Polish UI

examples/models/llama2/export_llama_lib.py

@@ -317,6 +317,13 @@ def build_args_parser() -> argparse.ArgumentParser:
         choices=["b4w"],
         help="This option is only for coreml: Use coreml quantization, e.g. b4w (for blockwise 4 bit weight)",
     )
+    parser.add_argument(
+        "--coreml-ios",
+        type=int,
+        default=15,
+        choices=(15, 16, 17, 18),
+        help="This option is only for coreml: The minimum iOS version to deploy",
+    )
     parser.add_argument(
         "--qnn",
         action="store_true",
@@ -533,8 +540,7 @@ def _export_llama(modelname, args) -> LLMEdgeManager:  # noqa: C901
 
     if args.coreml:
         coreml_partitioner = get_coreml_partitioner(
-            args.use_kv_cache and args.coreml_enable_state,
-            args.coreml_preserve_sdpa,
+            args.coreml_ios,
             args.embedding_quantize,
             args.pt2e_quantize,
             args.coreml_quantize,
@@ -810,7 +816,8 @@ def _get_source_transforms(  # noqa
             transforms.append(replace_causal_mask)
 
         elif args.coreml:
-            if args.coreml_preserve_sdpa:
+            # iOS 18 introduced fused sdpa op
+            if args.coreml_ios >= 18:
                 transforms.append(replace_sdpa_with_coreml_sdpa)
             else:
                 transforms.append(replace_sdpa_with_simple_sdpa)

extension/llm/export/partitioner_lib.py

@@ -56,8 +56,7 @@ def get_mps_partitioner(use_kv_cache: bool = False):
 
 
 def get_coreml_partitioner(
-    enable_state: bool = False,
-    preserve_sdpa: bool = True,
+    ios: int = 15,
     embedding_quantize: Optional[str] = None,
     pt2e_quantize: Optional[str] = None,
     coreml_quantize: Optional[str] = None,
@@ -75,29 +74,42 @@ def get_coreml_partitioner(
             "Please install the CoreML backend follwing https://pytorch.org/executorch/main/build-run-coreml.html"
         )
 
-    minimum_deployment_target = ct.target.iOS15
-    # In Core ML, stateful execution is introduced in iOS 18
-    if enable_state:
-        minimum_deployment_target = max(minimum_deployment_target, ct.target.iOS18)
-    # In Core ML, sdpa op is introduced in iOS 18
-    if preserve_sdpa:
-        minimum_deployment_target = max(minimum_deployment_target, ct.target.iOS18)
-    # In Core ML, quantization is introduced in iOS 16
-    if embedding_quantize is not None or pt2e_quantize is not None:
-        minimum_deployment_target = max(minimum_deployment_target, ct.target.iOS16)
-    # In Core ML, 8-bit activation quantization is introduced in iOS 17
-    if (
-        embedding_quantize is not None and int(embedding_quantize.split(",")[0]) == 8
-    ) or pt2e_quantize in ("coreml_8a_c8w", "coreml_baseline_8a_c8w"):
-        minimum_deployment_target = max(minimum_deployment_target, ct.target.iOS17)
-    # In Core ML, 4-bit weight compression is introduced in iOS 18
-    if (
-        (embedding_quantize is not None and int(embedding_quantize.split(",")[0]) == 4)
-        or pt2e_quantize in ("coreml_c4w", "coreml_8a_c4w", "coreml_baseline_8a_c4w")
-        or coreml_quantize == "b4w"
-    ):
-        minimum_deployment_target = max(minimum_deployment_target, ct.target.iOS18)
+    def _validate_ios_version() -> None:
+        assert ios in (15, 16, 17, 18)
 
+        if embedding_quantize is not None and ios < 18:
+            raise ValueError(
+                "In Core ML, per-block quantization is introduced in iOS 18"
+            )
+
+        use_quantization = pt2e_quantize is not None or coreml_quantize is not None
+        if use_quantization and ios < 16:
+            raise ValueError("In Core ML, quantization is introduced in iOS 16")
+
+        use_8a = (pt2e_quantize is not None and "8a" in pt2e_quantize) or (
+            coreml_quantize is not None and "8a" in coreml_quantize
+        )
+        if use_8a and ios < 17:
+            raise ValueError(
+                "In Core ML, 8-bit activation quantization is introduced in iOS 17"
+            )
+
+        use_4w = (pt2e_quantize is not None and "4w" in pt2e_quantize) or (
+            coreml_quantize is not None and "4w" in coreml_quantize
+        )
+        if use_4w and ios < 18:
+            raise ValueError(
+                "In Core ML, 4-bit weight compression is introduced in iOS 18"
+            )
+
+    _validate_ios_version()
+
+    minimum_deployment_target = {
+        15: ct.target.iOS15,
+        16: ct.target.iOS16,
+        17: ct.target.iOS17,
+        18: ct.target.iOS18,
+    }[ios]
     op_linear_quantizer_config = None
     if coreml_quantize == "b4w":
         op_linear_quantizer_config = {
@@ -107,7 +119,6 @@ def get_coreml_partitioner(
             "block_size": 32,
             "weight_threshold": 512,
         }
-
     compile_specs = CoreMLBackend.generate_compile_specs(  # pyre-fixme[16]
         minimum_deployment_target=minimum_deployment_target,
         compute_precision=ct.precision(ct.precision.FLOAT16.value),
@@ -116,9 +127,12 @@ def get_coreml_partitioner(
         model_type=CoreMLBackend.MODEL_TYPE.MODEL,  # pyre-fixme[16]
         op_linear_quantizer_config=op_linear_quantizer_config,
     )
+
+    take_over_mutable_buffer = minimum_deployment_target >= ct.target.iOS18
+
     return CoreMLPartitioner(  # pyre-fixme[16]
         compile_specs=compile_specs,
-        take_over_mutable_buffer=enable_state,
+        take_over_mutable_buffer=take_over_mutable_buffer,
     )