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Verify HostTensorDescriptor when it is created (#2829)
* 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>
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emezh
@@ -95,25 +95,26 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[])
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exit(0);
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}
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using DefaultLayout = ck::tensor_layout::gemm::RowMajor;
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// For Real Part of Complex Tensor
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Tensor<ADataType> a_ms_ks_re(a_ms_ks_lengths, a_ms_ks_strides);
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Tensor<BDataType> b_ns_ks_re(b_ns_ks_lengths, b_ns_ks_strides);
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Tensor<EDataType> d_ms_ns_re(d_ms_ns_lengths, d_ms_ns_strides);
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Tensor<ADataType> a_ms_ks_re(a_ms_ks_lengths, a_ms_ks_strides, DefaultLayout{});
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Tensor<BDataType> b_ns_ks_re(b_ns_ks_lengths, b_ns_ks_strides, DefaultLayout{});
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Tensor<EDataType> d_ms_ns_re(d_ms_ns_lengths, d_ms_ns_strides, DefaultLayout{});
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Tensor<EDataType> e_ms_ns_host_result_re(e_ms_ns_lengths, e_ms_ns_strides);
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Tensor<EDataType> e_ms_ns_device_result_re(e_ms_ns_lengths, e_ms_ns_strides);
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Tensor<EDataType> e_ms_ns_host_result_re(e_ms_ns_lengths, e_ms_ns_strides, DefaultLayout{});
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Tensor<EDataType> e_ms_ns_device_result_re(e_ms_ns_lengths, e_ms_ns_strides, DefaultLayout{});
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// For Imaginary Part of Complex Tensor
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Tensor<ADataType> a_ms_ks_img(a_ms_ks_lengths, a_ms_ks_strides);
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Tensor<BDataType> b_ns_ks_img(b_ns_ks_lengths, b_ns_ks_strides);
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Tensor<EDataType> d_ms_ns_img(d_ms_ns_lengths, d_ms_ns_strides);
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Tensor<ADataType> a_ms_ks_img(a_ms_ks_lengths, a_ms_ks_strides, DefaultLayout{});
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Tensor<BDataType> b_ns_ks_img(b_ns_ks_lengths, b_ns_ks_strides, DefaultLayout{});
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Tensor<EDataType> d_ms_ns_img(d_ms_ns_lengths, d_ms_ns_strides, DefaultLayout{});
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Tensor<EDataType> e_ms_ns_host_result_img(e_ms_ns_lengths, e_ms_ns_strides);
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Tensor<EDataType> e_ms_ns_device_result_img(e_ms_ns_lengths, e_ms_ns_strides);
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Tensor<EDataType> e_ms_ns_host_result_img(e_ms_ns_lengths, e_ms_ns_strides, DefaultLayout{});
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Tensor<EDataType> e_ms_ns_device_result_img(e_ms_ns_lengths, e_ms_ns_strides, DefaultLayout{});
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// Intermediate E tensor Definition
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Tensor<EDataType> e_ms_ns_device_result_re1(e_ms_ns_lengths, e_ms_ns_strides);
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Tensor<EDataType> e_ms_ns_device_result_img1(e_ms_ns_lengths, e_ms_ns_strides);
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Tensor<EDataType> e_ms_ns_device_result_re1(e_ms_ns_lengths, e_ms_ns_strides, DefaultLayout{});
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Tensor<EDataType> e_ms_ns_device_result_img1(e_ms_ns_lengths, e_ms_ns_strides, DefaultLayout{});
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std::cout << "a_ms_ks_re: " << a_ms_ks_re.mDesc << std::endl;
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std::cout << "b_ns_ks_re: " << b_ns_ks_re.mDesc << std::endl;
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@@ -349,8 +350,10 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[])
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if(do_verification)
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{
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// Real Part Verification
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Tensor<CShuffleDataType> c_ms_ns_host_result_re(e_ms_ns_lengths, e_ms_ns_strides);
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Tensor<CShuffleDataType> c_ms_ns_host_result_re1(e_ms_ns_lengths, e_ms_ns_strides);
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Tensor<CShuffleDataType> c_ms_ns_host_result_re(
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e_ms_ns_lengths, e_ms_ns_strides, DefaultLayout{});
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Tensor<CShuffleDataType> c_ms_ns_host_result_re1(
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e_ms_ns_lengths, e_ms_ns_strides, DefaultLayout{});
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using ReferenceOpInstance =
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ck::tensor_operation::host::ReferenceContraction_M2_N2_K2<NumDimM,
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@@ -422,8 +425,10 @@ int run_complex_contraction_bilinear_example(int argc, char* argv[])
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isRealOk = ck::utils::check_err(e_ms_ns_device_result_re, e_ms_ns_host_result_re) ? 0 : 1;
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// Img Part Verification
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Tensor<CShuffleDataType> c_ms_ns_host_result_img(e_ms_ns_lengths, e_ms_ns_strides);
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Tensor<CShuffleDataType> c_ms_ns_host_result_img1(e_ms_ns_lengths, e_ms_ns_strides);
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Tensor<CShuffleDataType> c_ms_ns_host_result_img(
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e_ms_ns_lengths, e_ms_ns_strides, DefaultLayout{});
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Tensor<CShuffleDataType> c_ms_ns_host_result_img1(
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e_ms_ns_lengths, e_ms_ns_strides, DefaultLayout{});
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auto ref_argument_img = ref_op.MakeArgument(
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a_ms_ks_re, b_ns_ks_img, c_ms_ns_host_result_img, a_element_op, b_element_op);
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