cmake torchao_ops_mps_linear_fp_act_xbit_weight

Differential Revision: D66120124

Pull Request resolved: #1304

Author: manuelcandales

torchao/experimental/kernels/mps/codegen/gen_metal_shader_lib.py

@@ -1,11 +1,22 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
 from typing import Optional
 import os
+import sys
 import yaml
 
-torchao_root: Optional[str] = os.getenv("TORCHAO_ROOT")
-assert torchao_root is not None, "TORCHAO_ROOT is not set"
+if len(sys.argv) != 2:
+    print("Usage: gen_metal_shader_lib.py <output_file>")
+    sys.exit(1)
+
+# Output file where the generated code will be written
+OUTPUT_FILE = sys.argv[1]
 
-MPS_DIR = os.path.join(torchao_root, "torchao", "experimental", "kernels", "mps")
+MPS_DIR = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
 
 # Path to yaml file containing the list of .metal files to include
 METAL_YAML = os.path.join(MPS_DIR, "metal.yaml")
@@ -21,9 +32,6 @@
 # Path to the folder containing the .metal files
 METAL_DIR = os.path.join(MPS_DIR, "metal")
 
-# Output file where the generated code will be written
-OUTPUT_FILE = os.path.join(MPS_DIR, "src", "metal_shader_lib.h")
-
 prefix = """/**
  * This file is generated by gen_metal_shader_lib.py
  */
@@ -48,6 +56,7 @@
 
 """
 
+os.makedirs(os.path.dirname(OUTPUT_FILE), exist_ok=True)
 with open(OUTPUT_FILE, "w") as outf:
     outf.write(prefix)
     for file in metal_files:

torchao/experimental/ops/mps/.gitignore

@@ -0,0 +1 @@
+cmake-out/

torchao/experimental/ops/mps/CMakeLists.txt

@@ -0,0 +1,60 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+cmake_minimum_required(VERSION 3.19)
+
+project(torchao_ops_mps_linear_fp_act_xbit_weight)
+
+set(CMAKE_CXX_STANDARD 17)
+set(CMAKE_CXX_STANDARD_REQUIRED YES)
+
+if (NOT CMAKE_BUILD_TYPE)
+    set(CMAKE_BUILD_TYPE Release)
+endif()
+
+if (CMAKE_SYSTEM_NAME STREQUAL "Darwin")
+    if (NOT CMAKE_SYSTEM_PROCESSOR STREQUAL "arm64")
+        message(FATAL_ERROR "Unified Memory requires Apple Silicon architecture")
+    endif()
+else()
+    message(FATAL_ERROR "Torchao experimental mps ops can only be built on macOS/iOS")
+endif()
+
+find_package(Torch REQUIRED)
+
+# Generate metal_shader_lib.h by running gen_metal_shader_lib.py
+set(GENERATED_METAL_SHADER_LIB ${CMAKE_INSTALL_PREFIX}/include/torchao/experimental/kernels/mps/src/metal_shader_lib.h)
+add_custom_command(
+    OUTPUT ${GENERATED_METAL_SHADER_LIB}
+    COMMAND python ${CMAKE_CURRENT_SOURCE_DIR}/../../kernels/mps/codegen/gen_metal_shader_lib.py ${GENERATED_METAL_SHADER_LIB}
+    COMMENT "Generating metal_shader_lib.h using gen_metal_shader_lib.py"
+)
+add_custom_target(generated_metal_shader_lib ALL DEPENDS ${GENERATED_METAL_SHADER_LIB})
+
+if(NOT TORCHAO_INCLUDE_DIRS)
+  set(TORCHAO_INCLUDE_DIRS ${CMAKE_CURRENT_SOURCE_DIR}/../../../..)
+endif()
+message(STATUS "TORCHAO_INCLUDE_DIRS: ${TORCHAO_INCLUDE_DIRS}")
+
+include_directories(${TORCHAO_INCLUDE_DIRS})
+include_directories(${CMAKE_INSTALL_PREFIX}/include)
+add_library(torchao_ops_mps_linear_fp_act_xbit_weight_aten SHARED aten/register.mm)
+add_dependencies(torchao_ops_mps_linear_fp_act_xbit_weight_aten generated_metal_shader_lib)
+
+target_include_directories(torchao_ops_mps_linear_fp_act_xbit_weight_aten PRIVATE "${TORCH_INCLUDE_DIRS}")
+target_link_libraries(torchao_ops_mps_linear_fp_act_xbit_weight_aten PRIVATE "${TORCH_LIBRARIES}")
+target_compile_definitions(torchao_ops_mps_linear_fp_act_xbit_weight_aten PRIVATE USE_ATEN=1)
+
+# Enable Metal support
+find_library(METAL_LIB Metal)
+find_library(FOUNDATION_LIB Foundation)
+target_link_libraries(torchao_ops_mps_linear_fp_act_xbit_weight_aten PRIVATE ${METAL_LIB} ${FOUNDATION_LIB})
+
+install(
+    TARGETS torchao_ops_mps_linear_fp_act_xbit_weight_aten
+    EXPORT _targets
+    DESTINATION lib
+)

torchao/experimental/ops/mps/register.mm renamed to torchao/experimental/ops/mps/aten/register.mm

@@ -5,7 +5,7 @@
 // LICENSE file in the root directory of this source tree.
 
 // clang-format off
-#include <torch/extension.h>
+#include <torch/library.h>
 #include <ATen/native/mps/OperationUtils.h>
 #include <torchao/experimental/kernels/mps/src/lowbit.h>
 // clang-format on
@@ -147,9 +147,6 @@ Tensor pack_weights_cpu_kernel(const Tensor& W) {
   return B;
 }
 
-// Registers _C as a Python extension module.
-PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {}
-
 TORCH_LIBRARY(torchao, m) {
   m.def("_pack_weight_1bit(Tensor W) -> Tensor");
   m.def("_pack_weight_2bit(Tensor W) -> Tensor");

torchao/experimental/ops/mps/build.sh

@@ -0,0 +1,19 @@
+#!/bin/bash -eu
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+cd "$(dirname "$BASH_SOURCE")"
+
+export CMAKE_PREFIX_PATH=$(python -c 'from distutils.sysconfig import get_python_lib; print(get_python_lib())')
+echo "CMAKE_PREFIX_PATH: ${CMAKE_PREFIX_PATH}"
+export CMAKE_OUT=${PWD}/cmake-out
+echo "CMAKE_OUT: ${CMAKE_OUT}"
+
+cmake -DCMAKE_PREFIX_PATH=${CMAKE_PREFIX_PATH} \
+    -DCMAKE_INSTALL_PREFIX=${CMAKE_OUT} \
+    -S . \
+    -B ${CMAKE_OUT}
+cmake --build  ${CMAKE_OUT} -j 16 --target install --config Release

torchao/experimental/ops/mps/setup.py

@@ -4,25 +4,38 @@
 # This source code is licensed under the license found in the
 # LICENSE file in the root directory of this source tree.
 
+import os
+import sys
 import torch
-import torchao_mps_ops
 import unittest
 
+from parameterized import parameterized
 
-def parameterized(test_cases):
-    def decorator(func):
-        def wrapper(self):
-            for case in test_cases:
-                with self.subTest(case=case):
-                    func(self, *case)
+libname = "libtorchao_ops_mps_linear_fp_act_xbit_weight_aten.dylib"
+libpath = os.path.abspath(
+    os.path.join(os.path.dirname(__file__), "../cmake-out/lib/", libname)
+)
 
-        return wrapper
-
-    return decorator
+try:
+    for nbit in range(1, 8):
+        getattr(torch.ops.torchao, f"_linear_fp_act_{nbit}bit_weight")
+        getattr(torch.ops.torchao, f"_pack_weight_{nbit}bit")
+except AttributeError:
+    try:
+        torch.ops.load_library(libpath)
+    except:
+        raise RuntimeError(f"Failed to load library {libpath}")
+    else:
+        try:
+            for nbit in range(1, 8):
+                getattr(torch.ops.torchao, f"_linear_fp_act_{nbit}bit_weight")
+                getattr(torch.ops.torchao, f"_pack_weight_{nbit}bit")
+        except AttributeError as e:
+            raise e
 
 
 class TestLowBitQuantWeightsLinear(unittest.TestCase):
-    cases = [
+    CASES = [
         (nbit, *param)
         for nbit in range(1, 8)
         for param in [
@@ -73,7 +86,7 @@ def _reference_linear_lowbit_quant_weights(self, A, W, group_size, S, Z, nbit):
         W = scales * W + zeros
         return torch.mm(A, W.t())
 
-    @parameterized(cases)
+    @parameterized.expand(CASES)
     def test_linear(self, nbit, M=1, K=32, N=32, group_size=32):
         print(f"nbit: {nbit}, M: {M}, K: {K}, N: {N}, group_size: {group_size}")
         A, W, S, Z = self._init_tensors(group_size, M, K, N, nbit=nbit)

torchao/experimental/ops/mps/test/test_lowbit.py

@@ -11,13 +11,34 @@
 import sys
 
 import torch
-import torchao_mps_ops
 import unittest
 
 from parameterized import parameterized
 from torchao.experimental.quant_api import UIntxWeightOnlyLinearQuantizer
 from torchao.experimental.quant_api import _quantize
 
+libname = "libtorchao_ops_mps_linear_fp_act_xbit_weight_aten.dylib"
+libpath = os.path.abspath(
+    os.path.join(os.path.dirname(__file__), "../cmake-out/lib/", libname)
+)
+
+try:
+    for nbit in range(1, 8):
+        getattr(torch.ops.torchao, f"_linear_fp_act_{nbit}bit_weight")
+        getattr(torch.ops.torchao, f"_pack_weight_{nbit}bit")
+except AttributeError:
+    try:
+        torch.ops.load_library(libpath)
+    except:
+        raise RuntimeError(f"Failed to load library {libpath}")
+    else:
+        try:
+            for nbit in range(1, 8):
+                getattr(torch.ops.torchao, f"_linear_fp_act_{nbit}bit_weight")
+                getattr(torch.ops.torchao, f"_pack_weight_{nbit}bit")
+        except AttributeError as e:
+            raise e
+
 
 class TestUIntxWeightOnlyLinearQuantizer(unittest.TestCase):
     BITWIDTHS = range(1, 8)