torch_utils.hpp 4.62 KB
Newer Older
raojy's avatar
raojy committed
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
#pragma once

#include <torch/all.h>

#include "cute/layout.hpp"
#include "cutlass/layout/matrix.h"
#include "cutlass/bfloat16.h"
#include "cutlass/half.h"

using ColumnMajor = typename cutlass::layout::ColumnMajor;
using RowMajor = typename cutlass::layout::RowMajor;

namespace cute {

namespace detail {

template <class T, class F, class G, int... I>
CUTE_HOST_DEVICE constexpr auto tapply_with_idx(T&& t, F&& f, G&& g,
                                                seq<I...>) {
  return g(f(cute::get<I>(static_cast<T&&>(t)), I)...);
}

template <class F, int... I>
CUTE_HOST_DEVICE constexpr auto make_shape_from_idx(F&& f, seq<I...>) {
  return make_shape(f(I)...);
}

};  // namespace detail

template <class T, class F>
CUTE_HOST_DEVICE constexpr auto transform_with_idx(T const& t, F&& f) {
  if constexpr (cute::is_tuple<T>::value) {
    return detail::tapply_with_idx(
        t, f, [](auto const&... a) { return cute::make_tuple(a...); },
        tuple_seq<T>{});
  } else {
    return f(t);
  }

  CUTE_GCC_UNREACHABLE;
}

// calls: make_shape(f(0), f(1), ..., f(N-1))
template <int N, class F>
CUTE_HOST_DEVICE constexpr auto make_shape_from_idx(F&& f) {
  return detail::make_shape_from_idx(f, make_seq<N>{});
}

};  // namespace cute

// Make a layout from a tensor with `rank(Stride{})`, where the shape is the
// shape of the passed in tensor and the strides are of type `Stride` and
// contain the strides of the passed in tensor, checking that any static strides
// in `Stride{}` match the strides of the passed in tensor.
// If `tensor.dim() < rank(Stride{})`, the shape is padded with 1s and the extra
// strides are set to be 0 or 1.
template <typename Stride>
static inline auto make_cute_layout(torch::Tensor const& tensor,
                                    std::string_view name = "tensor") {
  TORCH_CHECK(tensor.dim() <= rank(Stride{}));
  auto stride = cute::transform_with_idx(
      Stride{}, [&](auto const& stride_ele, auto const& idx) {
        using StrideEle = std::decay_t<decltype(stride_ele)>;

        if (idx < tensor.dim()) {
          if constexpr (cute::is_static_v<StrideEle>) {
            TORCH_CHECK(StrideEle::value == tensor.stride(idx), "Expected ",
                        name, ".stride(", idx, ") to be ", StrideEle::value);
            return StrideEle{};
          } else {
            if (tensor.size(idx) == 1) {
              // use 0 stride for dim with size 1, this is easier for
              // cute/cutlass to optimize (helps the TMA code flatten dims)
              return StrideEle{0};
            } else {
              return tensor.stride(idx);
            }
          }
        } else {
          // Extra strides are assumed to be 0 or 1
          if constexpr (cute::is_static_v<StrideEle>) {
            static_assert(StrideEle::value == 0 || StrideEle::value == 1);
          }
          return StrideEle{};
        }
      });

  auto shape = cute::make_shape_from_idx<rank(Stride{})>([&](auto const& idx) {
    if (idx < tensor.dim())
      return tensor.size(idx);
    else
      return int64_t(1);
  });

  return make_layout(shape, stride);
}

template <typename Stride>
static inline auto maybe_make_cute_layout(
    std::optional<torch::Tensor> const& tensor,
    std::string_view name = "tensor") {
  using Layout = decltype(make_cute_layout<Stride>(*tensor));

  if (tensor) {
    return std::optional<Layout>{make_cute_layout<Stride>(*tensor, name)};
  } else {
    return std::optional<Layout>{};
  }
}

//
//  Torch Type to Cutlass Type (equivalent_cutlass_type)
//

template <typename T>
struct equivalent_cutlass_type {
  using type = T;
};

template <typename T>
using equivalent_cutlass_type_t = typename equivalent_cutlass_type<T>::type;

template <>
struct equivalent_cutlass_type<c10::Half> {
  using type = cutlass::half_t;
};

template <>
struct equivalent_cutlass_type<c10::BFloat16> {
  using type = cutlass::bfloat16_t;
};

//
// equivalent_scalar_t (basically inverse of equivalent_cutlass_type)
//

// Return a `c10::CppTypeToScalarType<T>` compatible type, i.e. get the C++ from
// c10 that is equivalent to T, e.g.: `cutlass::half_t -> c10::Half`
template <typename T>
struct equivalent_scalar_type {
  using type = T;
};

template <typename T>
using equivalent_scalar_type_t = typename equivalent_scalar_type<T>::type;

template <>
struct equivalent_scalar_type<cutlass::half_t> {
  using type = c10::Half;
};

template <>
struct equivalent_scalar_type<cutlass::bfloat16_t> {
  using type = c10::BFloat16;
};

// get equivalent c10::ScalarType tag from compile time type
template <typename T>
static inline constexpr c10::ScalarType equivalent_scalar_type_v =
    c10::CppTypeToScalarType<equivalent_scalar_type_t<T>>::value;