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Commit db775824 authored by Jehandad Khan's avatar Jehandad Khan
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Merge branch 'develop' into jd/dev_pkg

parents 74397984 7c0b1498
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Showing with 16 additions and 86 deletions
test/reduce/reduce_no_index.cpp
View file @ db775824
...@@ -37,19 +37,6 @@ static inline std::vector<int> get_invariant_dims(const std::vector<int>& reduce ...@@ -37,19 +37,6 @@ static inline std::vector<int> get_invariant_dims(const std::vector<int>& reduce
return invariantDims; return invariantDims;
}; };
// map the data type used by the GPU kernels to the corresponding type used by the host codes
template <typename InType>
struct type_mapping
{
using OutType = InType;
};
template <>
struct type_mapping<ck::half_t>
{
using OutType = half_float::half;
};
constexpr int Rank = 4; constexpr int Rank = 4;
constexpr ReduceTensorOp ReduceOpId = ReduceTensorOp::AVG; constexpr ReduceTensorOp ReduceOpId = ReduceTensorOp::AVG;
...@@ -226,13 +213,9 @@ bool test_reduce_no_index_impl(int init_method, ...@@ -226,13 +213,9 @@ bool test_reduce_no_index_impl(int init_method,
bool result = true; bool result = true;
using HostInDataType = typename type_mapping<InDataType>::OutType; ReductionHost<InDataType,
using HostOutDataType = typename type_mapping<OutDataType>::OutType; AccDataType,
using HostAccDataType = typename type_mapping<AccDataType>::OutType; OutDataType,
ReductionHost<HostInDataType,
HostAccDataType,
HostOutDataType,
ReduceOpId, ReduceOpId,
Rank, Rank,
NumReduceDim, NumReduceDim,
...@@ -240,11 +223,7 @@ bool test_reduce_no_index_impl(int init_method, ...@@ -240,11 +223,7 @@ bool test_reduce_no_index_impl(int init_method,
NeedIndices> NeedIndices>
hostReduce(in.mDesc, out_ref.mDesc, invariantDims, reduceDims); hostReduce(in.mDesc, out_ref.mDesc, invariantDims, reduceDims);
hostReduce.Run(alpha, hostReduce.Run(alpha, in.mData.data(), beta, out_ref.mData.data(), nullptr);
reinterpret_cast<const HostInDataType*>(in.mData.data()),
beta,
reinterpret_cast<HostOutDataType*>(out_ref.mData.data()),
nullptr);
const auto i_inLengths = to_int_vector(inLengths); const auto i_inLengths = to_int_vector(inLengths);
const auto i_inStrides = to_int_vector(inStrides); const auto i_inStrides = to_int_vector(inStrides);
......
test/reduce/reduce_with_index.cpp
View file @ db775824
...@@ -36,19 +36,6 @@ static inline std::vector<int> get_invariant_dims(const std::vector<int>& reduce ...@@ -36,19 +36,6 @@ static inline std::vector<int> get_invariant_dims(const std::vector<int>& reduce
return invariantDims; return invariantDims;
}; };
// map the data type used by the GPU kernels to the corresponding type used by the host codes
template <typename InType>
struct type_mapping
{
using OutType = InType;
};
template <>
struct type_mapping<ck::half_t>
{
using OutType = half_float::half;
};
constexpr int Rank = 4; constexpr int Rank = 4;
constexpr ReduceTensorOp ReduceOpId = ReduceTensorOp::AMAX; constexpr ReduceTensorOp ReduceOpId = ReduceTensorOp::AMAX;
...@@ -209,13 +196,9 @@ bool test_reduce_with_index_impl(int init_method, ...@@ -209,13 +196,9 @@ bool test_reduce_with_index_impl(int init_method,
bool result = true; bool result = true;
using HostInDataType = typename type_mapping<InDataType>::OutType; ReductionHost<InDataType,
using HostOutDataType = typename type_mapping<OutDataType>::OutType; AccDataType,
using HostAccDataType = typename type_mapping<AccDataType>::OutType; OutDataType,
ReductionHost<HostInDataType,
HostAccDataType,
HostOutDataType,
ReduceOpId, ReduceOpId,
Rank, Rank,
NumReduceDim, NumReduceDim,
...@@ -223,11 +206,8 @@ bool test_reduce_with_index_impl(int init_method, ...@@ -223,11 +206,8 @@ bool test_reduce_with_index_impl(int init_method,
NeedIndices> NeedIndices>
hostReduce(in.mDesc, out_ref.mDesc, invariantDims, reduceDims); hostReduce(in.mDesc, out_ref.mDesc, invariantDims, reduceDims);
hostReduce.Run(alpha, hostReduce.Run(
reinterpret_cast<const HostInDataType*>(in.mData.data()), alpha, in.mData.data(), beta, out_ref.mData.data(), out_indices_ref.mData.data());
beta,
reinterpret_cast<HostOutDataType*>(out_ref.mData.data()),
out_indices_ref.mData.data());
const auto i_inLengths = to_int_vector(inLengths); const auto i_inLengths = to_int_vector(inLengths);
const auto i_inStrides = to_int_vector(inStrides); const auto i_inStrides = to_int_vector(inStrides);
......
test/reference_conv_fwd/CMakeLists.txt
View file @ db775824
add_test_executable(test_reference_conv_fwd reference_conv_fwd.cpp) add_test_executable(test_reference_conv_fwd reference_conv_fwd.cpp)
target_link_libraries(test_reference_conv_fwd PRIVATE host_tensor) target_link_libraries(test_reference_conv_fwd PRIVATE host_tensor conv_fwd_util)
test/reference_conv_fwd/reference_conv_fwd.cpp
View file @ db775824
#include <algorithm>
#include <cmath> #include <cmath>
#include <cstdlib> #include <cstdlib>
#include <half.hpp> #include <half.hpp>
...@@ -10,6 +9,7 @@ ...@@ -10,6 +9,7 @@
#include "config.hpp" #include "config.hpp"
#include "conv_fwd_util.hpp" #include "conv_fwd_util.hpp"
#include "element_wise_operation.hpp" #include "element_wise_operation.hpp"
#include "fill.hpp"
#include "host_tensor.hpp" #include "host_tensor.hpp"
#include "reference_conv_fwd.hpp" #include "reference_conv_fwd.hpp"
#include "tensor_layout.hpp" #include "tensor_layout.hpp"
...@@ -19,35 +19,6 @@ using InElementOp = ck::tensor_operation::element_wise::PassThrough; ...@@ -19,35 +19,6 @@ using InElementOp = ck::tensor_operation::element_wise::PassThrough;
using WeiElementOp = ck::tensor_operation::element_wise::PassThrough; using WeiElementOp = ck::tensor_operation::element_wise::PassThrough;
using OutElementOp = ck::tensor_operation::element_wise::PassThrough; using OutElementOp = ck::tensor_operation::element_wise::PassThrough;
template <typename T>
struct FillMonotonicSeq
{
T m_init_value{0};
T m_step{1};
template <typename ForwardIter>
void operator()(ForwardIter first, ForwardIter last) const
{
std::generate(first, last, [=, n = m_init_value]() mutable {
auto tmp = n;
n += m_step;
return tmp;
});
}
};
template <typename T>
struct FillConstant
{
T m_value{0};
template <typename ForwardIter>
void operator()(ForwardIter first, ForwardIter last) const
{
std::fill(first, last, m_value);
}
};
template <ck::index_t NDim, template <ck::index_t NDim,
typename InDataType = float, typename InDataType = float,
typename WeiDataType = float, typename WeiDataType = float,
...@@ -55,8 +26,8 @@ template <ck::index_t NDim, ...@@ -55,8 +26,8 @@ template <ck::index_t NDim,
typename InLayout = ck::tensor_layout::convolution::NHWC, typename InLayout = ck::tensor_layout::convolution::NHWC,
typename WeiLayout = ck::tensor_layout::convolution::KYXC, typename WeiLayout = ck::tensor_layout::convolution::KYXC,
typename OutLayout = ck::tensor_layout::convolution::NHWK, typename OutLayout = ck::tensor_layout::convolution::NHWK,
typename FillInputOp = FillMonotonicSeq<InDataType>, typename FillInputOp = ck::utils::FillMonotonicSeq<InDataType>,
typename FillWeightsOp = FillConstant<WeiDataType>> typename FillWeightsOp = ck::utils::FillConstant<WeiDataType>>
Tensor<OutDataType> Tensor<OutDataType>
run_reference_convolution_forward(const ck::utils::conv::ConvParams& params, run_reference_convolution_forward(const ck::utils::conv::ConvParams& params,
const FillInputOp& fill_input_op = FillInputOp{}, const FillInputOp& fill_input_op = FillInputOp{},
...@@ -251,7 +222,7 @@ bool test_conv1d_nwc() ...@@ -251,7 +222,7 @@ bool test_conv1d_nwc()
ck::tensor_layout::convolution::NWC, ck::tensor_layout::convolution::NWC,
ck::tensor_layout::convolution::KXC, ck::tensor_layout::convolution::KXC,
ck::tensor_layout::convolution::NWK>( ck::tensor_layout::convolution::NWK>(
params, FillMonotonicSeq<float>{0.f, 0.1f}); params, ck::utils::FillMonotonicSeq<float>{0.f, 0.1f});
ref_dims = std::vector<std::size_t>{2, 16, 16}; ref_dims = std::vector<std::size_t>{2, 16, 16};
ref_data = std::vector<float>{ ref_data = std::vector<float>{
...@@ -349,7 +320,7 @@ bool test_conv3d_ncdhw() ...@@ -349,7 +320,7 @@ bool test_conv3d_ncdhw()
ck::tensor_layout::convolution::NCDHW, ck::tensor_layout::convolution::NCDHW,
ck::tensor_layout::convolution::KCZYX, ck::tensor_layout::convolution::KCZYX,
ck::tensor_layout::convolution::NKDHW>( ck::tensor_layout::convolution::NKDHW>(
params, FillMonotonicSeq<float>{0.f, 0.1f}); params, ck::utils::FillMonotonicSeq<float>{0.f, 0.1f});
std::vector<std::size_t> ref_dims{1, 1, 4, 4, 4}; std::vector<std::size_t> ref_dims{1, 1, 4, 4, 4};
std::vector<float> ref_data{ std::vector<float> ref_data{
407.7, 410.40002, 413.09998, 415.80002, 423.90002, 426.6, 429.30002, 432., 407.7, 410.40002, 413.09998, 415.80002, 423.90002, 426.6, 429.30002, 432.,
...@@ -383,7 +354,7 @@ bool test_conv3d_ncdhw() ...@@ -383,7 +354,7 @@ bool test_conv3d_ncdhw()
ck::tensor_layout::convolution::NCDHW, ck::tensor_layout::convolution::NCDHW,
ck::tensor_layout::convolution::KCZYX, ck::tensor_layout::convolution::KCZYX,
ck::tensor_layout::convolution::NKDHW>( ck::tensor_layout::convolution::NKDHW>(
params, FillMonotonicSeq<float>{0.f, 0.1f}); params, ck::utils::FillMonotonicSeq<float>{0.f, 0.1f});
ref_dims = std::vector<std::size_t>{1, 2, 4, 4, 4}; ref_dims = std::vector<std::size_t>{1, 2, 4, 4, 4};
ref_data = std::vector<float>{ ref_data = std::vector<float>{
2756.7002, 2764.7998, 2772.9001, 2781., 2853.9001, 2862., 2870.1, 2878.2002, 2756.7002, 2764.7998, 2772.9001, 2781., 2853.9001, 2862., 2870.1, 2878.2002,
......
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