diff --git a/samplelib/SampleGeneratorFace.py b/samplelib/SampleGeneratorFace.py
index 5f64852..344c792 100644
--- a/samplelib/SampleGeneratorFace.py
+++ b/samplelib/SampleGeneratorFace.py
@@ -27,7 +27,6 @@ class SampleGeneratorFace(SampleGeneratorBase):
                         output_sample_types=[],
                         add_sample_idx=False,
                         generators_count=4,
-                        rnd_seed=None,
                         **kwargs):
 
         super().__init__(samples_path, debug, batch_size)
@@ -35,9 +34,6 @@ class SampleGeneratorFace(SampleGeneratorBase):
         self.output_sample_types = output_sample_types
         self.add_sample_idx = add_sample_idx
         
-        if rnd_seed is None:
-            rnd_seed = np.random.randint(0x80000000)
-
         if self.debug:
             self.generators_count = 1
         else:
@@ -49,11 +45,11 @@ class SampleGeneratorFace(SampleGeneratorBase):
         if self.samples_len == 0:
             raise ValueError('No training data provided.')
 
-        index_host = mplib.IndexHost(self.samples_len, rnd_seed=rnd_seed)
+        index_host = mplib.IndexHost(self.samples_len)
 
         if random_ct_samples_path is not None:
             ct_samples = SampleLoader.load (SampleType.FACE, random_ct_samples_path)
-            ct_index_host = mplib.IndexHost( len(ct_samples), rnd_seed=rnd_seed )
+            ct_index_host = mplib.IndexHost( len(ct_samples) )
         else:
             ct_samples = None
             ct_index_host = None
@@ -62,9 +58,9 @@ class SampleGeneratorFace(SampleGeneratorBase):
         ct_pickled_samples = pickle.dumps(ct_samples, 4) if ct_samples is not None else None
 
         if self.debug:
-            self.generators = [ThisThreadGenerator ( self.batch_func, (pickled_samples, index_host.create_cli(), ct_pickled_samples, ct_index_host.create_cli() if ct_index_host is not None else None, rnd_seed) )]
+            self.generators = [ThisThreadGenerator ( self.batch_func, (pickled_samples, index_host.create_cli(), ct_pickled_samples, ct_index_host.create_cli() if ct_index_host is not None else None) )]
         else:
-            self.generators = [SubprocessGenerator ( self.batch_func, (pickled_samples, index_host.create_cli(), ct_pickled_samples, ct_index_host.create_cli() if ct_index_host is not None else None, rnd_seed+i), start_now=False ) \
+            self.generators = [SubprocessGenerator ( self.batch_func, (pickled_samples, index_host.create_cli(), ct_pickled_samples, ct_index_host.create_cli() if ct_index_host is not None else None), start_now=False ) \
                                for i in range(self.generators_count) ]
                                
             SubprocessGenerator.start_in_parallel( self.generators )
@@ -80,10 +76,8 @@ class SampleGeneratorFace(SampleGeneratorBase):
         return next(generator)
 
     def batch_func(self, param ):
-        pickled_samples, index_host, ct_pickled_samples, ct_index_host, rnd_seed = param
+        pickled_samples, index_host, ct_pickled_samples, ct_index_host = param
         
-        rnd_state = np.random.RandomState(rnd_seed)
-
         samples = pickle.loads(pickled_samples)
         ct_samples = pickle.loads(ct_pickled_samples) if ct_pickled_samples is not None else None
 
@@ -104,7 +98,7 @@ class SampleGeneratorFace(SampleGeneratorBase):
                     ct_sample = ct_samples[ct_indexes[n_batch]]
 
                 try:
-                    x, = SampleProcessor.process ([sample], self.sample_process_options, self.output_sample_types, self.debug, ct_sample=ct_sample, rnd_state=rnd_state)
+                    x, = SampleProcessor.process ([sample], self.sample_process_options, self.output_sample_types, self.debug, ct_sample=ct_sample)
                 except:
                     raise Exception ("Exception occured in sample %s. Error: %s" % (sample.filename, traceback.format_exc() ) )
 
diff --git a/samplelib/SampleProcessor.py b/samplelib/SampleProcessor.py
index c30e5f0..8a64ed3 100644
--- a/samplelib/SampleProcessor.py
+++ b/samplelib/SampleProcessor.py
@@ -63,13 +63,10 @@ class SampleProcessor(object):
                                  }
 
     @staticmethod
-    def process (samples, sample_process_options, output_sample_types, debug, ct_sample=None, rnd_state=None):
+    def process (samples, sample_process_options, output_sample_types, debug, ct_sample=None):
         SPTF = SampleProcessor.Types
 
-        if rnd_state is None:
-            rnd_state = np.random.RandomState( np.random.randint(0x80000000) )
-            
-        sample_rnd_seed = rnd_state.randint(0x80000000)
+        sample_rnd_seed = np.random.randint(0x80000000)
         
         outputs = []
         for sample in samples:
@@ -82,7 +79,7 @@ class SampleProcessor(object):
             if debug and is_face_sample:
                 LandmarksProcessor.draw_landmarks (sample_bgr, sample.landmarks, (0, 1, 0))
 
-            params = imagelib.gen_warp_params(sample_bgr, sample_process_options.random_flip, rotation_range=sample_process_options.rotation_range, scale_range=sample_process_options.scale_range, tx_range=sample_process_options.tx_range, ty_range=sample_process_options.ty_range, rnd_state=rnd_state )
+            params = imagelib.gen_warp_params(sample_bgr, sample_process_options.random_flip, rotation_range=sample_process_options.rotation_range, scale_range=sample_process_options.scale_range, tx_range=sample_process_options.tx_range, ty_range=sample_process_options.ty_range )
 
             outputs_sample = []
             for opts in output_sample_types: