diff --git a/lang/fr/gklearn/kernels/treelet.py b/lang/fr/gklearn/kernels/treelet.py
index c3204ec..61ffd47 100644
--- a/lang/fr/gklearn/kernels/treelet.py
+++ b/lang/fr/gklearn/kernels/treelet.py
@@ -39,7 +39,7 @@ class Treelet(GraphKernel):
 	def _compute_gm_series(self):
 		self.__add_dummy_labels(self._graphs)
 		
-		# get all canonical keys of all graphs before calculating kernels to save 
+		# get all canonical keys of all graphs before computing kernels to save 
 		# time, but this may cost a lot of memory for large dataset.
 		canonkeys = []
 		if self._verbose >= 2:
@@ -55,7 +55,7 @@ class Treelet(GraphKernel):
 		from itertools import combinations_with_replacement
 		itr = combinations_with_replacement(range(0, len(self._graphs)), 2)
 		if self._verbose >= 2:
-			iterator = tqdm(itr, desc='calculating kernels', file=sys.stdout)
+			iterator = tqdm(itr, desc='Computing kernels', file=sys.stdout)
 		else:
 			iterator = itr
 		for i, j in iterator:
@@ -69,7 +69,7 @@ class Treelet(GraphKernel):
 	def _compute_gm_imap_unordered(self):
 		self.__add_dummy_labels(self._graphs)
 		
-		# get all canonical keys of all graphs before calculating kernels to save 
+		# get all canonical keys of all graphs before computing kernels to save 
 		# time, but this may cost a lot of memory for large dataset.
 		pool = Pool(self._n_jobs)
 		itr = zip(self._graphs, range(0, len(self._graphs)))
@@ -105,7 +105,7 @@ class Treelet(GraphKernel):
 	def _compute_kernel_list_series(self, g1, g_list):
 		self.__add_dummy_labels(g_list + [g1])
 		
-		# get all canonical keys of all graphs before calculating kernels to save 
+		# get all canonical keys of all graphs before computing kernels to save 
 		# time, but this may cost a lot of memory for large dataset.
 		canonkeys_1 = self.__get_canonkeys(g1)
 		canonkeys_list = []
@@ -119,7 +119,7 @@ class Treelet(GraphKernel):
 		# compute kernel list.
 		kernel_list = [None] * len(g_list)
 		if self._verbose >= 2:
-			iterator = tqdm(range(len(g_list)), desc='calculating kernels', file=sys.stdout)
+			iterator = tqdm(range(len(g_list)), desc='Computing kernels', file=sys.stdout)
 		else:
 			iterator = range(len(g_list))
 		for i in iterator:
@@ -132,7 +132,7 @@ class Treelet(GraphKernel):
 	def _compute_kernel_list_imap_unordered(self, g1, g_list):
 		self.__add_dummy_labels(g_list + [g1])
 		
-		# get all canonical keys of all graphs before calculating kernels to save 
+		# get all canonical keys of all graphs before computing kernels to save 
 		# time, but this may cost a lot of memory for large dataset.
 		canonkeys_1 = self.__get_canonkeys(g1)
 		canonkeys_list = [[] for _ in range(len(g_list))]
@@ -167,7 +167,7 @@ class Treelet(GraphKernel):
 		len_itr = len(g_list)
 		parallel_me(do_fun, func_assign, kernel_list, itr, len_itr=len_itr,
 			init_worker=init_worker, glbv=(canonkeys_1, canonkeys_list), method='imap_unordered', 
-			n_jobs=self._n_jobs, itr_desc='calculating kernels', verbose=self._verbose)
+			n_jobs=self._n_jobs, itr_desc='Computing kernels', verbose=self._verbose)
 			
 		return kernel_list
 	
@@ -185,7 +185,7 @@ class Treelet(GraphKernel):
 	
 	
 	def __kernel_do(self, canonkey1, canonkey2):
-		"""Calculate treelet graph kernel between 2 graphs.
+		"""Compute treelet graph kernel between 2 graphs.
 		
 		Parameters
 		----------