validating fashion_mnist train - kamangir/bolt#692

image_classifier/classes.py

@@ -11,6 +11,7 @@ import matplotlib.pyplot as plt
 import tensorflow as tf
 from tqdm import *
 import time
+from abcli.logging import crash_report
 import abcli.logging
 import logging
 
@@ -36,7 +37,9 @@ class Image_Classifier(object):
         if not success:
             return False
 
-        success, self.params = file.load_json(f"{model_path}/params.json", default={})
+        success, self.params = file.load_json(
+            f"{model_path}/image_classifier/model/params.json"
+        )
         if not success:
             return False
 
@@ -247,29 +250,32 @@ class Image_Classifier(object):
                 file.save_image(output_filename, image)
 
     def save(self, model_path):
-        model_filename = "{}/image_classifier/model".format(model_path)
-        file.prepare_for_saving(model_filename)
+        model_filename = f"{model_path}/image_classifier/model"
+
+        if not file.prepare_for_saving(model_filename):
+            return False
+
         try:
             self.model.save(model_filename)
-            logger.info("image_classifier.model -> {}".format(model_filename))
+            logger.info(f"image_classifier.model -> {model_filename}")
         except:
-            from abcli.logging import crash_report
-
-            crash_report("image_classifier.save({}) failed".format(model_path))
+            crash_report(f"-image_classifier: save({model_path}): failed.")
             return False
 
         self.params["object_name"] = path.name(model_path)
 
-        self.params["model_size"] = file.size(
-            "{}/image_classifier/model".format(model_path)
-        )
+        self.params["model_size"] = file.size(f"{model_path}/image_classifier/model")
 
         if not file.save_json(
-            "{}/class_names.json".format(model_path), self.class_names
+            f"{model_path}/class_names.json",
+            self.class_names,
         ):
             return False
 
-        if not file.save_json("{}/params.json".format(model_path), self.params):
+        if not file.save_json(
+            f"{model_path}/image_classifier/model/params.json",
+            self.params,
+        ):
             return False
 
         return True