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Commit e1ae8f18 authored by Chao Liu's avatar Chao Liu
Browse files

added GetLinearDimensionMask

parent 4f4aba48
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Inline Side-by-side
Showing with 63 additions and 56 deletions
composable_kernel/include/kernel_algorithm/gridwise_convolution_implicit_gemm_v4r1_nchw_kcyx_nkhw_padded_lds_double_buffer.hpp
View file @ e1ae8f18
......@@ -173,8 +173,6 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_padded_lds_double_buf
BlockwiseGenericTensorSliceCopy_v4<BlockSize,
decltype(in_e_n1_b_n2_global_desc),
decltype(in_e_n1_b_n2_block_desc),
Sequence<0, 1, 0, 1>,
Sequence<1, 1, 1, 1>,
decltype(in_e_n1_b_n2_block_desc.GetLengths()),
InBlockCopySubLengths_E_N1_B_N2,
InBlockCopyClusterLengths_E_N1_B_N2,
......@@ -216,8 +214,6 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_padded_lds_double_buf
BlockwiseGenericTensorSliceCopy_v4<BlockSize,
decltype(wei_e_k_global_desc),
decltype(wei_e_k_block_desc),
Sequence<1, 1>,
Sequence<1, 1>,
decltype(wei_e_k_block_desc.GetLengths()),
WeiBlockCopySubLengths_E_K,
WeiBlockCopyClusterLengths_E_K,
......@@ -427,8 +423,6 @@ struct GridwiseConvolutionImplicitGemm_v4r1_nchw_kcyx_nkhw_padded_lds_double_buf
ThreadwiseGenericTensorSliceCopy_v4r2<decltype(out_k0_k1_n1_b_n2_thread_desc),
decltype(out_k0_k1_n1_b_n2_global_desc),
Sequence<1, 1, 1, 1, 1>,
Sequence<1, 1, 1, 0, 1>,
decltype(
out_k0_k1_n1_b_n2_thread_desc.GetLengths()),
arithmetic_sequence_gen<0, 5, 1>::type,
......
composable_kernel/include/kernel_algorithm/gridwise_convolution_implicit_gemm_v4r4_nchw_kcyx_nkhw_padded_lds_double_buffer.hpp
View file @ e1ae8f18
......@@ -145,8 +145,6 @@ struct GridwiseConvolutionImplicitGemm_v4r4_nchw_kcyx_nkhw_padded_lds_double_buf
BlockwiseGenericTensorSliceCopy_v4<BlockSize,
decltype(in_e_b_global_desc),
decltype(in_e_b_block_desc),
Sequence<0, 0>,
Sequence<1, 1>,
decltype(in_e_b_block_desc.GetLengths()),
InBlockCopySubLengths_E_B,
InBlockCopyClusterLengths_E_B,
......@@ -186,8 +184,6 @@ struct GridwiseConvolutionImplicitGemm_v4r4_nchw_kcyx_nkhw_padded_lds_double_buf
BlockwiseGenericTensorSliceCopy_v4<BlockSize,
decltype(wei_e_k_global_desc),
decltype(wei_e_k_block_desc),
Sequence<1, 1>,
Sequence<1, 1>,
decltype(wei_e_k_block_desc.GetLengths()),
WeiBlockCopySubLengths_E_K,
WeiBlockCopyClusterLengths_E_K,
......@@ -390,8 +386,6 @@ struct GridwiseConvolutionImplicitGemm_v4r4_nchw_kcyx_nkhw_padded_lds_double_buf
ThreadwiseGenericTensorSliceCopy_v4r2<
decltype(out_k0_k1_b0_b1_thread_desc),
decltype(out_k0_k1_b0_b1_global_desc),
Sequence<1, 1, 1, 1>,
Sequence<1, 1, 0, 0>,
decltype(out_k0_k1_b0_b1_thread_desc.GetLengths()),
arithmetic_sequence_gen<0, 4, 1>::type,
3,
......
composable_kernel/include/tensor_description/tensor_descriptor.hpp
View file @ e1ae8f18
......@@ -353,7 +353,6 @@ struct TransformedTensorDescriptor
return GetLowerTensorDescriptor().CalculateOffset(CalculateLowerIndex(idx_up));
}
#if 1
struct lambda_sequence_logical_and
{
template <typename... Seqs>
......@@ -378,7 +377,7 @@ struct TransformedTensorDescriptor
// check only one transform at a time
template <typename Transform, typename LowDimensionId, typename UpDimensionId>
__host__ __device__ constexpr auto
operator()(const Transform& tran, LowDimensionId, UpDimensionId) const
operator()(Transform, LowDimensionId, UpDimensionId) const
{
// judge if transformation is linear
constexpr bool is_linear_transform = Transform::IsLinearTransform();
......@@ -392,23 +391,42 @@ struct TransformedTensorDescriptor
// create linear mask for upper dimensions
constexpr bool are_up_dim_linear = is_linear_transform && are_all_low_dim_linear;
constexpr auto mask_of_up_linear_dims = modifiy_sequence_by_ids(
typename uniform_sequence_gen<nDimUp, 0>::type{},
typename uniform_sequence_gen<UpDimensionId::Size(), 1>::type{},
constexpr auto mask_of_up_linear_dims = modify_sequence_elements_by_ids(
typename uniform_sequence_gen<nDimUp, 1>::type{},
typename uniform_sequence_gen<UpDimensionId::Size(), are_up_dim_linear>::type{},
UpDimensionId{});
return mask_of_up_linear_dims;
}
};
// TODO: this is a hack, transform_tuples() doesn't compile, would complain about constexpr
template <typename F, typename X, typename Y, typename Z, index_t... Is>
__host__ __device__ static constexpr auto
dummy_transform_tuples_impl(F f, X x, Y y, Z z, Sequence<Is...>)
{
return make_tuple(f(x.At(Number<Is>{}), y.At(Number<Is>{}), z.At(Number<Is>{}))...);
}
__host__ __device__ static constexpr auto GetLinearDimensionMask()
{
#if 0
// create tuple of linear dimension masks, for all transformations
constexpr auto tuple_of_linear_dimension_mask =
transform_tuples(lambda_get_linear_dimension_mask_of_single_tranform{},
Transforms{},
LowDimensionIds{},
UpDimensionIds{});
#else
// create tuple of linear dimension masks, for all transformations
// TODO: this is a hack, transform_tuples() doesn't compile, complain about constexpr
constexpr auto tuple_of_linear_dimension_mask = dummy_transform_tuples_impl(
lambda_get_linear_dimension_mask_of_single_tranform{},
Transforms{},
LowDimensionIds{},
UpDimensionIds{},
typename arithmetic_sequence_gen<0, Transforms::Size(), 1>::type{});
#endif
// reduce tuple of masks into one mask
constexpr auto linear_dimension_mask =
......@@ -444,6 +462,7 @@ struct TransformedTensorDescriptor
typename arithmetic_sequence_gen<0, nDimUp, 1>::type{}, nonlinear_dimension_mask);
}
#if 0
__host__ __device__ static constexpr auto GetNonLinearIndependentDimensionGroups()
{
// not implemented
......
composable_kernel/include/tensor_operation/blockwise_generic_tensor_slice_copy.hpp
View file @ e1ae8f18
......@@ -680,8 +680,6 @@ struct BlockwiseGenericTensorSliceCopy_v3
template <index_t BlockSize,
typename SrcDesc,
typename DstDesc,
typename SrcLinearDimensionMask,
typename DstLinearDimensionMask,
typename SliceLengths,
typename SubLengths,
typename ThreadClusterLengths,
......@@ -794,22 +792,16 @@ struct BlockwiseGenericTensorSliceCopy_v4
private:
using RegisterBufferDesc = decltype(make_native_tensor_descriptor_packed(SubLengths{}));
using ThreadwiseLoad =
ThreadwiseGenericTensorSliceCopy_v4r2<SrcDesc,
using ThreadwiseLoad = ThreadwiseGenericTensorSliceCopy_v4r2<SrcDesc,
RegisterBufferDesc,
SrcLinearDimensionMask,
typename uniform_sequence_gen<nDim, 1>::type,
SubLengths,
SrcDimAccessOrder,
SrcVectorAccessDim,
SrcDataPerAccess,
1>;
using ThreadwiseStore =
ThreadwiseGenericTensorSliceCopy_v4r2<RegisterBufferDesc,
using ThreadwiseStore = ThreadwiseGenericTensorSliceCopy_v4r2<RegisterBufferDesc,
DstDesc,
typename uniform_sequence_gen<nDim, 1>::type,
DstLinearDimensionMask,
SubLengths,
DstDimAccessOrder,
DstVectorAccessDim,
......
composable_kernel/include/tensor_operation/threadwise_generic_tensor_slice_copy.hpp
View file @ e1ae8f18
......@@ -1130,8 +1130,6 @@ struct ThreadwiseGenericTensorSliceCopy_v3r1
// the other is device memory or LDS
template <typename SrcDesc,
typename DstDesc,
typename SrcLinearDimensionMask,
typename DstLinearDimensionMask,
typename SliceLengths,
typename DimAccessOrder,
index_t VectorAccessDim,
......@@ -1315,11 +1313,9 @@ struct ThreadwiseGenericTensorSliceCopy_v4r2
constexpr auto long_vector_access_lengths = SliceLengths::Modify(
vector_access_dim, SliceLengths::Get(vector_access_dim) / long_vector_size);
// TODO:: stop using this hack, once TransformedTensorDescriptor::GetLinearDimensionMask()
// is implemented
constexpr auto src_linear_dim_mask = SrcLinearDimensionMask{};
constexpr auto src_nonlinear_dim_mask =
SrcLinearDimensionMask::Transform(logical_not<index_t>{});
// separate linear dimensions from non-linear dimensions
constexpr auto src_linear_dim_mask = SrcDesc::GetLinearDimensionMask();
constexpr auto src_nonlinear_dim_mask = SrcDesc::GetNonLinearDimensionMask();
static_assert(
src_linear_dim_mask.At(VectorAccessDim) || long_vector_size == SrcDataPerAccess,
......@@ -1459,11 +1455,9 @@ struct ThreadwiseGenericTensorSliceCopy_v4r2
constexpr auto long_vector_access_lengths = SliceLengths::Modify(
vector_access_dim, SliceLengths::Get(vector_access_dim) / long_vector_size);
// TODO:: stop using this hack, once TransformedTensorDescriptor::GetLinearDimensionMask()
// is implemented
constexpr auto dst_linear_dim_mask = DstLinearDimensionMask{};
constexpr auto dst_nonlinear_dim_mask =
DstLinearDimensionMask::Transform(logical_not<index_t>{});
// separate linear dimensions from non-linear dimensions
constexpr auto dst_linear_dim_mask = DstDesc::GetLinearDimensionMask();
constexpr auto dst_nonlinear_dim_mask = DstDesc::GetNonLinearDimensionMask();
static_assert(
dst_linear_dim_mask.At(VectorAccessDim) || long_vector_size == DstDataPerAccess,
......
composable_kernel/include/utility/tuple.hpp
View file @ e1ae8f18
......@@ -125,6 +125,13 @@ transform_tuples_impl(F f, const X& x, const Y& y, Sequence<Is...>)
return make_tuple(f(x.At(Number<Is>{}), y.At(Number<Is>{}))...);
}
template <typename F, typename X, typename Y, typename Z, index_t... Is>
__host__ __device__ constexpr auto
transform_tuples_impl(F f, const X& x, const Y& y, const Z& z, Sequence<Is...>)
{
return make_tuple(f(x.At(Number<Is>{}), y.At(Number<Is>{}), z.At(Number<Is>{}))...);
}
} // namespace detail
template <typename F, typename X>
......@@ -141,5 +148,12 @@ __host__ __device__ constexpr auto transform_tuples(F f, const X& x, const Y& y)
f, x, y, typename arithmetic_sequence_gen<0, X::Size(), 1>::type{});
}
template <typename F, typename X, typename Y, typename Z>
__host__ __device__ constexpr auto transform_tuples(F f, const X& x, const Y& y, const Z& z)
{
return detail::transform_tuples_impl(
f, x, y, z, typename arithmetic_sequence_gen<0, X::Size(), 1>::type{});
}
} // namespace ck
#endif
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