Update

[ghstack-poisoned]

Author: swolchok

.github/workflows/trunk.yml

@@ -536,9 +536,8 @@ jobs:
         git clone https://github.com/huggingface/optimum-executorch
         cd optimum-executorch
         # There is no release yet, for CI stability, always test from the same commit on main
-        git checkout 6a7e83f3eee2976fa809335bfb78a45b1ea1cb25
-        pip install .
-        pip install accelerate sentencepiece
+        git checkout 1907349524b5f2d61f9c04d2e985da826d4308ba
+        pip install .[tests]
         pip list
         echo "::endgroup::"
 

Package.swift

@@ -82,5 +82,24 @@ let package = Package(
           (value["libraries"] as? [String] ?? []).map { .linkedLibrary($0) }
       ),
     ]
-  }
+  } + [
+    .testTarget(
+      name: "tests",
+      dependencies: [
+        .target(name: "executorch_debug"),
+        .target(name: "kernels_portable"),
+      ],
+      path: "extension/apple/ExecuTorch/__tests__",
+      resources: [
+        .copy("resources/add.pte")
+      ],
+      linkerSettings: [
+        .linkedLibrary("c++"),
+        .unsafeFlags([
+          "-Xlinker", "-force_load",
+          "-Xlinker", "cmake-out/kernels_portable.xcframework/macos-arm64/libkernels_portable_macos.a",
+        ])
+      ]
+    )
+  ]
 )

backends/apple/coreml/CMakeLists.txt

@@ -25,6 +25,8 @@ endif()
 
 option(COREML_BUILD_EXECUTOR_RUNNER "Build CoreML executor runner." OFF)
 
+set(CMAKE_OSX_DEPLOYMENT_TARGET 10.15)
+
 # inmemoryfs sources
 set(INMEMORYFS_SOURCES
     runtime/inmemoryfs/inmemory_filesystem.cpp
@@ -229,3 +231,18 @@ install(
   INCLUDES
   DESTINATION ${_common_include_directories}
 )
+
+# We only care about building the pybinding when building for macOS wheels.
+if(EXECUTORCH_BUILD_COREML AND EXECUTORCH_BUILD_PYBIND)
+  if(NOT TARGET pybind11::pybind11)
+    add_subdirectory(${EXECUTORCH_ROOT}/third-party/pybind11 ${CMAKE_CURRENT_BINARY_DIR}/pybind11)
+  endif()
+
+  pybind11_add_module(executorchcoreml SHARED runtime/inmemoryfs/inmemory_filesystem_py.cpp)
+
+  target_compile_options(executorchcoreml PRIVATE -mmacosx-version-min=${CMAKE_OSX_DEPLOYMENT_TARGET})
+  if(CMAKE_BUILD_TYPE STREQUAL "Debug" OR CMAKE_BUILD_TYPE STREQUAL "RelWithDebInfo")
+    target_compile_options(executorchcoreml PRIVATE -g)
+  endif()
+  target_link_libraries(executorchcoreml PRIVATE coreml_util coreml_inmemoryfs)
+endif()

backends/apple/coreml/runtime/delegate/ETCoreMLModelManager.mm

@@ -208,7 +208,7 @@ void set_outputs(std::vector<executorchcoreml::MultiArray>& outputs,
                                     const inmemoryfs::InMemoryFileSystem *inmemory_fs,
                                     NSError * __autoreleasing *error) {
     NSError *local_error = nil;
-    if (![fm createDirectoryAtURL:dst_url withIntermediateDirectories:NO attributes:@{} error:error]) {
+    if (![fm createDirectoryAtURL:dst_url withIntermediateDirectories:YES attributes:@{} error:error]) {
         ETCoreMLLogUnderlyingErrorAndSetNSError(error,
                                                 ETCoreMLErrorModelSaveFailed,
                                                 local_error,

extension/apple/ExecuTorch/Internal/ExecuTorchUtils.h

@@ -7,3 +7,40 @@
  */
 
 #import <Foundation/Foundation.h>
+
+#ifdef __cplusplus
+
+#import <executorch/runtime/core/exec_aten/exec_aten.h>
+
+namespace executorch::extension::utils {
+using namespace aten;
+
+/**
+ * Deduces the scalar type for a given NSNumber based on its type encoding.
+ *
+ * @param number The NSNumber instance whose scalar type is to be deduced.
+ * @return The corresponding ScalarType.
+ */
+static inline ScalarType deduceScalarType(NSNumber *number) {
+  auto type = [number objCType][0];
+  type = (type >= 'A' && type <= 'Z') ? type + ('a' - 'A') : type;
+  if (type == 'c') {
+    return ScalarType::Byte;
+  } else if (type == 's') {
+    return ScalarType::Short;
+  } else if (type == 'i') {
+    return ScalarType::Int;
+  } else if (type == 'q' || type == 'l') {
+    return ScalarType::Long;
+  } else if (type == 'f') {
+    return ScalarType::Float;
+  } else if (type == 'd') {
+    return ScalarType::Double;
+  }
+  ET_CHECK_MSG(false, "Unsupported type: %c", type);
+  return ScalarType::Undefined;
+}
+
+} // namespace executorch::extension::utils
+
+#endif // __cplusplus

extension/apple/ExecuTorch/__tests__/ModuleTest.swift

@@ -11,9 +11,16 @@
 import XCTest
 
 class ModuleTest: XCTestCase {
+  var resourceBundle: Bundle {
+#if SWIFT_PACKAGE
+    return Bundle.module
+#else
+    return Bundle(for: type(of: self))
+#endif
+  }
+  
   func test() throws {
-    let bundle = Bundle(for: type(of: self))
-    guard let modelPath = bundle.path(forResource: "add", ofType: "pte") else {
+    guard let modelPath = resourceBundle.path(forResource: "add", ofType: "pte") else {
       XCTFail("Couldn't find the model file")
       return
     }

extension/flat_tensor/serialize/serialize.py

@@ -10,29 +10,33 @@
 import os
 import tempfile
 from dataclasses import dataclass
-from typing import ClassVar, Dict, List, Literal, Optional
+from typing import ClassVar, Dict, List, Literal, Optional, Sequence
 
 import pkg_resources
 from executorch.exir._serialize._cord import Cord
 from executorch.exir._serialize._dataclass import _DataclassEncoder, _json_to_dataclass
 
 from executorch.exir._serialize._flatbuffer import _flatc_compile, _flatc_decompile
 from executorch.exir._serialize._program import _insert_flatbuffer_header
-from executorch.exir._serialize.data_serializer import DataPayload, DataSerializer
+from executorch.exir._serialize.data_serializer import (
+    DataPayload,
+    DataSerializer,
+    TensorEntry,
+)
 
 from executorch.exir._serialize.padding import aligned_size, pad_to, padding_required
 
-# Byte order of numbers written to flat tensor headers. Always little-endian
-# regardless of the host system, since all commonly-used modern CPUs are little
-# endian.
-_HEADER_BYTEORDER: Literal["little"] = "little"
-
 from executorch.extension.flat_tensor.serialize.flat_tensor_schema import (
     DataSegment,
     FlatTensor,
     TensorMetadata,
 )
 
+# Byte order of numbers written to flat tensor headers. Always little-endian
+# regardless of the host system, since all commonly-used modern CPUs are little
+# endian.
+_HEADER_BYTEORDER: Literal["little"] = "little"
+
 
 def _serialize_to_flatbuffer(flat_tensor: FlatTensor) -> Cord:
     """Serializes a FlatTensor to a flatbuffer and returns the serialized data."""
@@ -209,6 +213,62 @@ def _get_extended_header(flat_tensor_data: bytes) -> Optional[FlatTensorHeader]:
     return None
 
 
+def _extract_tensors(
+    fqn_to_tensor: Dict[str, TensorEntry],
+    buffers: Sequence[bytes],
+    segments: List[Cord],
+    tensor_alignment: int,
+) -> List[TensorMetadata]:
+    """Places tensors into a single segment, aligned to tensor_alignment within
+        the segment.
+
+    Args:
+        fqn_to_tensor: A map from fully qualified names to tensor entries.
+        buffers: A sequence of tensor buffers.
+        segments: A list of segments to append the tensor data to. Modified in-place.
+        tensor_alignment: The alignment of the tensor data.
+
+    Returns:
+        A list of TensorMetadata, which describes the tensors in the segment.
+    """
+    tensor_data: Cord = Cord()
+    tensors: List[TensorMetadata] = []
+    # {idx, offset}
+    saved_offsets: Dict[int, int] = {}
+    for fqn, tensor_entry in fqn_to_tensor.items():
+        assert tensor_entry.layout is not None
+        # Check index into the tensor buffers is valid.
+        assert tensor_entry.buffer_index < len(
+            buffers
+        ), f"Invalid index {tensor_entry.buffer_index} is greater than tensor buffer size {len(buffers)}."
+
+        # Check if the tensor has already been appended to the flat_tensor_data.
+        offset = saved_offsets.get(tensor_entry.buffer_index, -1)
+        if offset == -1:
+            if len(tensor_data) > 0:
+                # Add padding to round off the previous tensor offset.
+                pad_length = padding_required(len(tensor_data), tensor_alignment)
+                tensor_data.append(b"\x00" * pad_length)
+            # Add to saved offsets.
+            offset = len(tensor_data)
+            saved_offsets[tensor_entry.buffer_index] = offset
+            # Append to flat_tensor_data at the offset.
+            tensor_data.append(buffers[tensor_entry.buffer_index])
+
+        tensors.append(
+            TensorMetadata(
+                fully_qualified_name=fqn,
+                scalar_type=tensor_entry.layout.scalar_type,
+                sizes=tensor_entry.layout.sizes,
+                dim_order=tensor_entry.layout.dim_order,
+                segment_index=len(segments),
+                offset=offset,
+            )
+        )
+    segments.append(tensor_data)
+    return tensors
+
+
 class FlatTensorSerializer(DataSerializer):
     """A concrete implementation of the DataSerializer interface that
     serializes and deserializes data to/from the FlatTensor format.
@@ -227,61 +287,45 @@ def serialize(
         self,
         data: DataPayload,
     ) -> Cord:
-        """Serializes a list of tensor metadata and tensors into a blob."""
-
-        flat_tensor_metadata: List[TensorMetadata] = []
-        flat_tensor_data: Cord = Cord()
-
-        # {idx, offset}
-        saved_offsets: Dict[int, int] = {}
-
-        for fqn, tensor_entry in data.fqn_to_tensor.items():
-            assert tensor_entry.layout is not None
-            # Check index into the tensor buffers is valid.
-            assert tensor_entry.buffer_index < len(
-                data.buffers
-            ), f"Invalid index {tensor_entry.buffer_index} is greater than tensor buffer size {len(data.buffers)}."
-
-            # Check if the tensor has already been appended to the flat_tensor_data.
-            offset = saved_offsets.get(tensor_entry.buffer_index, -1)
-            if offset == -1:
-                if len(flat_tensor_data) > 0:
-                    # Add padding to round off the previous tensor offset.
-                    pad_length = padding_required(
-                        len(flat_tensor_data), self.config.tensor_alignment
-                    )
-                    flat_tensor_data.append(b"\x00" * pad_length)
-                # Add to saved offsets.
-                offset = len(flat_tensor_data)
-                saved_offsets[tensor_entry.buffer_index] = offset
-                # Append to flat_tensor_data at the offset.
-                flat_tensor_data.append(data.buffers[tensor_entry.buffer_index])
-
-            flat_tensor_metadata.append(
-                TensorMetadata(
-                    fully_qualified_name=fqn,
-                    scalar_type=tensor_entry.layout.scalar_type,
-                    sizes=tensor_entry.layout.sizes,
-                    dim_order=tensor_entry.layout.dim_order,
-                    segment_index=0,
-                    offset=offset,
+        """Serializes a list of tensors and named data into a blob."""
+
+        segments: List[Cord] = []
+        tensors = _extract_tensors(
+            data.fqn_to_tensor,
+            data.buffers,
+            segments,
+            self.config.tensor_alignment,
+        )
+
+        data_segments: List[DataSegment] = []
+        segment_data = Cord()
+        for segment in segments:
+            prev_end = (
+                (data_segments[-1].offset + data_segments[-1].size)
+                if data_segments
+                else 0
+            )
+            data_segments.append(
+                DataSegment(
+                    offset=aligned_size(prev_end, self.config.segment_alignment),
+                    size=len(segment),
                 )
             )
-
-        # Pad flat_tensor_data to segment alignment.
-        segment_pad_length = padding_required(
-            len(flat_tensor_data), self.config.segment_alignment
-        )
-        if segment_pad_length > 0:
-            flat_tensor_data.append(b"\x00" * segment_pad_length)
+            # Pad segment_data to segment alignment.
+            segment_pad_length = padding_required(
+                len(segment_data), self.config.segment_alignment
+            )
+            if segment_pad_length > 0:
+                segment_data.append(b"\x00" * segment_pad_length)
+            segment_data.append(segment)
 
         # Create FlatTensor, which describes of the contents of the file and
         # points to all the data segments. It will be serialized to flatbuffer.
         flat_tensor = FlatTensor(
             version=0,  # Keep in sync with c++ version number in serialize.h
             tensor_alignment=self.config.tensor_alignment,
-            tensors=flat_tensor_metadata,
-            segments=[DataSegment(offset=0, size=len(flat_tensor_data))],
+            tensors=tensors,
+            segments=data_segments,
             named_data=[],
         )
 
@@ -307,7 +351,7 @@ def serialize(
             flatbuffer_offset=padded_header_length,
             flatbuffer_size=len(flatbuffer_payload),
             segment_base_offset=segment_base_offset,
-            segment_data_size=len(flat_tensor_data),
+            segment_data_size=len(segment_data),
         ).to_bytes()
 
         # Pad header and payload to segment alignment.
@@ -327,15 +371,15 @@ def serialize(
         assert eh.flatbuffer_size == original_flatbuffer_payload_size
         assert eh.segment_base_offset == segment_base_offset
         assert eh.flatbuffer_offset == padded_header_length
-        assert eh.segment_data_size == len(flat_tensor_data)
+        assert eh.segment_data_size == len(segment_data)
 
         del header_data
         del flatbuffer_payload
 
         # Place everything into one segment.
         payload = Cord()
         payload.append(injected_flatbuffer_data)
-        payload.append(flat_tensor_data)
+        payload.append(segment_data)
 
         return payload
 

requirements-examples.txt

@@ -2,4 +2,4 @@
 # TODO: Make each example publish its own requirements.txt
 timm == 1.0.7
 torchsr == 1.0.4
-transformers ==4.47.1
+transformers ==4.50.1

scripts/build_apple_frameworks.sh

@@ -206,7 +206,7 @@ cmake_build() {
     cmake --build . \
         --config "$mode" \
         --verbose
-    cd ..
+    cd -
 }
 
 for index in ${!PLATFORMS[*]}; do
@@ -285,4 +285,9 @@ done
 
 rm -rf "$HEADERS_PATH"
 
+echo "Running tests"
+
+cd "$SOURCE_ROOT_DIR"
+swift test
+
 echo "Build succeeded!"