fix some mmap and vicuna bugs

apps/language_models/scripts/vicuna.py

@@ -61,26 +61,22 @@
     vic = None
     if not args.sharded:
         first_vic_mlir_path = (
-            Path(f"first_vicuna_{args.precision}.mlir")
+            None
             if args.first_vicuna_mlir_path is None
             else Path(args.first_vicuna_mlir_path)
         )
         second_vic_mlir_path = (
-            Path(f"second_vicuna_{args.precision}.mlir")
+            None
             if args.second_vicuna_mlir_path is None
             else Path(args.second_vicuna_mlir_path)
         )
         first_vic_vmfb_path = (
-            Path(
-                f"first_vicuna_{args.precision}_{args.device.replace('://', '_')}.vmfb"
-            )
+            None
             if args.first_vicuna_vmfb_path is None
             else Path(args.first_vicuna_vmfb_path)
         )
         second_vic_vmfb_path = (
-            Path(
-                f"second_vicuna_{args.precision}_{args.device.replace('://', '_')}.vmfb"
-            )
+            None
             if args.second_vicuna_vmfb_path is None
             else Path(args.second_vicuna_vmfb_path)
         )

apps/language_models/src/pipelines/vicuna_pipeline.py

@@ -33,6 +33,7 @@ def __init__(
         first_vicuna_vmfb_path=None,
         second_vicuna_vmfb_path=None,
         load_mlir_from_shark_tank=True,
+        low_device_memory=False,
     ) -> None:
         super().__init__(model_name, hf_model_path, max_num_tokens)
         self.max_sequence_length = 256
@@ -43,6 +44,9 @@ def __init__(
         self.first_vicuna_mlir_path = first_vicuna_mlir_path
         self.second_vicuna_mlir_path = second_vicuna_mlir_path
         self.load_mlir_from_shark_tank = load_mlir_from_shark_tank
+        self.low_device_memory = low_device_memory
+        self.first_vic = None
+        self.second_vic = None
         if self.first_vicuna_mlir_path == None:
             self.first_vicuna_mlir_path = self.get_model_path()
         if self.second_vicuna_mlir_path == None:
@@ -61,7 +65,7 @@ def get_model_path(self, model_number="first", suffix="mlir"):
         if suffix == "mlir":
             return Path(f"{model_number}_vicuna_{self.precision}.{suffix}")
         return Path(
-            f"{model_number}_vicuna_{safe_device}_{self.precision}.{suffix}"
+            f"{model_number}_vicuna_{self.precision}_{safe_device}.{suffix}"
         )
 
     def get_tokenizer(self):
@@ -87,7 +91,7 @@ def compile_first_vicuna(self):
         # Compilation path needs some more work before it is functional
 
         print(
-            f"[DEBUG] vmfb not found at {self.first_vicuna_vmfb_path.absolute()}. Trying to work with"
+            f"[DEBUG] vmfb not found at {self.first_vicuna_vmfb_path.absolute()}. Trying to work with\n"
             f"[DEBUG] mlir path { self.first_vicuna_mlir_path} {'exists' if self.first_vicuna_mlir_path.exists() else 'does not exist'}"
         )
         if self.first_vicuna_mlir_path.exists():
@@ -436,12 +440,19 @@ def generate(self, prompt, cli=False):
         # TODO: refactor for cleaner integration
         import gc
 
+        if not self.low_device_memory:
+            if self.first_vic == None:
+                self.first_vic = self.compile_first_vicuna()
+            if self.second_vic == None:
+                self.second_vic = self.compile_second_vicuna()
         res = []
         res_tokens = []
         params = {
             "prompt": prompt,
             "is_first": True,
-            "fv": self.compile_first_vicuna(),
+            "fv": self.compile_first_vicuna()
+            if self.first_vic == None
+            else self.first_vic,
         }
 
         generated_token_op = self.generate_new_token(params=params)
@@ -457,18 +468,20 @@ def generate(self, prompt, cli=False):
             print(f"Assistant: {detok}", end=" ", flush=True)
 
         # Clear First Vic from Memory (main and cuda)
-        del params
-        torch.cuda.empty_cache()
-        gc.collect()
+        if self.low_device_memory:
+            del params
+            torch.cuda.empty_cache()
+            gc.collect()
 
-        sec_vic = self.compile_second_vicuna()
         for _ in range(self.max_num_tokens - 2):
             params = {
                 "prompt": None,
                 "is_first": False,
                 "logits": logits,
                 "pkv": pkv,
-                "sv": sec_vic,
+                "sv": self.compile_second_vicuna()
+                if self.second_vic == None
+                else self.second_vic,
             }
 
             generated_token_op = self.generate_new_token(params=params)
@@ -489,9 +502,10 @@ def generate(self, prompt, cli=False):
                 res.append(detok)
                 if cli:
                     print(f"{detok}", end=" ", flush=True)
-        del sec_vic, pkv, logits
-        torch.cuda.empty_cache()
-        gc.collect()
+        if self.device == "cuda":
+            del sec_vic, pkv, logits
+            torch.cuda.empty_cache()
+            gc.collect()
 
         for i in range(len(res_tokens)):
             if type(res_tokens[i]) != int:

shark/iree_utils/compile_utils.py

@@ -20,6 +20,7 @@
 import os
 import re
 import tempfile
+from pathlib import Path
 
 
 # Get the iree-compile arguments given device.
@@ -355,6 +356,9 @@ def load_vmfb_using_mmap(
     #   OR 2. We are compiling on the fly, therefore we have the flatbuffer blob to play with.
     #         (This would arise if we're invoking `compile` from a SharkInference obj)
     temp_file_to_unlink = None
+
+    if isinstance(flatbuffer_blob_or_path, Path):
+        flatbuffer_blob_or_path = flatbuffer_blob_or_path.__str__()
     if (
         isinstance(flatbuffer_blob_or_path, str)
         and ".vmfb" in flatbuffer_blob_or_path