[MPS] Support includes in metal objects (pytorch#145087)

malfet · pytorchmergebot · commit dc9b77cc552d · 2025-01-18T05:35:22.000Z
Useful for code reuse for Metal shader build both for eager mode and MPSInductor, but it requires one to implement `_cpp_embed_headers` tool that, as name suggests, would preprocess and embeds the for shader to be used in dynamic compilation. Test using: - `TestMetalLibrary.test_metal_include` - Moving `i0`/`i1` implementation to `c10/util/metal_special_math.h` and call it from `SpecialOps.metal` shader, which now looks much more compact: ```metal template <typename T, typename Tout = T> void kernel i0(constant T* input, device Tout* output, uint index [[thread_position_in_grid]]) { output[index] = c10::i0(static_cast<Tout>(input[index])); } ``` Pull Request resolved: pytorch#145087 Approved by: https://github.com/dcci ghstack dependencies: pytorch#145023
diff --git a/.lintrunner.toml b/.lintrunner.toml
@@ -249,6 +249,7 @@ exclude_patterns = [
     'c10/util/complex_utils.h',
     'c10/util/flat_hash_map.h',
     'c10/util/logging*.h',
+    'c10/metal/*.h',
     'c10/util/hash.h',
     'c10/util/strong_type.h',
     'c10/util/SmallVector.h',
diff --git a/aten/src/ATen/native/mps/kernels/SpecialOps.metal b/aten/src/ATen/native/mps/kernels/SpecialOps.metal
@@ -1,149 +1,19 @@
-#include <metal_stdlib>
-using namespace metal;
-
-/*
- * For licensing information and documentation, please refer to the cpu
- * implementation located in "ATen/native/Math.h".
- */
-
-template <typename T>
-T chbevl(T x, const float array[], const int len) {
-  T b0, b1, b2;
-
-  b0 = array[0];
-  b1 = 0;
-
-  for (int i = 1; i < len; ++i) {
-    b2 = b1;
-    b1 = b0;
-    b0 = x * b1 - b2 + array[i];
-  }
-
-  return T{0.5} * (b0 - b2);
-}
-
-// Copied from
-// https://github.com/pytorch/pytorch/blob/58b661cda2c002a8e1ac3bee494bfe1f7420437c/aten/src/ATen/native/cuda/Math.cuh#L502
-
-template <typename T>
-T i0(T _x) {
-  auto x = fabs(_x);
-
-  if (x <= 8.0) {
-    /* Chebyshev coefficients for exp(-x) I0(x)
-     *   in the interval [0,8].
-     *
-     * lim(x->0){ exp(-x) I0(x) } = 1.
-     */
-    const float A[] = {-4.41534164647933937950E-18, 3.33079451882223809783E-17,
-                       -2.43127984654795469359E-16, 1.71539128555513303061E-15,
-                       -1.16853328779934516808E-14, 7.67618549860493561688E-14,
-                       -4.85644678311192946090E-13, 2.95505266312963983461E-12,
-                       -1.72682629144155570723E-11, 9.67580903537323691224E-11,
-                       -5.18979560163526290666E-10, 2.65982372468238665035E-9,
-                       -1.30002500998624804212E-8,  6.04699502254191894932E-8,
-                       -2.67079385394061173391E-7,  1.11738753912010371815E-6,
-                       -4.41673835845875056359E-6,  1.64484480707288970893E-5,
-                       -5.75419501008210370398E-5,  1.88502885095841655729E-4,
-                       -5.76375574538582365885E-4,  1.63947561694133579842E-3,
-                       -4.32430999505057594430E-3,  1.05464603945949983183E-2,
-                       -2.37374148058994688156E-2,  4.93052842396707084878E-2,
-                       -9.49010970480476444210E-2,  1.71620901522208775349E-1,
-                       -3.04682672343198398683E-1,  6.76795274409476084995E-1};
-
-    auto y = (x / 2.0) - 2.0;
-    return static_cast<T>(exp(x) * chbevl(y, A, 30));
-  }
-
-  // Handles x > 8 case
-  /* Chebyshev coefficients for exp(-x) sqrt(x) I0(x)
-   * in the inverted interval [8,infinity].
-   *
-   * lim(x->inf){ exp(-x) sqrt(x) I0(x) } = 1/sqrt(2pi).
-   */
-  const float B[] = {-7.23318048787475395456E-18, -4.83050448594418207126E-18,
-                     4.46562142029675999901E-17,  3.46122286769746109310E-17,
-                     -2.82762398051658348494E-16, -3.42548561967721913462E-16,
-                     1.77256013305652638360E-15,  3.81168066935262242075E-15,
-                     -9.55484669882830764870E-15, -4.15056934728722208663E-14,
-                     1.54008621752140982691E-14,  3.85277838274214270114E-13,
-                     7.18012445138366623367E-13,  -1.79417853150680611778E-12,
-                     -1.32158118404477131188E-11, -3.14991652796324136454E-11,
-                     1.18891471078464383424E-11,  4.94060238822496958910E-10,
-                     3.39623202570838634515E-9,   2.26666899049817806459E-8,
-                     2.04891858946906374183E-7,   2.89137052083475648297E-6,
-                     6.88975834691682398426E-5,   3.36911647825569408990E-3,
-                     8.04490411014108831608E-1};
-
-  return static_cast<T>((exp(x) * chbevl(32.0 / x - 2.0, B, 25)) / sqrt(x));
-}
-
-// Copied from
-// https://github.com/pytorch/pytorch/blob/58b661cda2c002a8e1ac3bee494bfe1f7420437c/aten/src/ATen/native/cuda/Math.cuh#L576
-
-template <typename T>
-T i1(T _x) {
-  const auto x = fabs(_x);
-
-  if (x <= 8.0) {
-    // Chebyshev coefficients for exp(-x) i1(x) in the internal [0, 8]
-    //   lim(x->0){ exp(-x) i1(x) / x } = 1/2
-    const float coefficients[] = {
-        2.77791411276104639959E-18, -2.11142121435816608115E-17,
-        1.55363195773620046921E-16, -1.10559694773538630805E-15,
-        7.60068429473540693410E-15, -5.04218550472791168711E-14,
-        3.22379336594557470981E-13, -1.98397439776494371520E-12,
-        1.17361862988909016308E-11, -6.66348972350202774223E-11,
-        3.62559028155211703701E-10, -1.88724975172282928790E-9,
-        9.38153738649577178388E-9,  -4.44505912879632808065E-8,
-        2.00329475355213526229E-7,  -8.56872026469545474066E-7,
-        3.47025130813767847674E-6,  -1.32731636560394358279E-5,
-        4.78156510755005422638E-5,  -1.61760815825896745588E-4,
-        5.12285956168575772895E-4,  -1.51357245063125314899E-3,
-        4.15642294431288815669E-3,  -1.05640848946261981558E-2,
-        2.47264490306265168283E-2,  -5.29459812080949914269E-2,
-        1.02643658689847095384E-1,  -1.76416518357834055153E-1,
-        2.52587186443633654823E-1};
-    const auto y = x / 2.0 - 2.0;
-    const auto out = exp(x) * x * chbevl(y, coefficients, 29);
-    return static_cast<T>(_x < T(0.) ? -out : out);
-  }
-
-  // Chebyshev coefficients for exp(-x) sqrt(x) i1(x)
-  //   in the inverted interval [8, infinity]
-  //   lim(x->inf){ exp(-x) sqrt(x) i1(x) } = 1/sqrt(2pi)
-  const float coefficients[] = {
-      7.51729631084210481353E-18,  4.41434832307170791151E-18,
-      -4.65030536848935832153E-17, -3.20952592199342395980E-17,
-      2.96262899764595013876E-16,  3.30820231092092828324E-16,
-      -1.88035477551078244854E-15, -3.81440307243700780478E-15,
-      1.04202769841288027642E-14,  4.27244001671195135429E-14,
-      -2.10154184277266431302E-14, -4.08355111109219731823E-13,
-      -7.19855177624590851209E-13, 2.03562854414708950722E-12,
-      1.41258074366137813316E-11,  3.25260358301548823856E-11,
-      -1.89749581235054123450E-11, -5.58974346219658380687E-10,
-      -3.83538038596423702205E-9,  -2.63146884688951950684E-8,
-      -2.51223623787020892529E-7,  -3.88256480887769039346E-6,
-      -1.10588938762623716291E-4,  -9.76109749136146840777E-3,
-      7.78576235018280120474E-1};
-  const auto out = (exp(x) * chbevl(32. / x - 2., coefficients, 25)) / sqrt(x);
-  return static_cast<T>(_x < T(0.) ? -out : out);
-}
+#include <c10/metal/special_math.h>
 
 template <typename T, typename Tout = T>
 void kernel
 i0(constant T* input,
    device Tout* output,
    uint index [[thread_position_in_grid]]) {
-  output[index] = i0(static_cast<Tout>(input[index]));
+  output[index] = c10::metal::i0(static_cast<Tout>(input[index]));
 }
 
 template <typename T, typename Tout = T>
 void kernel
 i1(constant T* input,
    device Tout* output,
    uint index [[thread_position_in_grid]]) {
-  output[index] = i1(static_cast<Tout>(input[index]));
+  output[index] = c10::metal::i1(static_cast<Tout>(input[index]));
 }
 
 #define REGISTER_I0_I1(DTI, DTO)                                        \
diff --git a/c10/metal/special_math.h b/c10/metal/special_math.h
@@ -0,0 +1,139 @@
+// Implementation of specal math functions for Metal
+#include <metal_stdlib>
+
+namespace c10 {
+namespace metal {
+
+/*
+ * For licensing information and documentation, please refer to the cpu
+ * implementation located in "ATen/native/Math.h".
+ */
+
+template <typename T>
+T chbevl(T x, const float array[], const int len) {
+  T b0, b1, b2;
+
+  b0 = array[0];
+  b1 = 0;
+
+  for (int i = 1; i < len; ++i) {
+    b2 = b1;
+    b1 = b0;
+    b0 = x * b1 - b2 + array[i];
+  }
+
+  return T{0.5} * (b0 - b2);
+}
+
+// Copied from
+// https://github.com/pytorch/pytorch/blob/58b661cda2c002a8e1ac3bee494bfe1f7420437c/aten/src/ATen/native/cuda/Math.cuh#L502
+
+template <typename T>
+T i0(T _x) {
+  auto x = ::metal::fabs(_x);
+
+  if (x <= 8.0) {
+    /* Chebyshev coefficients for exp(-x) I0(x)
+     *   in the interval [0,8].
+     *
+     * lim(x->0){ exp(-x) I0(x) } = 1.
+     */
+    const float A[] = {-4.41534164647933937950E-18, 3.33079451882223809783E-17,
+                       -2.43127984654795469359E-16, 1.71539128555513303061E-15,
+                       -1.16853328779934516808E-14, 7.67618549860493561688E-14,
+                       -4.85644678311192946090E-13, 2.95505266312963983461E-12,
+                       -1.72682629144155570723E-11, 9.67580903537323691224E-11,
+                       -5.18979560163526290666E-10, 2.65982372468238665035E-9,
+                       -1.30002500998624804212E-8,  6.04699502254191894932E-8,
+                       -2.67079385394061173391E-7,  1.11738753912010371815E-6,
+                       -4.41673835845875056359E-6,  1.64484480707288970893E-5,
+                       -5.75419501008210370398E-5,  1.88502885095841655729E-4,
+                       -5.76375574538582365885E-4,  1.63947561694133579842E-3,
+                       -4.32430999505057594430E-3,  1.05464603945949983183E-2,
+                       -2.37374148058994688156E-2,  4.93052842396707084878E-2,
+                       -9.49010970480476444210E-2,  1.71620901522208775349E-1,
+                       -3.04682672343198398683E-1,  6.76795274409476084995E-1};
+
+    auto y = (x / 2.0) - 2.0;
+    return static_cast<T>(::metal::exp(x) * chbevl(y, A, 30));
+  }
+
+  // Handles x > 8 case
+  /* Chebyshev coefficients for exp(-x) sqrt(x) I0(x)
+   * in the inverted interval [8,infinity].
+   *
+   * lim(x->inf){ exp(-x) sqrt(x) I0(x) } = 1/sqrt(2pi).
+   */
+  const float B[] = {-7.23318048787475395456E-18, -4.83050448594418207126E-18,
+                     4.46562142029675999901E-17,  3.46122286769746109310E-17,
+                     -2.82762398051658348494E-16, -3.42548561967721913462E-16,
+                     1.77256013305652638360E-15,  3.81168066935262242075E-15,
+                     -9.55484669882830764870E-15, -4.15056934728722208663E-14,
+                     1.54008621752140982691E-14,  3.85277838274214270114E-13,
+                     7.18012445138366623367E-13,  -1.79417853150680611778E-12,
+                     -1.32158118404477131188E-11, -3.14991652796324136454E-11,
+                     1.18891471078464383424E-11,  4.94060238822496958910E-10,
+                     3.39623202570838634515E-9,   2.26666899049817806459E-8,
+                     2.04891858946906374183E-7,   2.89137052083475648297E-6,
+                     6.88975834691682398426E-5,   3.36911647825569408990E-3,
+                     8.04490411014108831608E-1};
+
+  return static_cast<T>(
+      (::metal::exp(x) * chbevl(32.0 / x - 2.0, B, 25)) / ::metal::sqrt(x));
+}
+
+// Copied from
+// https://github.com/pytorch/pytorch/blob/58b661cda2c002a8e1ac3bee494bfe1f7420437c/aten/src/ATen/native/cuda/Math.cuh#L576
+
+template <typename T>
+T i1(T _x) {
+  const auto x = ::metal::fabs(_x);
+
+  if (x <= 8.0) {
+    // Chebyshev coefficients for exp(-x) i1(x) in the internal [0, 8]
+    //   lim(x->0){ exp(-x) i1(x) / x } = 1/2
+    const float coefficients[] = {
+        2.77791411276104639959E-18, -2.11142121435816608115E-17,
+        1.55363195773620046921E-16, -1.10559694773538630805E-15,
+        7.60068429473540693410E-15, -5.04218550472791168711E-14,
+        3.22379336594557470981E-13, -1.98397439776494371520E-12,
+        1.17361862988909016308E-11, -6.66348972350202774223E-11,
+        3.62559028155211703701E-10, -1.88724975172282928790E-9,
+        9.38153738649577178388E-9,  -4.44505912879632808065E-8,
+        2.00329475355213526229E-7,  -8.56872026469545474066E-7,
+        3.47025130813767847674E-6,  -1.32731636560394358279E-5,
+        4.78156510755005422638E-5,  -1.61760815825896745588E-4,
+        5.12285956168575772895E-4,  -1.51357245063125314899E-3,
+        4.15642294431288815669E-3,  -1.05640848946261981558E-2,
+        2.47264490306265168283E-2,  -5.29459812080949914269E-2,
+        1.02643658689847095384E-1,  -1.76416518357834055153E-1,
+        2.52587186443633654823E-1};
+    const auto y = x / 2.0 - 2.0;
+    const auto out = ::metal::exp(x) * x * chbevl(y, coefficients, 29);
+    return static_cast<T>(_x < T(0.) ? -out : out);
+  }
+
+  // Chebyshev coefficients for exp(-x) sqrt(x) i1(x)
+  //   in the inverted interval [8, infinity]
+  //   lim(x->inf){ exp(-x) sqrt(x) i1(x) } = 1/sqrt(2pi)
+  const float coefficients[] = {
+      7.51729631084210481353E-18,  4.41434832307170791151E-18,
+      -4.65030536848935832153E-17, -3.20952592199342395980E-17,
+      2.96262899764595013876E-16,  3.30820231092092828324E-16,
+      -1.88035477551078244854E-15, -3.81440307243700780478E-15,
+      1.04202769841288027642E-14,  4.27244001671195135429E-14,
+      -2.10154184277266431302E-14, -4.08355111109219731823E-13,
+      -7.19855177624590851209E-13, 2.03562854414708950722E-12,
+      1.41258074366137813316E-11,  3.25260358301548823856E-11,
+      -1.89749581235054123450E-11, -5.58974346219658380687E-10,
+      -3.83538038596423702205E-9,  -2.63146884688951950684E-8,
+      -2.51223623787020892529E-7,  -3.88256480887769039346E-6,
+      -1.10588938762623716291E-4,  -9.76109749136146840777E-3,
+      7.78576235018280120474E-1};
+  const auto out = (::metal::exp(x) * chbevl(32. / x - 2., coefficients, 25)) /
+      ::metal::sqrt(x);
+  return static_cast<T>(_x < T(0.) ? -out : out);
+}
+
+} // namespace metal
+} // namespace c10
diff --git a/cmake/Metal.cmake b/cmake/Metal.cmake
@@ -8,7 +8,7 @@ if(WERROR)
 endif()
 
 function(metal_to_air SRC TARGET FLAGS)
-    add_custom_command(COMMAND xcrun metal -c ${SRC} -o ${TARGET} ${FLAGS} ${METAL_CFLAGS}
+    add_custom_command(COMMAND xcrun metal -c ${SRC} -I ${CMAKE_SOURCE_DIR} -o ${TARGET} ${FLAGS} ${METAL_CFLAGS}
                        DEPENDS ${SRC}
                        OUTPUT ${TARGET}
                        COMMENT "Compiling ${SRC} to ${TARGET}"
@@ -25,7 +25,14 @@ function(air_to_metallib TARGET OBJECTS)
 endfunction()
 
 function(metal_to_metallib_h SRC TGT)
-    file(READ ${SRC} SHADER_CONTENT)
+    execute_process(COMMAND ${Python_EXECUTABLE} torch/utils/_cpp_embed_headers.py ${SRC}
+                    WORKING_DIRECTORY ${CMAKE_SOURCE_DIR}
+                    OUTPUT_VARIABLE SHADER_CONTENT
+                    RESULT_VARIABLE _exitcode)
+    if(NOT _exitcode EQUAL 0)
+        message(FATAL_ERROR "Failed to preprocess Metal shader ${SRC}")
+        return()
+    endif()
     file(WRITE ${TGT} "#include <ATen/native/mps/OperationUtils.h>\n")
     file(APPEND ${TGT} "static ::at::native::mps::MetalShaderLibrary lib(R\"SHDR(\n")
     file(APPEND ${TGT} "${SHADER_CONTENT}")
diff --git a/setup.py b/setup.py
@@ -1248,6 +1248,7 @@ def main():
         "include/c10/cuda/impl/*.h",
         "include/c10/hip/*.h",
         "include/c10/hip/impl/*.h",
+        "include/c10/metal/*.h",
         "include/c10/xpu/*.h",
         "include/c10/xpu/impl/*.h",
         "include/torch/*.h",
diff --git a/test/test_mps.py b/test/test_mps.py
@@ -12698,6 +12698,11 @@ def test_metal_error_checking(self):
         # Passing no tensors asserts
         self.assertRaises(RuntimeError, lambda: lib.full(12))
 
+    def test_metal_include(self):
+        # Checks that includes embedding works
+        lib = torch.mps._compile_shader("#include <c10/metal/special_math.h>")
+        self.assertIsNotNone(lib)
+
     @unittest.skipIf(not torch.mps.profiler.is_metal_capture_enabled(), "Set MTL_CAPTURE_ENABLED and try again")
     def test_metal_capture(self):
         lib = torch.mps._compile_shader("kernel void full(device float* x, uint idx [[thread_position_in_grid]]) { x[idx] = 1.0; }")
diff --git a/torch/mps/__init__.py b/torch/mps/__init__.py
@@ -152,8 +152,17 @@ def _compile_shader(source: str):
         >>> x = torch.zeros(16, device="mps")
         >>> lib.full(x, 3.14)
     """
+    from pathlib import Path
+
+    from torch.utils._cpp_embed_headers import _embed_headers
+
     if not hasattr(torch._C, "_mps_compileShader"):
         raise RuntimeError("MPS is not available")
+    source = _embed_headers(
+        [l + "\n" for l in source.split("\n")],
+        [Path(__file__).parent.parent / "include"],
+        set(),
+    )
     return torch._C._mps_compileShader(source)
 
 
diff --git a/torch/utils/_cpp_embed_headers.py b/torch/utils/_cpp_embed_headers.py
