Fix TypeError: object of type 'NoneType' has no len() in dstack/_internal/backend/gcp/compute.py:513

cli/dstack/_internal/backend/gcp/compute.py

@@ -119,7 +119,7 @@ def get_supported_instances(self) -> List[InstanceType]:
             if row["spot"] == "True":  # any instance could be spot
                 continue
             instance_key = row["instance_name"]
-            gpus = None
+            gpus = []
             if int(row["gpu_count"]) > 0:
                 instance_key += f'-{row["gpu_count"]}x{row["gpu_name"]}-{row["gpu_memory"]}'
                 gpus = [

cli/dstack/_internal/backend/lambdalabs/compute.py

@@ -166,7 +166,7 @@ def _instance_type_data_to_instance_type(instance_type_data: Dict) -> Optional[I
     regions = [r["name"] for r in regions_data]
     instance_type_specs = instance_type["specs"]
     gpus = _get_instance_type_gpus(instance_type["name"])
-    if gpus is None:
+    if len(gpus) == 0:
         return None
     return InstanceType(
         instance_name=instance_type["name"],
@@ -181,10 +181,10 @@ def _instance_type_data_to_instance_type(instance_type_data: Dict) -> Optional[I
     )
 
 
-def _get_instance_type_gpus(instance_type_name: str) -> Optional[List[Gpu]]:
+def _get_instance_type_gpus(instance_type_name: str) -> List[Gpu]:
     gpu_data = _INSTANCE_TYPE_TO_GPU_DATA_MAP.get(instance_type_name)
     if gpu_data is None:
-        return None
+        return []
     return [
         Gpu(name=gpu_data["name"], memory_mib=gpu_data["memory_mib"])
         for _ in range(gpu_data["count"])

cli/dstack/_internal/core/runners.py

@@ -1,6 +1,6 @@
 from typing import List, Optional
 
-from pydantic import BaseModel
+from pydantic import BaseModel, validator
 
 from dstack._internal.core.job import Job
 
@@ -13,10 +13,14 @@ class Gpu(BaseModel):
 class Resources(BaseModel):
     cpus: int
     memory_mib: int
-    gpus: Optional[List[Gpu]]
+    gpus: List[Gpu]
     spot: bool
     local: bool
 
+    @validator("gpus")
+    def validate_gpus(cls, value):
+        return value or []
+
 
 class Runner(BaseModel):
     runner_id: str