Add coreml recipes

backends/apple/coreml/TARGETS

@@ -58,6 +58,20 @@ runtime.python_library(
     ],
 )
 
+runtime.python_library(
+    name = "recipes",
+    srcs = glob([
+        "recipes/*.py",
+    ]),
+    deps = [
+        ":partitioner",
+        ":quantizer",
+    ],
+    visibility = [
+        "@EXECUTORCH_CLIENTS",
+    ],
+)
+
 runtime.cxx_python_extension(
     name = "executorchcoreml",
     srcs = [

backends/apple/coreml/recipes/__init__.py

@@ -0,0 +1,5 @@
+from .recipes import iphone_coreml_et_recipe
+
+__all__ = [
+    "iphone_coreml_et_recipe",
+]

backends/apple/coreml/recipes/recipes.py

@@ -0,0 +1,69 @@
+# (c) Meta Platforms, Inc. and affiliates. Confidential and proprietary.
+
+# pyre-strict
+import torch
+
+from executorch.exir import ExportRecipe
+from executorch.exir import EdgeCompileConfig, ExecutorchBackendConfig
+
+def iphone_coreml_et_recipe(ios: int = 17, compute_unit: str = "CPU_ONLY") -> ExportRecipe:
+    import coremltools as ct
+    from coremltools.optimize.torch.quantization.quantization_config import (
+        LinearQuantizerConfig,
+        QuantizationScheme,
+    )
+    from executorch.backends.apple.coreml.compiler import CoreMLBackend
+    from executorch.backends.apple.coreml.partition import CoreMLPartitioner
+    from executorch.backends.apple.coreml.quantizer import CoreMLQuantizer
+
+    # TODO: Add compute precision, compute unit, and model type
+    quantization_config = LinearQuantizerConfig.from_dict(
+        {
+            "global_config": {
+                "quantization_scheme": QuantizationScheme.affine,
+                "activation_dtype": torch.quint8,
+                "weight_dtype": torch.qint8,
+                "weight_per_channel": True,
+            }
+        }
+    )
+    minimum_deployment_target = {
+        15: ct.target.iOS15,
+        16: ct.target.iOS16,
+        17: ct.target.iOS17,
+        18: ct.target.iOS18,
+    }[ios]
+    compute_unit_types = ["CPU_ONLY", "CPU_AND_NE", "CPU_AND_GPU", "ALL"]
+    assert (
+        compute_unit in compute_unit_types
+    ), f"Invalid compute unit: {compute_unit}, should be one of {compute_unit_types}"
+    if compute_unit == "CPU_ONLY":
+        compute_unit_specs = ct.ComputeUnit[ct.ComputeUnit.CPU_ONLY.name.upper()]
+    elif compute_unit == "CPU_AND_NE":
+        compute_unit_specs = ct.ComputeUnit[ct.ComputeUnit.CPU_AND_NE.name.upper()]
+    elif compute_unit == "CPU_AND_GPU":
+        compute_unit_specs = ct.ComputeUnit[ct.ComputeUnit.CPU_AND_GPU.name.upper()]
+    else:  # compute_unit == "ALL"
+        compute_unit_specs = ct.ComputeUnit[ct.ComputeUnit.ALL.name.upper()]
+    compile_specs = CoreMLBackend.generate_compile_specs(
+        minimum_deployment_target=minimum_deployment_target,
+        compute_precision=ct.precision(ct.precision.FLOAT16.value),
+        compute_unit=compute_unit_specs,
+        model_type=CoreMLBackend.MODEL_TYPE.MODEL,
+    )
+    take_over_mutable_buffer = minimum_deployment_target >= ct.target.iOS18
+    partitioner = CoreMLPartitioner(
+        compile_specs=compile_specs,
+        take_over_mutable_buffer=take_over_mutable_buffer,
+    )
+    return ExportRecipe(
+        "iphone_coreml",
+        quantizer=CoreMLQuantizer(quantization_config),
+        partitioners=[partitioner],
+        edge_compile_config=EdgeCompileConfig(
+            _check_ir_validity=False,
+            _skip_dim_order=True,
+        ),
+        edge_transform_passes=[],
+        executorch_backend_config=ExecutorchBackendConfig(),
+    )

extension/llm/export/TARGETS

@@ -28,6 +28,7 @@ runtime.python_library(
         "//caffe2:torch",
         "//executorch/backends/apple/coreml:backend",
         "//executorch/backends/apple/coreml:partitioner",
+        "//executorch/backends/apple/coreml:recipes",
         "//executorch/backends/apple/mps:partitioner",
         "//executorch/backends/qualcomm/partition:partition",
         "//executorch/backends/qualcomm/quantizer:quantizer",