class DiscourseParser(): def __init__(self, verbose, seg, output, SGML, edus, feature_sets = 'FengHirst'): ''' This is Hilda's segmentation module ''' self.segmenter = None self.verbose = verbose self.seg = seg self.output = output self.SGML = SGML self.edus = edus self.dependencies = True self.max_iters = 0 self.feature_sets = feature_sets initStart = time.time() try: self.segmenter = Segmenter(_model_path = os.path.join(paths.SEG_MODEL_PATH), _model_file = "training.scaled.model", _scale_model_file = "bin_scale", _name = "segmenter", verbose = self.verbose, dependencies = self.dependencies) except Exception, e: print "*** Loading Segmentation module failed..." if not self.segmenter is None: self.segmenter.unload() raise self.treebuilder = None try: if self.feature_sets == 'FengHirst': self.treebuilder = GreedyTreeBuilder(_model_path = paths.TREE_BUILD_MODEL_PATH, _bin_model_file = ['struct/FengHirst/within_no_context.svmperf', 'struct/FengHirst/above_no_context.svmperf'], _bin_scale_model_file = None, _mc_model_file = ['label/FengHirst/within_label_nuclearity_no_context.multiclass', 'label/FengHirst/above_label_nuclearity_no_context.multiclass'], _mc_scale_model_file = None, _name = "FengHirst", verbose = self.verbose, use_contextual_features = False) # else: # self.treebuilder = TreeBuilder(_model_path = paths.INIT_TREE_BUILD_MODEL_PATH, # _bin_model_file = 'struct/hilda/liblinear_bin_model.dat', _bin_scale_model_file = 'struct/hilda/bin_scale', # _mc_model_file = 'label/hilda/libsvm_rbf_mc_model.dat', _mc_scale_model_file = 'label/hilda/mc_scale', # _name = "hilda", verbose = self.verbose, use_contextual_features = False) except Exception, e: print "*** Loading Tree-building module failed..." print traceback.print_exc() if not self.treebuilder is None: self.treebuilder.unload() raise
def __init__(self, verbose, seg, output, SGML, edus, feature_sets = 'FengHirst'): ''' This is Hilda's segmentation module ''' self.segmenter = None self.verbose = verbose self.seg = seg self.output = output self.SGML = SGML self.edus = edus self.dependencies = True self.max_iters = 0 self.feature_sets = feature_sets initStart = time.time() try: self.segmenter = Segmenter(_model_path = os.path.join(paths.SEG_MODEL_PATH), _model_file = "training.scaled.model", _scale_model_file = "bin_scale", _name = "segmenter", verbose = self.verbose, dependencies = self.dependencies) except Exception, e: print "*** Loading Segmentation module failed..." if not self.segmenter is None: self.segmenter.unload() raise