Refactor the shark_runner shark_inference to only support mlir_modules.

1. The shark_inference is divided into shark_importer and
   shark_inference.
2. All the tank/pytorch tests have been updated.

shark/iree_utils/_common.py

@@ -75,3 +75,17 @@ def check_device_drivers(device):
         return True
 
     return False
+
+
+# Installation info for the missing device drivers.
+def device_driver_info(device):
+    if device in ["gpu", "cuda"]:
+        print(
+            "nvidia-smi not found, please install the required drivers from https://www.nvidia.in/Download/index.aspx?lang=en-in"
+        )
+    elif device in ["metal", "vulkan"]:
+        print(
+            "vulkaninfo not found, Install from https://vulkan.lunarg.com/sdk/home or your distribution"
+        )
+    else:
+        print(f"{device} is not supported.")

shark/iree_utils/compile_utils.py

@@ -14,7 +14,6 @@
 import iree.runtime as ireert
 import iree.compiler as ireec
 from shark.iree_utils._common import IREE_DEVICE_MAP, IREE_TARGET_MAP
-from shark.model_annotation import *
 import numpy as np
 import os
 
@@ -157,23 +156,7 @@ def export_module_to_mlir_file(module, frontend, directory: str):
 
 def get_results(compiled_vm, input, config, frontend="torch"):
     """Runs a .vmfb file given inputs and config and returns output."""
-    device_inputs = input
-    if frontend in ["torch", "pytorch"]:
-        device_inputs = [ireert.asdevicearray(config.device, a) for a in input]
-    if frontend in ["tensorflow", "tf", "tflite", "tflite-tosa"]:
-        device_inputs = []
-        for a in input:
-            if isinstance(a, list):
-                device_inputs.append(
-                    [
-                        ireert.asdevicearray(
-                            config.device, val, dtype=val.dtype
-                        )
-                        for val in a
-                    ]
-                )
-            else:
-                device_inputs.append(ireert.asdevicearray(config.device, a))
+    device_inputs = [ireert.asdevicearray(config.device, a) for a in input]
     result = compiled_vm(*device_inputs)
     result_tensors = []
     if isinstance(result, tuple):