reduce_mean(out) return out
Example 10
Project: neural-fingerprinting Author: StephanZheng File: utils_tf.py License: BSD 3-Clause "New" or "Revised" License | 6 votes |
def infer_devices(devices=None): """ Returns the list of devices that multi-replica code should use. :param devices: list of string device names, e.g. ["/GPU:0"] If the user specifies this, `infer_devices` checks that it is valid, and then uses this user-specified list. If the user does not specify this, infer_devices uses: - All available GPUs, if there are any - CPU otherwise """ if devices is None: devices = get_available_gpus() if len(devices) == 0: warnings.warn("No GPUS, running on CPU") # Set device to empy string, tf will figure out whether to use # XLA or not, etc., automatically devices = [""] else: assert len(devices) > 0 for device in devices: assert isinstance(device, str), type(device) return devices
Example 11
Project: multibootusb Author: mbusb File: monitor.py License: GNU General Public License v2.0 | 6 votes |
def enable_receiving(self): """ Switch the monitor into listing mode. Connect to the event source and receive incoming events. Only after calling this method, the monitor listens for incoming events. .. note:: This method is implicitly called by :meth:`__iter__`. You don't need to call it explicitly, if you are iterating over the monitor. .. deprecated:: 0.16 Will be removed in 1.0. Use :meth:`start()` instead. """ import warnings warnings.warn('Will be removed in 1.0. Use Monitor.start() instead.', DeprecationWarning) self.start()
Example 12
Project: multibootusb Author: mbusb File: _device.py License: GNU General Public License v2.0 | 6 votes |
def from_sys_path(cls, context, sys_path): #pragma: no cover """ .. versionchanged:: 0.4 Raise :exc:`NoSuchDeviceError` instead of returning ``None``, if no device was found for ``sys_path``. .. versionchanged:: 0.5 Raise :exc:`DeviceNotFoundAtPathError` instead of :exc:`NoSuchDeviceError`. .. deprecated:: 0.18 Use :class:`Devices.from_sys_path` instead. """ import warnings warnings.warn( 'Will be removed in 1.0. Use equivalent Devices method instead.', DeprecationWarning, stacklevel=2 ) return Devices.from_sys_path(context, sys_path)
Example 13
Project: multibootusb Author: mbusb File: _device.py License: GNU General Public License v2.0 | 6 votes |
def traverse(self): """ Traverse all parent devices of this device from bottom to top. Return an iterable yielding all parent devices as :class:`Device` objects, *not* including the current device. The last yielded :class:`Device` is the top of the device hierarchy. .. deprecated:: 0.16 Will be removed in 1.0. Use :attr:`ancestors` instead. """ import warnings warnings.warn( 'Will be removed in 1.0. Use Device.ancestors instead.', DeprecationWarning, stacklevel=2 ) return self.ancestors
Example 14
Project: multibootusb Author: mbusb File: _device.py License: GNU General Public License v2.0 | 6 votes |
def __iter__(self): """ Iterate over the names of all properties defined for this device. Return a generator yielding the names of all properties of this device as unicode strings. .. deprecated:: 0.21 Will be removed in 1.0. Access properties with Device.properties. """ import warnings warnings.warn( 'Will be removed in 1.0. Access properties with Device.properties.', DeprecationWarning, stacklevel=2 ) return self.properties.__iter__()
Example 15
Project: multibootusb Author: mbusb File: _device.py License: GNU General Public License v2.0 | 6 votes |
def __getitem__(self, prop): """ Get the given property from this device. ``prop`` is a unicode or byte string containing the name of the property. Return the property value as unicode string, or raise a :exc:`~exceptions.KeyError`, if the given property is not defined for this device. .. deprecated:: 0.21 Will be removed in 1.0. Access properties with Device.properties. """ import warnings warnings.warn( 'Will be removed in 1.0. Access properties with Device.properties.', DeprecationWarning, stacklevel=2 ) return self.properties.__getitem__(prop)
Example 16
Project: multibootusb Author: mbusb File: _device.py License: GNU General Public License v2.0 | 6 votes |
def asint(self, prop): """ Get the given property from this device as integer. ``prop`` is a unicode or byte string containing the name of the property. Return the property value as integer. Raise a :exc:`~exceptions.KeyError`, if the given property is not defined for this device, or a :exc:`~exceptions.ValueError`, if the property value cannot be converted to an integer. .. deprecated:: 0.21 Will be removed in 1.0. Use Device.properties.asint() instead. """ import warnings warnings.warn( 'Will be removed in 1.0. Use Device.properties.asint instead.', DeprecationWarning, stacklevel=2 ) return self.properties.asint(prop)
Example 17
Project: mlearn Author: materialsvirtuallab File: models.py License: BSD 3-Clause "New" or "Revised" License | 6 votes |
def fit(self, inputs, outputs, weights=None, override=False): """ Fit model. Args: inputs (list/Array): List/Array of input training objects. outputs (list/Array): List/Array of output values (supervisory signals). weights (list/Array): List/Array of weights. Default to None, i.e., unweighted. override (bool): Whether to calculate the feature vectors from given inputs. Default to False. Set to True if you want to retrain the model with a different set of training inputs. """ if self._xtrain is None or override: xtrain = self.describer.describe_all(inputs) else: warnings.warn("Feature vectors retrieved from cache " "and input training objects ignored. " "To override the old cache with feature vectors " "of new training objects, set override=True.") xtrain = self._xtrain self.model.fit(xtrain, outputs, weights) self._xtrain = xtrain
Example 18
Project: mlearn Author: materialsvirtuallab File: models.py License: BSD 3-Clause "New" or "Revised" License | 6 votes |
def predict(self, inputs, override=False): """ Predict outputs with fitted model. Args: inputs (list/Array): List/Array of input testing objects. override (bool): Whether to calculate the feature vectors from given inputs. Default to False. Set to True if you want to test the model with a different set of testing inputs. Returns: Predicted output array from inputs. """ if self._xtest is None or override: xtest = self.describer.describe_all(inputs) else: warnings.warn("Feature vectors retrieved from cache " "and input testing objects ignored. " "To override the old cache with feature vectors " "of new testing objects, set override=True.") xtest = self._xtest self._xtest = xtest return self.model.predict(xtest)
Example 19
Project: mlearn Author: materialsvirtuallab File: models.py License: BSD 3-Clause "New" or "Revised" License | 6 votes |
def fit(self, inputs, outputs, override=False): """ Args: inputs (list): List of input training objects. outputs (list): List/Array of output values (supervisory signals). override: (bool) Whether to calculate the feature vectors from given inputs. Default to False. Set to True if you want to retrain the model with a different set of training inputs. """ if not self._xtrain or override: xtrain = self.describer.describe_all(inputs) else: warnings.warn("Feature vectors retrieved from cache " "and input training objects ignored. " "To override the old cache with feature vectors " "of new training objects, set override=True.") xtrain = self._xtrain self.model.fit(xtrain, outputs) self._xtrain = xtrain
Example 20
Project: mlearn Author: materialsvirtuallab File: models.py License: BSD 3-Clause "New" or "Revised" License | 6 votes |
def predict(self, inputs, override=False, **kwargs): """ Args: inputs (List): List of input testing objects. override: (bool) Whether to calculate the feature vectors from given inputs. Default to False. Set to True if you want to test the model with a different set of testing inputs. kwargs: kwargs to be passed to predict method, e.g. return_std, return_cov. Returns: Predicted output array from inputs. """ if self._xtest is None or override: xtest = self.describer.describe_all(inputs) else: warnings.warn("Feature vectors retrieved from cache " "and input testing objects ignored. " "To override the old cache with feature vectors " "of new testing objects, set override=True.") xtest = self._xtest self._xtest = xtest return self.model.predict(xtest, **kwargs)
Example 21
Project: neuropythy Author: noahbenson File: conf.py License: GNU Affero General Public License v3.0 | 6 votes |
def rc(): ''' config.rc() yields the data imported from the Neuropythy rc file, if any. ''' if config._rc is None: # First: We check to see if we have been given a custom nptyhrc file: npythyrc_path = os.path.expanduser('~/.npythyrc') if 'NPYTHYRC' in os.environ: npythyrc_path = os.path.expanduser(os.path.expandvars(os.environ['NPYTHYRC'])) # the default config: if os.path.isfile(npythyrc_path): try: config._rc = loadrc(npythyrc_path) config._rc['npythyrc_loaded'] = True except Exception as err: warnings.warn('Could not load neuropythy RC file: %s' % npythyrc_path) config._rc = {'npythyrc_loaded':False, 'npythyrc_error': err} else: config._rc = {'npythyrc_loaded':False} config._rc['npythyrc'] = npythyrc_path return config._rc
Example 22
Project: indras_net Author: gcallah File: registry.py License: GNU General Public License v3.0 | 5 votes |
def __setitem__(self, key, value): if key not in self.agents or self.agents[key] is None: self.agents[key] = value if value is None: warnings.warn("Trying to set the value of key {} to None.". format(key), RuntimeWarning) else: pass # this fails the tests at the moment, so we need to debug # it is the tests that have a problem! # raise KeyError("The key \"{}\" already exists in the registry" # .format(key))
Example 23
Project: vergeml Author: mme File: __main__.py License: MIT License | 5 votes |
def _configure_logging(level=logging.INFO): logging.addLevelName(logging.DEBUG, 'Debug:') logging.addLevelName(logging.INFO, 'Info:') logging.addLevelName(logging.WARNING, 'Warning!') logging.addLevelName(logging.CRITICAL, 'Critical!') logging.addLevelName(logging.ERROR, 'Error!') logging.basicConfig(format='%(levelname)s %(message)s', level=logging.INFO) if not sys.warnoptions: import warnings warnings.simplefilter("ignore") # TODO hack to get rid of deprecation warning that appeared allthough filters # are set to ignore. Is there a more sane way? warnings.warn = lambda *args, **kwargs: None
Example 24
Project: aegea Author: kislyuk File: orgs.py License: Apache License 2.0 | 5 votes |
def add_member(self, login): """Add ``login`` to this team. :returns: bool """ warnings.warn( 'This is no longer supported by the GitHub API, see ' 'https://developer.github.com/changes/2014-09-23-one-more-week' '-before-the-add-team-member-api-breaking-change/', DeprecationWarning) url = self._build_url('members', login, base_url=self._api) return self._boolean(self._put(url), 204, 404)
Example 25
Project: aegea Author: kislyuk File: orgs.py License: Apache License 2.0 | 5 votes |
def remove_member(self, login): """Remove ``login`` from this team. :param str login: (required), login of the member to remove :returns: bool """ warnings.warn( 'This is no longer supported by the GitHub API, see ' 'https://developer.github.com/changes/2014-09-23-one-more-week' '-before-the-add-team-member-api-breaking-change/', DeprecationWarning) url = self._build_url('members', login, base_url=self._api) return self._boolean(self._delete(url), 204, 404)
Example 26
Project: aegea Author: kislyuk File: orgs.py License: Apache License 2.0 | 5 votes |
def add_member(self, login, team): """Add ``login`` to ``team`` and thereby to this organization. .. warning:: This method is no longer valid. To add a member to a team, you must now retrieve the team directly, and use the ``invite`` method. Any user that is to be added to an organization, must be added to a team as per the GitHub api. .. note:: This method is of complexity O(n). This iterates over all teams in your organization and only adds the user when the team name matches the team parameter above. If you want constant time, you should retrieve the team and call ``add_member`` on that team directly. :param str login: (required), login name of the user to be added :param str team: (required), team name :returns: bool """ warnings.warn( 'This is no longer supported by the GitHub API, see ' 'https://developer.github.com/changes/2014-09-23-one-more-week' '-before-the-add-team-member-api-breaking-change/', DeprecationWarning) for t in self.iter_teams(): if team == t.name: return t.add_member(login) return False
Example 27
Project: aegea Author: kislyuk File: tempfile.py License: Apache License 2.0 | 5 votes |
def _cleanup(cls, name, warn_message): _rmtree(name) _warnings.warn(warn_message, _ResourceWarning)
Example 28
Project: xrft Author: xgcm File: xrft.py License: MIT License | 5 votes |
def isotropic_powerspectrum(*args, **kwargs): # pragma: no cover """ Deprecated function. See isotropic_power_spectrum doc """ import warnings msg = "This function has been renamed and will disappear in the future."\ +" Please use isotropic_power_spectrum instead" warnings.warn(msg, Warning) return isotropic_power_spectrum(*args, **kwargs)
Example 29
Project: xrft Author: xgcm File: xrft.py License: MIT License | 5 votes |
def isotropic_crossspectrum(*args, **kwargs): # pragma: no cover """ Deprecated function. See isotropic_cross_spectrum doc """ import warnings msg = "This function has been renamed and will disappear in the future."\ +" Please use isotropic_cross_spectrum instead" warnings.warn(msg, Warning) return isotropic_cross_spectrum(*args, **kwargs)
Example 30
Project: cherrypy Author: cherrypy File: _cpchecker.py License: BSD 3-Clause "New" or "Revised" License | 5 votes |
def check_skipped_app_config(self): """Check for mounted Applications that have no config.""" for sn, app in cherrypy.tree.apps.items(): if not isinstance(app, cherrypy.Application): continue if not app.config: msg = 'The Application mounted at %r has an empty config.' % sn if self.global_config_contained_paths: msg += (' It looks like the config you passed to ' 'cherrypy.config.update() contains application-' 'specific sections. You must explicitly pass ' 'application config via ' 'cherrypy.tree.mount(..., config=app_config)') warnings.warn(msg) return