fixed formatting

Author: elizjo

ads/aqua/modeldeployment/deployment.py

@@ -64,7 +64,11 @@
     ModelDeploymentConfigSummary,
     MultiModelDeploymentConfigLoader,
 )
-from ads.aqua.modeldeployment.constants import DEFAULT_POLL_INTERVAL, DEFAULT_WAIT_TIME, SHAPE_MAP
+from ads.aqua.modeldeployment.constants import (
+    DEFAULT_POLL_INTERVAL,
+    DEFAULT_WAIT_TIME,
+    SHAPE_MAP,
+)
 from ads.aqua.modeldeployment.entities import (
     AquaDeployment,
     AquaDeploymentDetail,
@@ -1282,28 +1286,25 @@ def valid_compute_shapes(self, **kwargs) -> List["ComputeShapeSummary"]:
                 oci_shape = set_user_shapes.get(name)
 
                 compute_shape = ComputeShapeSummary(
-                        available=True,
-                        core_count= oci_shape.core_count,
-                        memory_in_gbs= oci_shape.memory_in_gbs,
-                        shape_series= SHAPE_MAP.get(oci_shape.shape_series, "GPU"),
-                        name= oci_shape.name,
-                        gpu_specs= spec
-                    )
+                    available=True,
+                    core_count=oci_shape.core_count,
+                    memory_in_gbs=oci_shape.memory_in_gbs,
+                    shape_series=SHAPE_MAP.get(oci_shape.shape_series, "GPU"),
+                    name=oci_shape.name,
+                    gpu_specs=spec,
+                )
             else:
                 compute_shape = ComputeShapeSummary(
-                        available=False, name=name, shape_series="GPU", gpu_specs=spec
-                    )
+                    available=False, name=name, shape_series="GPU", gpu_specs=spec
+                )
             valid_shapes.append(compute_shape)
 
         valid_shapes.sort(
             key=lambda shape: shape.gpu_specs.gpu_memory_in_gbs, reverse=True
         )
         return valid_shapes
 
-
-    def recommend_shape(
-        self, **kwargs
-    ) -> Union[Table, ShapeRecommendationReport]:
+    def recommend_shape(self, **kwargs) -> Union[Table, ShapeRecommendationReport]:
         """
         For the CLI (set generate_table = True), generates the table (in rich diff) with valid
         GPU deployment shapes for the provided model and configuration.
@@ -1334,9 +1335,6 @@ def recommend_shape(
         AquaValueError
             If model type is unsupported by tool (no recommendation report generated)
         """
-        # generate_table = kwargs.pop(
-        #     "generate_table", True
-        # )  # Generate rich diff table by default
         compartment_id = kwargs.get("compartment_id", COMPARTMENT_OCID)
 
         kwargs["shapes"] = self.valid_compute_shapes(compartment_id=compartment_id)

ads/aqua/shaperecommend/recommend.py

@@ -90,8 +90,9 @@ def which_shapes(self, **kwargs) -> Union[ShapeRecommendationReport, Table]:
             )
 
             if request.generate_table and shape_recommendation_report.recommendations:
-                shape_recommendation_report = self._rich_diff_table(shape_recommendation_report)
-
+                shape_recommendation_report = self._rich_diff_table(
+                    shape_recommendation_report
+                )
 
         # custom error to catch model incompatibility issues
         except AquaRecommendationError as error:

ads/aqua/shaperecommend/shape_report.py

@@ -23,9 +23,12 @@ class RequestRecommend(BaseModel):
     shapes: List[ComputeShapeSummary] = Field(
         ..., description="The list of shapes on OCI."
     )
-    generate_table : Optional[bool] = Field(
-        True, description="True - to generate the rich diff Table, False - generate the JSON response"
-    ),
+    generate_table: Optional[bool] = (
+        Field(
+            True,
+            description="True - to generate the rich diff Table, False - generate the JSON response",
+        ),
+    )
     compartment_id: Optional[str] = Field(
         COMPARTMENT_OCID, description="The OCID of user's compartment"
     )