Version 1.1.0 & improved batching code

pom.xml

@@ -5,7 +5,7 @@
 
     <groupId>org.hucompute.textimager.uima</groupId>
     <artifactId>deep-eos-uima</artifactId>
-    <version>1.0.0</version>
+    <version>1.1.0</version>
 
     <properties>
         <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>

src/main/resources/python/model.py

@@ -1,8 +1,6 @@
+import numpy as np
 import os
 from typing import List
-
-import numpy as np
-
 from utils import Utils
 
 os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
@@ -41,26 +39,22 @@ def tag(self, text) -> List[int]:
         potential_eos_list = util.build_potential_eos_list(text, self.window_size)
 
         eos_pos = []
-        for batch_no in range(int(len(potential_eos_list) / self.batch_size) + 1):
-            i = batch_no * self.batch_size
-            j = min(len(potential_eos_list), i + self.batch_size)
-            batch = potential_eos_list[i:j]
+        for i in range(0, len(potential_eos_list), self.batch_size):
+            batch = potential_eos_list[i:i + self.batch_size]
+            batch_size = len(batch)
 
             eos_positions = [eos_position for eos_position, _ in batch]
             char_sequences = [(-1.0, char_sequence) for _, char_sequence in batch]
             data_set = util.build_data_set(char_sequences, self.char_2_id_dict, self.window_size)
             features = np.array([i[1] for i in data_set])
-            batch_size = len(features)
-
-            if batch_size > 0:
-                predicted = self.deep_eos_model.predict(
-                    features,
-                    batch_size=batch_size,
-                    verbose=0)
 
-                for i in range(batch_size):
-                    if predicted[i][0] >= 0.5:
-                        eos_pos.append(int(eos_positions[i]))
+            predicted = self.deep_eos_model.predict(
+                features,
+                batch_size=batch_size,
+                verbose=0)
 
+            for j in range(batch_size):
+                if predicted[j][0] >= 0.5:
+                    eos_pos.append(int(eos_positions[j]))
 
         return eos_pos