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https://github.com/gsi-upm/senpy
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Adding the evaluation method inside the Senpy Context
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@ -7,7 +7,7 @@ standard_library.install_aliases()
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from . import plugins, api
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from .plugins import Plugin
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from .models import Error
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from .models import Error, AggregatedEvaluation
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from .blueprints import api_blueprint, demo_blueprint, ns_blueprint
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from threading import Thread
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@ -18,6 +18,10 @@ import errno
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import logging
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import traceback
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#Correct this import for managing the datasets
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from gsitk.datasets.datasets import DatasetManager
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logger = logging.getLogger(__name__)
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@ -42,6 +46,7 @@ class Senpy(object):
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self._default = None
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self._plugins = {}
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self._dm = DatasetManager()
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if plugin_folder:
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self.add_folder(plugin_folder)
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@ -190,6 +195,61 @@ class Senpy(object):
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results.analysis = [i['plugin'].id for i in results.analysis]
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return results
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def _get_datasets(self, request):
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if not self.datasets:
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raise Error(
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status=404,
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message=("No datasets found."
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" Please verify DatasetManager"))
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datasets_name = request.parameters.get('dataset', None).split(',')
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for dataset in datasets_name:
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if dataset not in self.datasets:
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logger.debug(("The dataset '{}' is not valid\n"
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"Valid datasets: {}").format(dataset,
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self.datasets.keys()))
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raise Error(
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status=404,
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message="The dataset '{}' is not valid".format(dataset))
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datasets = self._dm.prepare_datasets(datasets_name)
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return datasets
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@property
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def datasets(self):
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self._dataset_list = {}
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for item in self._dm.get_datasets():
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for key in item:
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if key in self._dataset_list:
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continue
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properties = item[key]
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properties['@id'] = key
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self._dataset_list[key] = properties
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return self._dataset_list
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def evaluate(self, params):
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logger.debug("evaluating request: {}".format(params))
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try:
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results = AggregatedEvaluation()
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results.parameters = params
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datasets = self._get_datasets(results)
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plugins = self._get_plugins(results)
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collector = list()
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for plugin in plugins:
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collector += [eval for eval in plugin.score(datasets)]
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if 'with_parameters' not in results.parameters:
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del results.parameters
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logger.debug("Returning evaluation result: {}".format(results))
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except (Error,Exception) as ex:
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if not isinstance(ex, Error):
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msg = "Error during evaluation: {} \n\t{}".format(ex,
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traceback.format_exc())
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ex = Error(message=msg, status=500)
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logger.exception('Error returning evaluation result')
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raise ex
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results.evaluations = collector
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return results
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def _conversion_candidates(self, fromModel, toModel):
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candidates = self.plugins(plugin_type='emotionConversionPlugin')
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for candidate in candidates:
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