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Summary: Add Stateful FC Cortex-m linearOps #14252

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Summary: Add Stateful FC Cortex-m linearOps #14252

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84 changes: 52 additions & 32 deletions backends/cortex_m/CMakeLists.txt
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -12,7 +12,7 @@ if(NOT CMAKE_CXX_STANDARD)
set(CMAKE_CXX_STANDARD 17)
endif()

# Source root directory for executorch.
# Source root directory for executorch
if(NOT EXECUTORCH_ROOT)
set(EXECUTORCH_ROOT ${CMAKE_CURRENT_SOURCE_DIR}/../..)
endif()
Expand All @@ -21,70 +21,90 @@ include(${EXECUTORCH_ROOT}/tools/cmake/Utils.cmake)
include(${EXECUTORCH_ROOT}/tools/cmake/Codegen.cmake)
include(FetchContent)

# CMSIS-NN version to download
# CMSIS-NN configuration with dynamic path detection
set(CMSIS_NN_VERSION
"v4.1.0"
"v7.0.0"
CACHE STRING "CMSIS-NN version to download"
)

# Declare CMSIS-NN as a FetchContent project
FetchContent_Declare(
cmsis_nn
GIT_REPOSITORY https://github.com/ARM-software/CMSIS-NN.git
GIT_TAG ${CMSIS_NN_VERSION}
set(CMSIS_NN_LOCAL_PATH
""
CACHE PATH "Path to existing local CMSIS-NN installation"
)

# Download and make CMSIS-NN available
FetchContent_MakeAvailable(cmsis_nn)
# Try to find existing / local CMSIS-NN installation. This is useful for
# debugging and testing with local changes. This is not common, as the CMSIS-NN
# library is downloaded via FetchContent in the default/regular case.
if(CMSIS_NN_LOCAL_PATH AND EXISTS "${CMSIS_NN_LOCAL_PATH}")
message(STATUS "Using CMSIS-NN from specified path: ${CMSIS_NN_LOCAL_PATH}")
add_subdirectory(${CMSIS_NN_LOCAL_PATH} cmsis_nn_build)
else()
# Use FetchContent with automatic fallback
message(STATUS "Using CMSIS-NN via FetchContent")

FetchContent_Declare(
cmsis_nn
GIT_REPOSITORY https://github.com/ARM-software/CMSIS-NN.git
GIT_TAG ${CMSIS_NN_VERSION}
GIT_SHALLOW TRUE
)

FetchContent_GetProperties(cmsis_nn)
if(NOT cmsis_nn_POPULATED)
FetchContent_Populate(cmsis_nn)
add_subdirectory(${cmsis_nn_SOURCE_DIR} ${cmsis_nn_BINARY_DIR})
endif()
endif()

# Print paths for debugging
message(STATUS "CMSIS-NN source dir: ${cmsis_nn_SOURCE_DIR}")
message(STATUS "CMSIS-NN binary dir: ${cmsis_nn_BINARY_DIR}")
# Add MVEI define to cmsis-nn target
if(TARGET cmsis-nn)
target_compile_definitions(cmsis-nn PUBLIC ARM_MATH_MVEI=1)
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get_target_property(CMSIS_NN_INCLUDES cmsis-nn INTERFACE_INCLUDE_DIRECTORIES)
message(STATUS "CMSIS-NN include dirs: ${CMSIS_NN_INCLUDES}")
else()
message(
FATAL_ERROR
"CMSIS-NN target not found. Check your CMSIS_NN_LOCAL_PATH or network connection."
)
endif()

# Cortex-M ops kernel sources
set(_cortex_m_kernels__srcs
${CMAKE_CURRENT_SOURCE_DIR}/ops/op_quantize_per_tensor.cpp
${CMAKE_CURRENT_SOURCE_DIR}/ops/op_dequantize_per_tensor.cpp
${CMAKE_CURRENT_SOURCE_DIR}/ops/op_quantized_add.cpp
${CMAKE_CURRENT_SOURCE_DIR}/ops/op_quantized_linear.cpp
)

# Generate C++ bindings to register kernels into Executorch (for runtime)
# Generate C++ bindings to register kernels into Executorch
set(_yaml_file ${CMAKE_CURRENT_LIST_DIR}/ops/operators.yaml)
gen_selected_ops(LIB_NAME "cortex_m_ops_lib" OPS_SCHEMA_YAML "${_yaml_file}")

generate_bindings_for_kernels(
LIB_NAME "cortex_m_ops_lib" CUSTOM_OPS_YAML "${_yaml_file}"
)
message("Generated files ${gen_command_sources}")

# Build a library for cortex_m_kernels
# Build library for cortex_m_kernels
add_library(cortex_m_kernels ${_cortex_m_kernels__srcs})
target_compile_options(cortex_m_kernels PUBLIC ${_common_compile_options})

# Include directories for cortex_m_kernels
target_include_directories(
# Use PRIVATE for implementation dependencies to avoid INTERFACE pollution
target_link_libraries(
cortex_m_kernels
PRIVATE ${EXECUTORCH_ROOT}/..
${EXECUTORCH_ROOT}/runtime/core/portable_type/c10
${cmsis_nn_SOURCE_DIR}/Include
PRIVATE cmsis-nn
PRIVATE executorch
)

# Link directly to the CMSIS-NN static library file
target_link_libraries(
cortex_m_kernels PUBLIC ${cmsis_nn_BINARY_DIR}/libcmsis-nn.a executorch
# Include directories for cortex_m_kernels
target_include_directories(
cortex_m_kernels PRIVATE ${EXECUTORCH_ROOT}/..
${EXECUTORCH_ROOT}/runtime/core/portable_type/c10
)

# Add dependency to ensure CMSIS-NN builds before we try to link. Use the actual
# CMSIS-NN target name (usually 'cmsis-nn')
add_dependencies(cortex_m_kernels cmsis-nn)

# cortex_m_ops_lib: Register Cortex-M ops kernels into Executorch runtime
gen_operators_lib(
LIB_NAME "cortex_m_ops_lib" KERNEL_LIBS cortex_m_kernels DEPS executorch
)

install(
TARGETS cortex_m_kernels cortex_m_ops_lib
TARGETS cortex_m_kernels cortex_m_ops_lib cmsis-nn
EXPORT ExecuTorchTargets
DESTINATION lib
PUBLIC_HEADER DESTINATION include/executorch/backends/cortex_m/ops/
Expand Down
46 changes: 40 additions & 6 deletions backends/cortex_m/ops/cortex_m_ops_common.h
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Original file line number Diff line number Diff line change
Expand Up @@ -22,6 +22,10 @@ using ScalarType = executorch::aten::ScalarType;
using Scalar = torch::executor::Scalar;
using Error = executorch::runtime::Error;

// From arm_nn_math_types.h
#define ARM_NN_Q31_MAX ((int32_t)(0x7FFFFFFFL))
#define ARM_NN_Q31_MIN ((int32_t)(0x80000000L))

// Basic tensor type / layout validation and dimension order checking
inline void validate_cmsis_nn_tensor_requirements(
const Tensor& input1,
Expand All @@ -32,16 +36,19 @@ inline void validate_cmsis_nn_tensor_requirements(
// Basic dtype validation
ET_CHECK_MSG(
input1.scalar_type() == expected_dtype,
"Input1 dtype must be %hhd",
expected_dtype);
"Input1 dtype must be %hhd, got %hhd",
expected_dtype,
input1.scalar_type());
ET_CHECK_MSG(
input2.scalar_type() == expected_dtype,
"Input2 dtype must be %hhd",
expected_dtype);
"Input2 dtype must be %hhd, got %hhd",
expected_dtype,
input2.scalar_type());
ET_CHECK_MSG(
output.scalar_type() == expected_dtype,
"Output dtype must be %hhd",
expected_dtype);
"Output dtype must be %hhd, got %hhd",
expected_dtype,
output.scalar_type());

// Dim order consistency
ET_CHECK_MSG(
Expand Down Expand Up @@ -114,6 +121,33 @@ inline void validate_quantization_params(
"Single quant Output");
}

// Refer to CMSIS-NN 'arm_nn_requantize' implementation for details:
// https://fburl.com/afvegf0m
// multiplier: Range {ARM_NN_Q31_MIN + 1, Q32_MAX}
// shift : Range {-31, 30}
inline bool validate_per_channel_quant_params(
const int32_t* multipliers,
const int32_t* shifts,
int num_channels) {
for (int i = 0; i < num_channels; ++i) {
// Multiplier: {ARM_NN_Q31_MIN + 1, ARM_NN_Q31_MAX}
if (multipliers[i] <= ARM_NN_Q31_MIN || multipliers[i] > ARM_NN_Q31_MAX) {
ET_LOG(
Error,
"weight_multiplier[%d] out of CMSIS-NN range: %d",
i,
multipliers[i]);
return false;
}
// Shift: {-31, 30} for arm_nn_requantize
if (shifts[i] < -31 || shifts[i] > 30) {
ET_LOG(Error, "weight_shift[%d] out of range: %d", i, shifts[i]);
return false;
}
}
return true;
}

inline Error resize_to_broadcast_target_size(
const Tensor& input1,
const Tensor& input2,
Expand Down
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