[Target] Improve TVM Target related items (#45)

* Refactor target_detector.py to improve CUDA target handling

* chore: Add get_all_nvidia_targets function to target_detector.py, and refactor the device mismatch print

python/bitblas/utils/__init__.py

@@ -2,4 +2,4 @@
 # Licensed under the MIT License.
 from .post_process import match_global_kernel, tensor_replace_dp4a, tensor_remove_make_int4  # noqa: F401
 from .tensor_adapter import tvm_tensor_to_torch, lazy_tvm_tensor_to_torch, lazy_torch_to_tvm_tensor  # noqa: F401
-from .target_detector import auto_detect_nvidia_target  # noqa: F401
+from .target_detector import get_all_nvidia_targets, auto_detect_nvidia_target  # noqa: F401

python/bitblas/utils/target_detector.py

@@ -2,13 +2,19 @@
 # Licensed under the MIT License.
 
 import subprocess
+from typing import List
 from thefuzz import process
 from tvm.target import Target
 from tvm.target.tag import list_tags
 
 import logging
+
 logger = logging.getLogger(__name__)
 
+TARGET_MISSING_ERROR = (
+    "TVM target not found. Please set the TVM target environment variable using `export TVM_TARGET=<target>`, "
+    "where <target> is one of the available targets can be found in the output of `tools/get_available_targets.py`."
+)
 
 def get_gpu_model_from_nvidia_smi():
     """
@@ -41,13 +47,21 @@ def find_best_match(tags, query):
     def check_target(best, default):
         return best if Target(best).arch == Target(default).arch else default
 
-    if check_target(best_match, "cuda"):
+    if check_target(best_match, "cuda") == best_match:
         return best_match if score >= MATCH_THRESHOLD else "cuda"
     else:
-        logger.info(f"Best match '{best_match}' is not a valid CUDA target, falling back to 'cuda'")
+        logger.warning(TARGET_MISSING_ERROR)
         return "cuda"
 
 
+def get_all_nvidia_targets() -> List[str]:
+    """
+    Returns all available NVIDIA targets.
+    """
+    all_tags = list_tags()
+    return [tag for tag in all_tags if "nvidia" in tag]
+
+
 def auto_detect_nvidia_target() -> str:
     """
     Automatically detects the NVIDIA GPU architecture to set the appropriate TVM target.

requirements-dev.txt

@@ -27,3 +27,4 @@ scipy
 tornado
 torch
 thefuzz
+tabulate

requirements.txt

@@ -20,3 +20,4 @@ scipy
 tornado
 torch
 thefuzz
+tabulate

tools/get_available_targets.py

@@ -0,0 +1,17 @@
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+
+from bitblas.utils import get_all_nvidia_targets
+from tabulate import tabulate
+
+def main():
+    # Get all available Nvidia targets
+    targets = get_all_nvidia_targets()
+
+    # Print available targets to console in a table format
+    table = [[i + 1, target] for i, target in enumerate(targets)]
+    headers = ["Index", "Target"]
+    print(tabulate(table, headers, tablefmt="pretty"))
+
+if __name__ == "__main__":
+    main()