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Commit 995c6b1c authored by Astha Rai's avatar Astha Rai
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working column major implementation

parent bcc66c9b
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Showing with 44 additions and 50 deletions
example/65_hip_tensor_permute/elementwise_permute_4D_fp16_col.cpp
View file @ 995c6b1c
...@@ -38,15 +38,22 @@ void host_elementwise4D(HostTensorB& B_nhwc, ...@@ -38,15 +38,22 @@ void host_elementwise4D(HostTensorB& B_nhwc,
FunctorB functor_b, FunctorB functor_b,
float scale) float scale)
{ {
for(std::size_t n = 0; n < A_nchw.mDesc.GetLengths()[0]; ++n) std::size_t N = A_nchw.mDesc.GetLengths()[0];
for(std::size_t c = 0; c < A_nchw.mDesc.GetLengths()[1]; ++c) std::size_t C = A_nchw.mDesc.GetLengths()[1];
for(std::size_t h = 0; h < A_nchw.mDesc.GetLengths()[2]; ++h) std::size_t H = A_nchw.mDesc.GetLengths()[2];
for(std::size_t w = 0; w < A_nchw.mDesc.GetLengths()[3]; ++w) std::size_t W = A_nchw.mDesc.GetLengths()[3];
for(std::size_t w = 0; w < W; ++w)
for(std::size_t h = 0; h < H; ++h)
for(std::size_t c = 0; c < C; ++c)
for(std::size_t n = 0; n < N; ++n)
{ {
ADataType tmp_val; ADataType tmp_val;
auto a_val = A_nchw(n, c, h, w); // auto a_val = A_nchw(n, c, h, w);
auto a_val = A_nchw.mData[(n) + (c * N) + (h * C * N) + (w * H * C * N)];
functor_b(tmp_val, a_val); functor_b(tmp_val, a_val);
functor_a(B_nhwc(n, h, w, c), scale * tmp_val); // functor_a(B_nhwc(n, h, w, c), scale * tmp_val);
functor_a(B_nhwc.mData[(n) + (c * W * H * N) + (h * N) + (w * H * N)],
scale * tmp_val);
} }
} }
...@@ -60,13 +67,7 @@ int main() ...@@ -60,13 +67,7 @@ int main()
Tensor<ADataType> a(nchw); Tensor<ADataType> a(nchw);
Tensor<BDataType> b(nhwc); Tensor<BDataType> b(nhwc);
float scale = 1.f; float scale = 1.f;
// a.GenerateTensorValue(GeneratorTensor_3<ADataType>{0.0, 1.0}); auto i = 0;
//
// for(std::size_t i = 0; i < a.mData.size(); i++){
// a.mData[i] = i;
// }
//
auto i = 0;
for(std::size_t w = 0; w < a.mDesc.GetLengths()[3]; ++w) for(std::size_t w = 0; w < a.mDesc.GetLengths()[3]; ++w)
for(std::size_t h = 0; h < a.mDesc.GetLengths()[2]; ++h) for(std::size_t h = 0; h < a.mDesc.GetLengths()[2]; ++h)
for(std::size_t c = 0; c < a.mDesc.GetLengths()[1]; ++c) for(std::size_t c = 0; c < a.mDesc.GetLengths()[1]; ++c)
...@@ -86,15 +87,16 @@ int main() ...@@ -86,15 +87,16 @@ int main()
std::array<void*, 1> output = {b_device_buf.GetDeviceBuffer()}; std::array<void*, 1> output = {b_device_buf.GetDeviceBuffer()};
std::array<ck::index_t, 4> ab_lengths; std::array<ck::index_t, 4> ab_lengths;
std::array<ck::index_t, 4> a_strides = {static_cast<int>(nchw[1] * nchw[2] * nchw[3]),
static_cast<int>(nchw[2] * nchw[3]),
static_cast<int>(nchw[3]),
1};
std::array<ck::index_t, 4> b_strides = {static_cast<int>(nhwc[1] * nhwc[2] * nhwc[3]),
1,
static_cast<int>(nhwc[2] * nhwc[3]),
static_cast<int>(nhwc[3])};
std::array<ck::index_t, 4> a_strides = {1,
static_cast<int>(nchw[0]),
static_cast<int>(nchw[0] * nchw[1]),
static_cast<int>(nchw[0] * nchw[1] * nchw[2])};
std::array<ck::index_t, 4> b_strides = {1,
static_cast<int>(nhwc[0] * nhwc[1] * nhwc[2]),
static_cast<int>(nhwc[0]),
static_cast<int>(nhwc[0] * nhwc[1])};
ck::ranges::copy(nchw, ab_lengths.begin()); ck::ranges::copy(nchw, ab_lengths.begin());
auto broadcastPermute = DeviceElementwisePermuteInstance{}; auto broadcastPermute = DeviceElementwisePermuteInstance{};
...@@ -133,16 +135,12 @@ int main() ...@@ -133,16 +135,12 @@ int main()
bool pass = true; bool pass = true;
LogRangeAsType<float>(std::cout << "A : ", a.mData, ",") << std::endl;
if(do_verification) if(do_verification)
{ {
b_device_buf.FromDevice(b.mData.data()); b_device_buf.FromDevice(b.mData.data());
Tensor<BDataType> host_b(nhwc); Tensor<BDataType> host_b(nhwc);
host_elementwise4D(host_b, a, PassThrough{}, UnaryOp{}, scale); host_elementwise4D(host_b, a, PassThrough{}, UnaryOp{}, scale);
LogRangeAsType<float>(std::cout << "B : ", b.mData, ",") << std::endl;
LogRangeAsType<float>(std::cout << "Host B : ", host_b.mData, ",") << std::endl;
pass &= pass &=
ck::utils::check_err(b.mData, host_b.mData, "Error: Incorrect results b", 1e-3, 1e-3); ck::utils::check_err(b.mData, host_b.mData, "Error: Incorrect results b", 1e-3, 1e-3);
} }
......
example/65_hip_tensor_permute/elementwise_permute_4D_fp32_col.cpp
View file @ 995c6b1c
...@@ -38,15 +38,20 @@ void host_elementwise4D(HostTensorB& B_nhwc, ...@@ -38,15 +38,20 @@ void host_elementwise4D(HostTensorB& B_nhwc,
FunctorB functor_b, FunctorB functor_b,
float scale) float scale)
{ {
for(std::size_t n = 0; n < A_nchw.mDesc.GetLengths()[0]; ++n) std::size_t N = A_nchw.mDesc.GetLengths()[0];
for(std::size_t c = 0; c < A_nchw.mDesc.GetLengths()[1]; ++c) std::size_t C = A_nchw.mDesc.GetLengths()[1];
for(std::size_t h = 0; h < A_nchw.mDesc.GetLengths()[2]; ++h) std::size_t H = A_nchw.mDesc.GetLengths()[2];
for(std::size_t w = 0; w < A_nchw.mDesc.GetLengths()[3]; ++w) std::size_t W = A_nchw.mDesc.GetLengths()[3];
for(std::size_t w = 0; w < W; ++w)
for(std::size_t h = 0; h < H; ++h)
for(std::size_t c = 0; c < C; ++c)
for(std::size_t n = 0; n < N; ++n)
{ {
ADataType tmp_val; ADataType tmp_val;
auto a_val = A_nchw(n, c, h, w); auto a_val = A_nchw.mData[(n) + (c * N) + (h * C * N) + (w * H * C * N)];
functor_b(tmp_val, a_val); functor_b(tmp_val, a_val);
functor_a(B_nhwc(n, h, w, c), scale * tmp_val); functor_a(B_nhwc.mData[(n) + (c * W * H * N) + (h * N) + (w * H * N)],
scale * tmp_val);
} }
} }
...@@ -60,13 +65,7 @@ int main() ...@@ -60,13 +65,7 @@ int main()
Tensor<ADataType> a(nchw); Tensor<ADataType> a(nchw);
Tensor<BDataType> b(nhwc); Tensor<BDataType> b(nhwc);
float scale = 1.f; float scale = 1.f;
// a.GenerateTensorValue(GeneratorTensor_3<ADataType>{0.0, 1.0}); auto i = 0;
//
// for(std::size_t i = 0; i < a.mData.size(); i++){
// a.mData[i] = i;
// }
//
auto i = 0;
for(std::size_t w = 0; w < a.mDesc.GetLengths()[3]; ++w) for(std::size_t w = 0; w < a.mDesc.GetLengths()[3]; ++w)
for(std::size_t h = 0; h < a.mDesc.GetLengths()[2]; ++h) for(std::size_t h = 0; h < a.mDesc.GetLengths()[2]; ++h)
for(std::size_t c = 0; c < a.mDesc.GetLengths()[1]; ++c) for(std::size_t c = 0; c < a.mDesc.GetLengths()[1]; ++c)
...@@ -86,15 +85,16 @@ int main() ...@@ -86,15 +85,16 @@ int main()
std::array<void*, 1> output = {b_device_buf.GetDeviceBuffer()}; std::array<void*, 1> output = {b_device_buf.GetDeviceBuffer()};
std::array<ck::index_t, 4> ab_lengths; std::array<ck::index_t, 4> ab_lengths;
std::array<ck::index_t, 4> a_strides = {static_cast<int>(nchw[1] * nchw[2] * nchw[3]),
static_cast<int>(nchw[2] * nchw[3]),
static_cast<int>(nchw[3]),
1};
std::array<ck::index_t, 4> b_strides = {static_cast<int>(nhwc[1] * nhwc[2] * nhwc[3]),
1,
static_cast<int>(nhwc[2] * nhwc[3]),
static_cast<int>(nhwc[3])};
std::array<ck::index_t, 4> a_strides = {1,
static_cast<int>(nchw[0]),
static_cast<int>(nchw[0] * nchw[1]),
static_cast<int>(nchw[0] * nchw[1] * nchw[2])};
std::array<ck::index_t, 4> b_strides = {1,
static_cast<int>(nhwc[0] * nhwc[1] * nhwc[2]),
static_cast<int>(nhwc[0]),
static_cast<int>(nhwc[0] * nhwc[1])};
ck::ranges::copy(nchw, ab_lengths.begin()); ck::ranges::copy(nchw, ab_lengths.begin());
auto broadcastPermute = DeviceElementwisePermuteInstance{}; auto broadcastPermute = DeviceElementwisePermuteInstance{};
...@@ -133,16 +133,12 @@ int main() ...@@ -133,16 +133,12 @@ int main()
bool pass = true; bool pass = true;
LogRangeAsType<float>(std::cout << "A : ", a.mData, ",") << std::endl;
if(do_verification) if(do_verification)
{ {
b_device_buf.FromDevice(b.mData.data()); b_device_buf.FromDevice(b.mData.data());
Tensor<BDataType> host_b(nhwc); Tensor<BDataType> host_b(nhwc);
host_elementwise4D(host_b, a, PassThrough{}, UnaryOp{}, scale); host_elementwise4D(host_b, a, PassThrough{}, UnaryOp{}, scale);
LogRangeAsType<float>(std::cout << "B : ", b.mData, ",") << std::endl;
LogRangeAsType<float>(std::cout << "Host B : ", host_b.mData, ",") << std::endl;
pass &= pass &=
ck::utils::check_err(b.mData, host_b.mData, "Error: Incorrect results b", 1e-3, 1e-3); ck::utils::check_err(b.mData, host_b.mData, "Error: Incorrect results b", 1e-3, 1e-3);
} }
......
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