Demo: updated notebooks and helper code to use new model format, whic…

…h does not need a separate weights file

demo/scenarios/2d_evidence_interpretability.ipynb

@@ -48,7 +48,7 @@
     "from demo.scenarios.model_analysis import *\n",
     "\n",
     "# Load the model/\n",
-    "loaded_model = load_model(MODEL_FILE_PATH, MODEL_WEIGHTS_PATH)"
+    "loaded_model = load_model(MODEL_FILE_PATH)"
    ]
   },
   {

demo/scenarios/2f_evidence_interoperability.ipynb

@@ -51,9 +51,7 @@
     "\n",
     "def run_and_get_log() -> str:\n",
     "    \"\"\"Runs the model and gets the log.\"\"\"\n",
-    "    model_predict.run_model(\n",
-    "        SAMPLE_DATASET_DIR, MODEL_FILE_PATH, MODEL_WEIGHTS_PATH\n",
-    "    )\n",
+    "    model_predict.run_model(SAMPLE_DATASET_DIR, MODEL_FILE_PATH)\n",
     "\n",
     "    return model_predict.load_log()"
    ]

demo/scenarios/2g_evidence_resilience.ipynb

@@ -51,9 +51,7 @@
     "\n",
     "def run_and_get_log() -> str:\n",
     "    \"\"\"Runs the model and gets the log.\"\"\"\n",
-    "    model_predict.run_model(\n",
-    "        OOD_DATASET_DIR, MODEL_FILE_PATH, MODEL_WEIGHTS_PATH\n",
-    "    )\n",
+    "    model_predict.run_model(OOD_DATASET_DIR, MODEL_FILE_PATH)\n",
     "\n",
     "    return model_predict.load_log()"
    ]

demo/scenarios/2h_evidence_monitorability.ipynb

@@ -50,9 +50,7 @@
     "\n",
     "def run_and_get_log() -> str:\n",
     "    \"\"\"Runs the model and gets the log.\"\"\"\n",
-    "    model_predict.run_model(\n",
-    "        OOD_DATASET_DIR, MODEL_FILE_PATH, MODEL_WEIGHTS_PATH\n",
-    "    )\n",
+    "    model_predict.run_model(OOD_DATASET_DIR, MODEL_FILE_PATH)\n",
     "    return model_predict.load_log()"
    ]
   },

demo/scenarios/2i_evidence_performance_time.ipynb

@@ -53,7 +53,7 @@
     "    \"\"\"Returns total time, and average time per inference.\"\"\"\n",
     "    start = time.time()\n",
     "    avg_time, _, _ = model_predict.run_model(\n",
-    "        SAMPLE_DATASET_DIR, MODEL_FILE_PATH, MODEL_WEIGHTS_PATH\n",
+    "        SAMPLE_DATASET_DIR, MODEL_FILE_PATH\n",
     "    )\n",
     "    end = time.time()\n",
     "    total = end - start\n",

demo/scenarios/get_model.sh

@@ -1,2 +1,2 @@
 #!/usr/bin/env bash
-curl -o ./model/oxford_flower_model_v6.testing.keras -L "https://docs.google.com/uc?export=download&id=15kAII1kOPGIAI46OP01ecNkq4tdf5yXw"
+curl -o ./model/oxford_flower_model.keras -L "https://drive.usercontent.google.com/download?id=17C_RowVjlZXrvY_VHXCTBAHwLZjZl1OD&export=download&authuser=0&confirm=t"

demo/scenarios/model_analysis.py

@@ -1,19 +1,9 @@
 import matplotlib.pyplot as plt
 import tensorflow as tf
-from tensorflow.keras.models import model_from_json
 
 
-def load_model(model_filename: str, weights_filename: str):
-    # Load model
-    json_file = open(model_filename, "r")
-    loaded_model_json = json_file.read()
-    loaded_model = model_from_json(loaded_model_json)
-    json_file.close()
-
-    # Load weights into new model
-    loaded_model.load_weights(weights_filename)
-
-    return loaded_model
+def load_model(model_filename: str):
+    return tf.keras.models.load_model(model_filename)
 
 
 def run_model(im, loaded_model):

demo/scenarios/model_predict.py

@@ -44,19 +44,13 @@ def parse_args():
     )
     # --model file example: model_f3_a.json
     parser.add_argument(
-        "--model", help="The json formatted model file.", required=True
-    )
-    # --weights file example: model_f_a.h5
-    parser.add_argument(
-        "--weights",
-        help="The file that contains the model weights.",
-        required=True,
+        "--model", help="The keras formatted model file.", required=True
     )
     args = parser.parse_args()
     return args
 
 
-def run_model(image_folder_path, model_file, weights_file):
+def run_model(image_folder_path, model_file):
     """
     This script gets performance metrics (elapsed time and memory consumption) for running inference on a model.
     It does NOT check accurate predictions - it simply runs the inference on the provided dataset and outputs statics
@@ -70,7 +64,6 @@ def run_model(image_folder_path, model_file, weights_file):
     import tensorflow as tf
 
     print_and_log(f"TensorFlow version: {tf.__version__}")
-    from tensorflow.keras.models import model_from_json
 
     # Load dataset
     dataset = tf.keras.utils.image_dataset_from_directory(
@@ -85,24 +78,16 @@ def run_model(image_folder_path, model_file, weights_file):
     ru1 = getrusage(RUSAGE_SELF).ru_maxrss
 
     # Load model
-    json_file = open(model_file, "r")
-    loaded_model_json = json_file.read()
-    loaded_model = model_from_json(loaded_model_json)
-    json_file.close()
-
-    # Load weights into new model
-    loaded_model.load_weights(weights_file)
+    loaded_model = tf.keras.models.load_model(model_file)
     print_and_log("Loaded model from disk!")
 
     ru2 = getrusage(RUSAGE_SELF).ru_maxrss
 
     print_and_log(loaded_model.summary())
 
     mfile_size = os.path.getsize(model_file)
-    wfile_size = os.path.getsize(weights_file)
 
-    print_and_log(f"Size of model json file ({model_file}): {mfile_size} bytes")
-    print_and_log(f"Size of weights file ({weights_file}): {wfile_size} bytes")
+    print_and_log(f"Size of model file ({model_file}): {mfile_size} bytes")
     print_and_log(
         f"Memory used for the entire model loading process: {ru2 - ru1} {r_mem_units_str}."
     )
@@ -208,6 +193,5 @@ def run_model(image_folder_path, model_file, weights_file):
     args = parse_args()
     image_folder = args.images
     model_file = args.model
-    weights_file = args.weights
 
-    run_model(image_folder, model_file, weights_file)
+    run_model(image_folder, model_file)

demo/scenarios/session.py

@@ -29,10 +29,7 @@
 os.makedirs(MEDIA_DIR, exist_ok=True)
 
 # The json file of the model to load
-MODEL_FILE_PATH = MODELS_DIR / "model_f3_a.json"
-
-# The weights file for the model
-MODEL_WEIGHTS_PATH = MODELS_DIR / "oxford_flower_model_v6.testing.keras"
+MODEL_FILE_PATH = MODELS_DIR / "oxford_flower_model.keras"
 
 # This is the external script that will load and run the model for inference/prediction.
 MODEL_SCRIPT = Path.cwd() / "model_predict.py"
@@ -41,6 +38,4 @@
     SAMPLE_DATASET_DIR,
     "--model",
     MODEL_FILE_PATH,
-    "--weights",
-    MODEL_WEIGHTS_PATH,
 ]