ExllamaV2: Cleanup log placements

Move the large import errors into the check functions themselves.
This helps reduce the difficulty in interpreting where errors are
coming from.

Signed-off-by: kingbri <bdashore3@proton.me>

backends/exllamav2/model.py

@@ -202,35 +202,11 @@ class ExllamaV2Container:
 
         # Check whether the user's configuration supports paged attention
         if not hardware_supports_flash_attn(gpu_device_list):
-            logger.warning(
-                "An unsupported GPU is found in this configuration. "
-                "Switching to compatibility mode. \n"
-                "This disables parallel batching "
-                "and features that rely on it (ex. CFG). \n"
-                "To disable compatability mode, all GPUs must be ampere "
-                "(30 series) or newer. AMD GPUs are not supported."
-            )
             self.config.no_flash_attn = True
             self.paged = False
             self.max_batch_size = 1
             torch.backends.cuda.enable_flash_sdp(False)
         elif not supports_paged_attn():
-            logger.warning(
-                "Flash attention version >=2.5.7 "
-                "is required to use paged attention. "
-                "Switching to compatibility mode. \n"
-                "This disables parallel batching "
-                "and features that rely on it (ex. CFG). \n"
-                "Please upgrade your environment by running a start script "
-                "(start.bat or start.sh)\n\n"
-                "Or you can manually run a requirements update "
-                "using the following command:\n\n"
-                "For CUDA 12.1:\n"
-                "pip install --upgrade .[cu121]\n\n"
-                "For CUDA 11.8:\n"
-                "pip install --upgrade .[cu118]\n\n"
-                "NOTE: Windows users must use CUDA 12.x to use flash-attn."
-            )
             self.config.no_flash_attn = True
             self.paged = False
             self.max_batch_size = 1

backends/exllamav2/utils.py

@@ -10,21 +10,23 @@ def check_exllama_version():
     required_version = version.parse("0.1.5")
     current_version = version.parse(package_version("exllamav2").split("+")[0])
 
+    unsupported_message = (
+        f"ERROR: TabbyAPI requires ExLlamaV2 {required_version} "
+        f"or greater. Your current version is {current_version}.\n"
+        "Please upgrade your environment by running a start script "
+        "(start.bat or start.sh)\n\n"
+        "Or you can manually run a requirements update "
+        "using the following command:\n\n"
+        "For CUDA 12.1:\n"
+        "pip install --upgrade .[cu121]\n\n"
+        "For CUDA 11.8:\n"
+        "pip install --upgrade .[cu118]\n\n"
+        "For ROCm:\n"
+        "pip install --upgrade .[amd]\n\n"
+    )
+
     if current_version < required_version:
-        raise SystemExit(
-            f"ERROR: TabbyAPI requires ExLlamaV2 {required_version} "
-            f"or greater. Your current version is {current_version}.\n"
-            "Please upgrade your environment by running a start script "
-            "(start.bat or start.sh)\n\n"
-            "Or you can manually run a requirements update "
-            "using the following command:\n\n"
-            "For CUDA 12.1:\n"
-            "pip install --upgrade .[cu121]\n\n"
-            "For CUDA 11.8:\n"
-            "pip install --upgrade .[cu118]\n\n"
-            "For ROCm:\n"
-            "pip install --upgrade .[amd]\n\n"
-        )
+        raise SystemExit(unsupported_message)
     else:
         logger.info(f"ExllamaV2 version: {current_version}")
 
@@ -37,11 +39,23 @@ def hardware_supports_flash_attn(gpu_device_list: list[int]):
     AMD is also unsupported until ROCm updates its FA2 fork
     """
 
+    # Logged message if unsupported
+    unsupported_message = (
+        "An unsupported GPU is found in this configuration. "
+        "Switching to compatibility mode. \n"
+        "This disables parallel batching "
+        "and features that rely on it (ex. CFG). \n"
+        "To disable compatability mode, all GPUs must be ampere "
+        "(30 series) or newer. AMD GPUs are not supported."
+    )
+
     min_compute_capability = min(
         torch.cuda.get_device_capability(device=device_idx)[0]
         for device_idx in gpu_device_list
     )
+
     if torch.version.hip or min_compute_capability < 8:
+        logger.warning(unsupported_message)
         return False
     else:
         return True
@@ -50,13 +64,33 @@ def hardware_supports_flash_attn(gpu_device_list: list[int]):
 def supports_paged_attn():
     """Check whether the user's flash-attn version supports paged mode"""
 
+    # Logged message if unsupported
+    unsupported_message = (
+        "Flash attention version >=2.5.7 "
+        "is required to use paged attention. "
+        "Switching to compatibility mode. \n"
+        "This disables parallel batching "
+        "and features that rely on it (ex. CFG). \n"
+        "Please upgrade your environment by running a start script "
+        "(start.bat or start.sh)\n\n"
+        "Or you can manually run a requirements update "
+        "using the following command:\n\n"
+        "For CUDA 12.1:\n"
+        "pip install --upgrade .[cu121]\n\n"
+        "For CUDA 11.8:\n"
+        "pip install --upgrade .[cu118]\n\n"
+        "NOTE: Windows users must use CUDA 12.x to use flash-attn."
+    )
+
     required_version = version.parse("2.5.7")
     try:
         current_version = version.parse(package_version("flash-attn").split("+")[0])
     except PackageNotFoundError:
+        logger.warning(unsupported_message)
         return False
 
     if current_version < required_version:
+        logger.warning(unsupported_message)
         return False
     else:
         return True