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Verify HostTensorDescriptor when it is created (#2829)

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* add proper GEMM layout verification

* Handle "auto" strides.

CalculateStrides only called when tensor's strides are empty or all of them are <=0 (auto strides).
CalculateStrides now supports GEMM::ColumnsMajor order. The assumption is still that it applies only to the inner two dims.
ValidateStrides throws if any of the tensor's strides is <=0.
profile_gemm_multiply_add updated to support "auto" strides for tensors.

Manual tests for profile_gemm_multiply_add (matrix B in Row and Col modes)
auto-strides
	bin/ckProfiler gemm_multiply_add 0 0 1 1 0 1 128 128 128 0 0 0 0 0
	bin/ckProfiler gemm_multiply_add 0 1 1 1 0 1 128 128 128 0 0 0 0 0
	bin/ckProfiler gemm_multiply_add 0 0 1 1 0 1 128 128 128 -1 -1 -1 -1 -1
Note, -1 should be deprecated (use 0 instead)

explicit strides (same as auto)
	bin/ckProfiler gemm_multiply_add 0 0 1 1 0 1 128 128 128 128 128 128 128 128
	bin/ckProfiler gemm_multiply_add 0 1 1 1 0 1 128 128 128 128 128 128 128 128

explicit strides (not the same as auto)
	bin/ckProfiler gemm_multiply_add 0 0 1 1 0 1 128 128 128 130 132 134 136 138
	bin/ckProfiler gemm_multiply_add 0 1 1 1 0 1 128 128 128 130 132 134 136 138

mix of explicit and auto strides
	bin/ckProfiler gemm_multiply_add 0 0 1 1 0 1 128 128 128 128 128 128 128 0

invalid stride
	bin/ckProfiler gemm_multiply_add 0 0 1 1 0 1 128 128 128 0 0 0 0 64
	terminate called after throwing an instance of 'std::runtime_error'
	  what():  Invalid strides for RowMajor: mLens: 128 128 , mStrides: 64 1
	Aborted (core dumped)

* - add more names to ck::tensor_layout for easier namespace hierarchy checking
- updated convolutional layouts to use explicit ones or BaseConvolutionalLayout where it is not clear which layout to use (TBD) - see include/ck/library/utility/convolution_host_tensor_descriptor_helper.hpp

* added handling of partially initialized strides for GEMM. fixed more tests.

* clang-format and more fixes

* replace long dash by a simple hyphen - causes build failure in CK codegen.

* increase sizeof input, otherwise output size becomes zero or negative with large filter size

* select stride based on layout

* specify layout explicitly to avoid errors in HostTensorDescriptor creation

* add validation for higher GEMM tensor dimensions.; Add docstring to `HostTensorDescriptor`

* Not clear why permute test in test/permute_scale/test_permute_scale.cpp uses a lot of invalid strides. Setting layout to BypassLayoutVerification to avoid a lot of errors

* fix test (incl removing invalid config)

* fix moe examples:
- (in .cpp) add layout argument to non-2D tensors
- (in .hpp) fix asserts/failures that show up in Debug mode, specifically addressing 2D tensor by a single index (and 3D tensor by 2d index)

* fix moe_gemm2 example.

* fix profile and wmma examples

* clean-up early mods for ckprofile. verified with:
```
ckProfiler gemm_multiply_add 0 0 1 1 0 1 128 128 128 0 0 0 0 0
ckProfiler gemm_multiply_add 0 1 1 1 0 1 128 128 128 0 0 0 0 0
ckProfiler gemm_multiply_add 0 0 1 1 0 1 128 128 128 130 132 134 136 138
ckProfiler gemm_multiply_add 0 1 1 1 0 1 128 128 128 130 132 134 136 138
#
ckProfiler gemm_fastgelu 1 0 1 2 0 1 128 128 128 0 0 0
ckProfiler gemm_fastgelu 1 1 1 2 0 1 128 128 128 0 0 0
ckProfiler gemm_fastgelu 1 2 1 2 0 1 128 128 128 0 0 0
ckProfiler gemm_fastgelu 1 3 1 2 0 1 128 128 128 0 0 0
ckProfiler gemm_fastgelu 1 0 1 2 0 1 128 128 128 128 128 128
#
ckProfiler gemm_add_relu 0 0 1 1 0 1 128 128 128 0 0 0 0
# ckProfiler gemm_add_relu 0 1 1 1 0 1 128 128 128 0 0 0 0    # not implemented
# ckProfiler gemm_add_relu 0 2 1 1 0 1 128 128 128 0 0 0 0    # not implemented
# ckProfiler gemm_add_relu 0 3 1 1 0 1 128 128 128 0 0 0 0    # not implemented
ckProfiler gemm_add_relu 0 0 1 1 0 1 128 128 128 128 128 128 128
#
ckProfiler gemm_add_relu_add_layernorm 1 0 1 1 0 0 128 128 128 0 0 0 0 0
ckProfiler gemm_add_relu_add_layernorm 1 1 1 1 0 0 128 128 128 0 0 0 0 0
ckProfiler gemm_add_relu_add_layernorm 1 2 1 1 0 0 128 128 128 0 0 0 0 0
ckProfiler gemm_add_relu_add_layernorm 1 3 1 1 0 0 128 128 128 0 0 0 0 0
ckProfiler gemm_add_relu_add_layernorm 1 0 1 1 0 0 128 128 128 130 132 134 136 138
#
example_gemm_add_multiply_dl_fp16
example_gemm_add_multiply_xdl_fp16
#
ckProfiler gemm_blockscale_wp 7 1 1 1 1 0 1 128 128 128 0 0 0
ckProfiler gemm_blockscale_wp 7 1 1 1 1 0 1 128 128 128 128 128 128
```

* temporary skip first 8 test configs - they throw error

* temporary skip first 8 test configs in wmma too - they throw error

---------

Co-authored-by: Illia Silin <98187287+illsilin@users.noreply.github.com>
This commit is contained in:
emezh
2025-09-25 21:22:13 -04:00
committed by GitHub
parent ec4d16b991
commit db2524be2d
122 changed files with 1732 additions and 848 deletions
Download Patch File Download Diff File Expand all files Collapse all files

20
example/61_contraction_multi_ABD/contraction_multi_ABD_xdl_fp16.cpp
View File

@@ -19,6 +19,9 @@
#include "ck/library/utility/check_err.hpp"
#include "ck/library/utility/numeric.hpp"
using Row = ck::tensor_layout::gemm::RowMajor;
using Bypass = ck::tensor_layout::BypassLayoutVerification;
template <ck::index_t... Is>
using S = ck::Sequence<Is...>;
@@ -160,12 +163,12 @@ int main(int argc, char* argv[])
exit(0);
}
Tensor<A0DataType> a0_ms_ks(a0_ms_ks_lengths, a0_ms_ks_strides);
Tensor<A1DataType> a1_ms_ks(a1_ms_ks_lengths, a1_ms_ks_strides);
Tensor<BDataType> b_ns_ks(b_ns_ks_lengths, b_ns_ks_strides);
Tensor<EDataType> d_ms_ns(d_ms_ns_lengths, d_ms_ns_strides);
Tensor<EDataType> e_ms_ns_host_result(e_ms_ns_lengths, e_ms_ns_strides);
Tensor<EDataType> e_ms_ns_device_result(e_ms_ns_lengths, e_ms_ns_strides);
Tensor<A0DataType> a0_ms_ks(a0_ms_ks_lengths, a0_ms_ks_strides, Row{});
Tensor<A1DataType> a1_ms_ks(a1_ms_ks_lengths, a1_ms_ks_strides, Bypass{});
Tensor<BDataType> b_ns_ks(b_ns_ks_lengths, b_ns_ks_strides, Row{});
Tensor<EDataType> d_ms_ns(d_ms_ns_lengths, d_ms_ns_strides, Row{});
Tensor<EDataType> e_ms_ns_host_result(e_ms_ns_lengths, e_ms_ns_strides, Row{});
Tensor<EDataType> e_ms_ns_device_result(e_ms_ns_lengths, e_ms_ns_strides, Row{});
std::cout << "a0_ms_ks: " << a0_ms_ks.mDesc << std::endl;
std::cout << "a1_ms_ks: " << a1_ms_ks.mDesc << std::endl;
@@ -264,9 +267,9 @@ int main(int argc, char* argv[])
if(do_verification)
{
Tensor<CShuffleDataType> c_ms_ns_host_result(e_ms_ns_lengths, e_ms_ns_strides);
Tensor<CShuffleDataType> c_ms_ns_host_result(e_ms_ns_lengths, e_ms_ns_strides, Row{});
Tensor<A0DataType> a_ms_ks(a0_ms_ks_lengths, a0_ms_ks_strides);
Tensor<A0DataType> a_ms_ks(a0_ms_ks_lengths, a0_ms_ks_strides, Row{});
for(size_t m0 = 0; m0 < a_ms_ks.mDesc.GetLengths()[0]; ++m0)
{
@@ -299,7 +302,6 @@ int main(int argc, char* argv[])
auto ref_op = ReferenceOpInstance{};
auto ref_invoker = ref_op.MakeInvoker();
Tensor<float> empty_tensor(std::vector<ck::index_t>{}, std::vector<ck::index_t>{});
auto ref_argument =
ref_op.MakeArgument(a_ms_ks, b_ns_ks, c_ms_ns_host_result, PassThrough{}, b_element_op);

21
example/61_contraction_multi_ABD/contraction_multi_ABD_xdl_fp8.cpp
View File

@@ -19,6 +19,9 @@
#include "ck/library/utility/check_err.hpp"
#include "ck/library/utility/numeric.hpp"
using Row = ck::tensor_layout::gemm::RowMajor;
using Bypass = ck::tensor_layout::BypassLayoutVerification;
template <ck::index_t... Is>
using S = ck::Sequence<Is...>;
@@ -140,12 +143,12 @@ int main(int argc, char* argv[])
exit(0);
}
Tensor<A0DataType> a0_ms_ks(a0_ms_ks_lengths, a0_ms_ks_strides);
Tensor<A1DataType> a1_ms_ks(a1_ms_ks_lengths, a1_ms_ks_strides);
Tensor<B0DataType> b0_ns_ks(b0_ns_ks_lengths, b0_ns_ks_strides);
Tensor<B1DataType> b1_ns_ks(b1_ns_ks_lengths, b1_ns_ks_strides);
Tensor<EDataType> e_ms_ns_host_result(e_ms_ns_lengths, e_ms_ns_strides);
Tensor<EDataType> e_ms_ns_device_result(e_ms_ns_lengths, e_ms_ns_strides);
Tensor<A0DataType> a0_ms_ks(a0_ms_ks_lengths, a0_ms_ks_strides, Row{});
Tensor<A1DataType> a1_ms_ks(a1_ms_ks_lengths, a1_ms_ks_strides, Bypass{});
Tensor<B0DataType> b0_ns_ks(b0_ns_ks_lengths, b0_ns_ks_strides, Row{});
Tensor<B1DataType> b1_ns_ks(b1_ns_ks_lengths, b1_ns_ks_strides, Row{});
Tensor<EDataType> e_ms_ns_host_result(e_ms_ns_lengths, e_ms_ns_strides, Row{});
Tensor<EDataType> e_ms_ns_device_result(e_ms_ns_lengths, e_ms_ns_strides, Row{});
std::cout << "a0_ms_ks: " << a0_ms_ks.mDesc << std::endl;
std::cout << "a1_ms_ks: " << a1_ms_ks.mDesc << std::endl;
@@ -246,9 +249,9 @@ int main(int argc, char* argv[])
if(do_verification)
{
Tensor<CShuffleDataType> c_ms_ns_host_result(e_ms_ns_lengths, e_ms_ns_strides);
Tensor<CShuffleDataType> c_ms_ns_host_result(e_ms_ns_lengths, e_ms_ns_strides, Row{});
Tensor<A0DataType> a_ms_ks(a0_ms_ks_lengths, a0_ms_ks_strides);
Tensor<A0DataType> a_ms_ks(a0_ms_ks_lengths, a0_ms_ks_strides, Row{});
for(size_t m0 = 0; m0 < a_ms_ks.mDesc.GetLengths()[0]; ++m0)
{
@@ -266,7 +269,7 @@ int main(int argc, char* argv[])
}
}
Tensor<B0DataType> b_ns_ks(b0_ns_ks_lengths, b0_ns_ks_strides);
Tensor<B0DataType> b_ns_ks(b0_ns_ks_lengths, b0_ns_ks_strides, Row{});
for(size_t n0 = 0; n0 < b_ns_ks.mDesc.GetLengths()[0]; ++n0)
{