Add hash of mlir for tf/tflite (#225)

generate_sharktank.py

@@ -124,6 +124,10 @@ def save_tf_model(tf_model_list):
                 dir=tf_model_dir,
                 model_name=tf_model_name,
             )
+            mlir_hash = create_hash(
+                os.path.join(tf_model_dir, tf_model_name + "_tf" + ".mlir")
+            )
+            np.save(os.path.join(tf_model_dir, "hash"), np.array(mlir_hash))
 
 
 def save_tflite_model(tflite_model_list):
@@ -161,6 +165,16 @@ def save_tflite_model(tflite_model_list):
                 model_name=tflite_model_name,
                 func_name="main",
             )
+            mlir_hash = create_hash(
+                os.path.join(
+                    tflite_model_name_dir,
+                    tflite_model_name + "_tflite" + ".mlir",
+                )
+            )
+            np.save(
+                os.path.join(tflite_model_name_dir, "hash"),
+                np.array(mlir_hash),
+            )
 
 
 # Validates whether the file is present or not.

shark/shark_downloader.py

@@ -128,9 +128,8 @@ def download_tflite_model(model_name, dynamic=False):
     dyn_str = "_dynamic" if dynamic else ""
     os.makedirs(WORKDIR, exist_ok=True)
     model_dir_name = model_name + "_tflite"
-    if not check_dir_exists(
-        model_dir_name, frontend="tflite", dynamic=dyn_str
-    ):
+
+    def gs_download_model():
         gs_command = (
             'gsutil -o "GSUtil:parallel_process_count=1" cp -r gs://shark_tank'
             + "/"
@@ -141,6 +140,29 @@ def download_tflite_model(model_name, dynamic=False):
         if os.system(gs_command) != 0:
             raise Exception("model not present in the tank. Contact Nod Admin")
 
+    if not check_dir_exists(
+        model_dir_name, frontend="tflite", dynamic=dyn_str
+    ):
+        gs_download_model()
+    else:
+        model_dir = os.path.join(WORKDIR, model_dir_name)
+        local_hash = str(np.load(os.path.join(model_dir, "hash.npy")))
+        gs_hash = (
+            'gsutil -o "GSUtil:parallel_process_count=1" cp gs://shark_tank'
+            + "/"
+            + model_dir_name
+            + "/hash.npy"
+            + " "
+            + os.path.join(model_dir, "upstream_hash.npy")
+        )
+        if os.system(gs_hash) != 0:
+            raise Exception("hash of the model not present in the tank.")
+        upstream_hash = str(
+            np.load(os.path.join(model_dir, "upstream_hash.npy"))
+        )
+        if local_hash != upstream_hash:
+            gs_download_model()
+
     model_dir = os.path.join(WORKDIR, model_dir_name)
     with open(
         os.path.join(model_dir, model_name + dyn_str + "_tflite.mlir")
@@ -160,7 +182,8 @@ def download_tf_model(model_name):
     model_name = model_name.replace("/", "_")
     os.makedirs(WORKDIR, exist_ok=True)
     model_dir_name = model_name + "_tf"
-    if not check_dir_exists(model_dir_name, frontend="tf"):
+
+    def gs_download_model():
         gs_command = (
             'gsutil -o "GSUtil:parallel_process_count=1" cp -r gs://shark_tank'
             + "/"
@@ -171,6 +194,27 @@ def download_tf_model(model_name):
         if os.system(gs_command) != 0:
             raise Exception("model not present in the tank. Contact Nod Admin")
 
+    if not check_dir_exists(model_dir_name, frontend="tf"):
+        gs_download_model()
+    else:
+        model_dir = os.path.join(WORKDIR, model_dir_name)
+        local_hash = str(np.load(os.path.join(model_dir, "hash.npy")))
+        gs_hash = (
+            'gsutil -o "GSUtil:parallel_process_count=1" cp gs://shark_tank'
+            + "/"
+            + model_dir_name
+            + "/hash.npy"
+            + " "
+            + os.path.join(model_dir, "upstream_hash.npy")
+        )
+        if os.system(gs_hash) != 0:
+            raise Exception("hash of the model not present in the tank.")
+        upstream_hash = str(
+            np.load(os.path.join(model_dir, "upstream_hash.npy"))
+        )
+        if local_hash != upstream_hash:
+            gs_download_model()
+
     model_dir = os.path.join(WORKDIR, model_dir_name)
     with open(os.path.join(model_dir, model_name + "_tf.mlir")) as f:
         mlir_file = f.read()

tank/tf/tf_model_list.csv

@@ -14,5 +14,6 @@ roberta-base,hf
 xlm-roberta-base,hf
 microsoft/MiniLM-L12-H384-uncased,hf
 funnel-transformer/small,hf
+microsoft/mpnet-base,hf
 facebook/convnext-tiny-224,img
 google/vit-base-patch16-224,img