Deleted outdated files and regenerated weights_tf_free files

Author: anushka-cseatmnc

.gitignore

@@ -15,3 +15,4 @@ Models/Burmese_model4_version2/
 Models/Other/
 *~
 venv/
+convert_weights.py

lstm_word_segmentation/word_segmenter.py

@@ -1,6 +1,5 @@
 from pathlib import Path
 import numpy as np
-import h5py  
 import json
 from icu import Char
 from keras.models import Sequential
@@ -605,13 +604,10 @@ def save_model(self):
         model_path = (Path.joinpath(Path(__file__).parent.parent.absolute(), "Models/" + self.name))
         tf.saved_model.save(self.model, model_path)
 
-        # Inlining weight saving directly into HDF5 format
-        weights_file = Path.joinpath(Path(__file__).parent.parent.absolute(), "Models/" + self.name + "/weights.h5")
-        with h5py.File(str(weights_file), 'w') as hdf5_file:
-         # Iterate over the model weights and save each one as a dataset in the HDF5 file
-         for i, weight in enumerate(self.model.weights):
-            weight_name = f"weight_{i+1}"
-            hdf5_file.create_dataset(weight_name, data=weight.numpy())  # Save weight tensor directly
+        # Save one np array that holds all weights
+        file = Path.joinpath(Path(__file__).parent.parent.absolute(), "Models/" + self.name + "/weights")
+        np.save(str(file), self.model.weights)
+
         # Save the model in json format, that has both weights and grapheme clusters dictionary
         json_file = Path.joinpath(Path(__file__).parent.parent.absolute(), "Models/" + self.name + "/weights.json")
         with open(str(json_file), 'w') as wfile:
@@ -640,7 +636,6 @@ def save_model(self):
                 dic_model["data"] = serial_mat
                 output["mat{}".format(i+1)] = dic_model
             json.dump(output, wfile)
-    print(f"Model, weights in .h5, and weights metadata in .json saved successfully!")        
 
     def set_model(self, input_model):
         """