Improve msg error thrown when no sharding option found (pytorch#1693)

Summary:

Add additional info in error msg and warning logs to make debugging easier for users.

Reviewed By: henrylhtsang

Differential Revision: D53539635

torchrec/distributed/planner/enumerators.py

@@ -136,6 +136,7 @@ def enumerate(
                     for compute_kernel in self._filter_compute_kernels(
                         name,
                         sharder.compute_kernels(sharding_type, self._compute_device),
+                        sharding_type,
                     ):
                         (
                             shard_sizes,
@@ -179,7 +180,9 @@ def enumerate(
                 if not sharding_options_per_table:
                     raise RuntimeError(
                         "No available sharding type and compute kernel combination "
-                        f"after applying user provided constraints for {name}"
+                        f"after applying user provided constraints for {name}. "
+                        f"Module: {sharder_key}, sharder: {sharder.__class__.__name__}, compute device: {self._compute_device}. "
+                        f"To debug, search above for warning logs about no available sharding types/compute kernels for table: {name}"
                     )
 
                 sharding_options.extend(sharding_options_per_table)
@@ -222,6 +225,7 @@ def _filter_compute_kernels(
         self,
         name: str,
         allowed_compute_kernels: List[str],
+        sharding_type: str,
     ) -> List[str]:
         # for the log message only
         constrained_compute_kernels: List[str] = [
@@ -251,7 +255,7 @@ def _filter_compute_kernels(
                 f"constraints for {name}. Constrained compute kernels: "
                 f"{constrained_compute_kernels}, allowed compute kernels: "
                 f"{allowed_compute_kernels}, filtered compute kernels: "
-                f"{filtered_compute_kernels}. Please check if the constrained "
+                f"{filtered_compute_kernels}, sharding type: {sharding_type}. Please check if the constrained "
                 "compute kernels are too restrictive, if the sharder allows the "
                 "compute kernels, or if non-strings are passed in."
             )

torchrec/distributed/planner/tests/test_enumerators.py

@@ -746,8 +746,9 @@ def test_filter_compute_kernels_ebc(self) -> None:
         )
 
         sharder = EmbeddingBagCollectionSharder()
+        sharding_type = ShardingType.ROW_WISE.value
         allowed_compute_kernels = enumerator._filter_compute_kernels(
-            "table_0", sharder.compute_kernels(ShardingType.ROW_WISE.value, "cuda")
+            "table_0", sharder.compute_kernels(sharding_type, "cuda"), sharding_type
         )
 
         self.assertEqual(
@@ -774,8 +775,9 @@ def test_filter_compute_kernels_mch_ebc(self) -> None:
         )
 
         sharder = ManagedCollisionEmbeddingBagCollectionSharder()
+        sharding_type = ShardingType.ROW_WISE.value
         allowed_compute_kernels = enumerator._filter_compute_kernels(
-            "table_0", sharder.compute_kernels(ShardingType.ROW_WISE.value, "cuda")
+            "table_0", sharder.compute_kernels(sharding_type, "cuda"), sharding_type
         )
 
         self.assertEqual(
@@ -797,9 +799,10 @@ def test_filter_compute_kernels_mch_ebc_no_available(self) -> None:
         )
 
         sharder = ManagedCollisionEmbeddingBagCollectionSharder()
+        sharding_type = ShardingType.ROW_WISE.value
         with self.assertWarns(Warning):
             allowed_compute_kernels = enumerator._filter_compute_kernels(
-                "table_0", sharder.compute_kernels(ShardingType.ROW_WISE.value, "cuda")
+                "table_0", sharder.compute_kernels(sharding_type, "cuda"), sharding_type
             )
 
         self.assertEqual(allowed_compute_kernels, [])
@@ -900,7 +903,9 @@ def test_throw_ex_no_sharding_option_for_table(self) -> None:
         with self.assertRaises(Exception) as context:
             _ = enumerator.enumerate(self.model, [sharder])
 
-        self.assertTrue(
-            "No available sharding type and compute kernel combination after applying user provided constraints for table_1"
-            in str(context.exception)
+        self.assertEqual(
+            str(context.exception),
+            "No available sharding type and compute kernel combination after applying user provided constraints for table_1. "
+            "Module: torchrec.modules.embedding_modules.EmbeddingBagCollection, sharder: CWSharder, compute device: cuda. "
+            "To debug, search above for warning logs about no available sharding types/compute kernels for table: table_1",
         )