New translations costs_learner.py (Chinese Simplified)

lang/zh/gklearn/ged/learning/costs_learner.py

@@ -0,0 +1,175 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Tue Jul  7 11:30:31 2020
+
+@author: ljia
+"""
+import numpy as np
+import cvxpy as cp
+import time
+from gklearn.utils import Timer
+
+
+class CostsLearner(object):
+	
+	
+	def __init__(self, parallel, verbose):
+		### To set.
+		self._parallel = parallel
+		self._verbose = verbose
+		# For update().
+		self._time_limit_in_sec = 0
+		self._max_itrs = 100
+		self._max_itrs_without_update = 3
+		self._epsilon_residual = 0.01
+		self._epsilon_ec = 0.1
+		### To compute.
+		self._residual_list = []
+		self._runtime_list = []
+		self._cost_list = []
+		self._nb_eo = None
+		# For update().
+		self._itrs = 0
+		self._converged = False
+		self._num_updates_ecs = 0
+		self._ec_changed = None
+		self._residual_changed = None
+		self._itrs_without_update = 0
+		### Both set and get.
+		self._ged_options = None
+
+
+	def fit(self, X, y):
+		pass
+	
+	
+	def preprocess(self):
+		pass # @todo: remove the zero numbers of edit costs.
+	
+	
+	def postprocess(self):
+		for i in range(len(self._cost_list[-1])):
+			if -1e-9 <= self._cost_list[-1][i] <= 1e-9:
+				self._cost_list[-1][i] = 0
+			if self._cost_list[-1][i] < 0:
+				raise ValueError('The edit cost is negative.')
+	
+	
+	def set_update_params(self, **kwargs):
+		self._time_limit_in_sec = kwargs.get('time_limit_in_sec', self._time_limit_in_sec)
+		self._max_itrs = kwargs.get('max_itrs', self._max_itrs)
+		self._max_itrs_without_update = kwargs.get('max_itrs_without_update', self._max_itrs_without_update)
+		self._epsilon_residual = kwargs.get('epsilon_residual', self._epsilon_residual)
+		self._epsilon_ec = kwargs.get('epsilon_ec', self._epsilon_ec)
+		
+
+	def update(self, y, graphs, ged_options, **kwargs):
+		# Set parameters.
+		self._ged_options = ged_options
+		if kwargs != {}:
+			self.set_update_params(**kwargs)
+		
+		# The initial iteration.
+		if self._verbose >= 2:
+			print('\ninitial:')
+		self.init_geds_and_nb_eo(y, graphs)
+
+		self._converged = False
+		self._itrs_without_update = 0
+		self._itrs = 0
+		self._num_updates_ecs = 0
+		timer = Timer(self._time_limit_in_sec)
+		# Run iterations from initial edit costs.
+		while not self.termination_criterion_met(self._converged, timer, self._itrs, self._itrs_without_update):
+			if self._verbose >= 2:
+				print('\niteration', self._itrs + 1)
+			time0 = time.time()
+				
+			# Fit GED space to the target space.
+			self.preprocess()
+			self.fit(self._nb_eo, y)
+			self.postprocess()
+			
+			# Compute new GEDs and numbers of edit operations.
+			self.update_geds_and_nb_eo(y, graphs, time0)
+			
+			# Check convergency.
+			self.check_convergency()
+			
+			# Print current states.
+			if self._verbose >= 2:
+				self.print_current_states()
+				
+			self._itrs += 1
+			
+			
+	def init_geds_and_nb_eo(self, y, graphs):
+		pass
+	
+	
+	def update_geds_and_nb_eo(self, y, graphs, time0):
+		pass
+			
+			
+	def compute_geds_and_nb_eo(self, graphs):
+		pass
+	
+	
+	def check_convergency(self):
+		pass
+	
+	
+	def print_current_states(self):
+		pass
+
+
+	def termination_criterion_met(self, converged, timer, itr, itrs_without_update):
+		if timer.expired() or (itr >= self._max_itrs if self._max_itrs >= 0 else False):
+# 			if self.__state == AlgorithmState.TERMINATED:
+# 				self.__state = AlgorithmState.INITIALIZED
+			return True
+		return converged or (itrs_without_update > self._max_itrs_without_update if self._max_itrs_without_update >= 0 else False)
+	
+	
+	def execute_cvx(self, prob):
+		try:
+			prob.solve(verbose=(self._verbose>=2))
+		except MemoryError as error0:
+			if self._verbose >= 2:
+				print('\nUsing solver "OSQP" caused a memory error.')
+				print('the original error message is\n', error0)
+				print('solver status: ', prob.status)
+				print('trying solver "CVXOPT" instead...\n')
+			try:
+				prob.solve(solver=cp.CVXOPT, verbose=(self._verbose>=2))
+			except Exception as error1:
+				if self._verbose >= 2:
+					print('\nAn error occured when using solver "CVXOPT".')
+					print('the original error message is\n', error1)
+					print('solver status: ', prob.status)
+					print('trying solver "MOSEK" instead. Notice this solver is commercial and a lisence is required.\n')
+				prob.solve(solver=cp.MOSEK, verbose=(self._verbose>=2))
+			else:
+				if self._verbose >= 2:
+					print('solver status: ', prob.status)					
+		else:
+			if self._verbose >= 2:
+				print('solver status: ', prob.status)
+		if self._verbose >= 2:				
+			print()
+			
+			
+	def get_results(self):
+		results = {}
+		results['residual_list'] = self._residual_list
+		results['runtime_list'] = self._runtime_list
+		results['cost_list'] = self._cost_list
+		results['nb_eo'] = self._nb_eo
+		results['itrs'] = self._itrs
+		results['converged'] = self._converged
+		results['num_updates_ecs'] = self._num_updates_ecs
+		results['ec_changed'] = self._ec_changed
+		results['residual_changed'] = self._residual_changed
+		results['itrs_without_update'] = self._itrs_without_update
+		return results