From ed5fe69b6612a5cf0dd52340f6781885d77afbc9 Mon Sep 17 00:00:00 2001 From: Gian Marco Iodice Date: Thu, 9 Jul 2020 08:41:10 +0100 Subject: COMPMID-3326: Update heuristic for GEMMReshaped and GEMMReshapedOnlyRHS - Update the heuristic for Arm Mali-G76 (F32) in order to use the OpenCL image2d object on GEMM - Create utility function to validate the support for image2d Change-Id: I0913ac5f27fd07992b0ac188af753a2abeb034ca Signed-off-by: Gian Marco Iodice Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/3559 Tested-by: Arm Jenkins Reviewed-by: Georgios Pinitas Comments-Addressed: Arm Jenkins --- arm_compute/core/CL/gemm/CLGEMMHelpers.h | 37 +++++++++++------ src/core/CL/gemm/CLGEMMHelpers.cpp | 48 ++++++++++++++-------- .../CLGEMMReshapedKernelConfigurationBifrost.cpp | 44 +++++++++++++++++++- ...MMReshapedOnlyRHSKernelConfigurationBifrost.cpp | 42 ++++++++++++++++++- .../kernels/CLGEMMMatrixMultiplyReshapedKernel.cpp | 19 +-------- .../CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.cpp | 19 +-------- .../CL/kernels/CLGEMMReshapeRHSMatrixKernel.cpp | 17 +------- 7 files changed, 144 insertions(+), 82 deletions(-) diff --git a/arm_compute/core/CL/gemm/CLGEMMHelpers.h b/arm_compute/core/CL/gemm/CLGEMMHelpers.h index a370f9171a..013c068cf7 100644 --- a/arm_compute/core/CL/gemm/CLGEMMHelpers.h +++ b/arm_compute/core/CL/gemm/CLGEMMHelpers.h @@ -29,32 +29,45 @@ namespace arm_compute { +class ITensorInfo; +struct GEMMRHSMatrixInfo; + namespace cl_gemm { /** Configure @ref GEMMLHSMatrixInfo and @ref GEMMRHSMatrixInfo * - * @param[in] m Number of rows (M) in the LHS matrix not reshaped - * @param[in] n Number of columns (N) in the RHS matrix not reshaped - * @param[in] m0 Number of rows processed by each thread/work-item - * @param[in] n0 Number of columns processed by each thread/work-item - * @param[in] k0 Number of inner accumulation performed by each thread/work-item - * @param[in] v0 Number of vertical blocks of size (m0xk0) stored on the same output row - * @param[in] h0 Number of horizontal blocks of size (k0xn0) stored on the same output row - * @param[in] lhs_interleave True if the v0 (m0xk0) blocks have to be interleaved in the output row - * @param[in] rhs_interleave True if the h0 (k0xn0) blocks have to be interleaved in the output row - * @param[in] lhs_transpose True if the (m0xk0) block has to be transposed before been stored - * @param[in] rhs_transpose True if the (k0xn0) block has to be transposed before been stored + * @param[in] m Number of rows (M) in the LHS matrix not reshaped + * @param[in] n Number of columns (N) in the RHS matrix not reshaped + * @param[in] m0 Number of rows processed by each thread/work-item + * @param[in] n0 Number of columns processed by each thread/work-item + * @param[in] k0 Number of inner accumulation performed by each thread/work-item + * @param[in] v0 Number of vertical blocks of size (m0xk0) stored on the same output row + * @param[in] h0 Number of horizontal blocks of size (k0xn0) stored on the same output row + * @param[in] lhs_interleave True if the v0 (m0xk0) blocks have to be interleaved in the output row + * @param[in] rhs_interleave True if the h0 (k0xn0) blocks have to be interleaved in the output row + * @param[in] lhs_transpose True if the (m0xk0) block has to be transposed before been stored + * @param[in] rhs_transpose True if the (k0xn0) block has to be transposed before been stored + * @param[in] export_to_cl_image (Optional) True if the RHS reshaped matrix has to be exported to cl_image * * @return @ref GEMMLHSMatrixInfo and @ref GEMMRHSMatrixInfo */ std::pair configure_lhs_rhs_info(unsigned int m, unsigned int n, unsigned int m0, unsigned int n0, unsigned int k0, unsigned int v0, unsigned int h0, - bool lhs_interleave, bool rhs_interleave, bool lhs_transpose, bool rhs_transpose); + bool lhs_interleave, bool rhs_interleave, bool lhs_transpose, bool rhs_transpose, bool export_to_cl_image = false); /** Update padding required to export the OpenCL buffer to OpenCL image2d * * @param[in,out] tensor ITensorInfo of the tensor required to be exported to OpenCL image2d */ void update_padding_for_cl_image(ITensorInfo *tensor); + +/** Utility function to validate the image2d OpenCL object support on the RHS reshaped matrix + * + * @param[in] tensor_reshaped_info TensorInfo for the RHS reshaped matrix + * @param[in] rhs_info @ref GEMMRHSMatrixInfo + * + * @return Status reporting if we can use the image2d OpenCL object on the RHS reshaped matrix + */ +Status validate_image2d_support_on_rhs(const ITensorInfo &tensor_reshaped_info, const GEMMRHSMatrixInfo &rhs_info); } // namespace cl_gemm } // namespace arm_compute #endif /*ARM_COMPUTE_CLGEMMHELPERS_H */ diff --git a/src/core/CL/gemm/CLGEMMHelpers.cpp b/src/core/CL/gemm/CLGEMMHelpers.cpp index 1165e70273..5734c93021 100644 --- a/src/core/CL/gemm/CLGEMMHelpers.cpp +++ b/src/core/CL/gemm/CLGEMMHelpers.cpp @@ -23,7 +23,10 @@ */ #include "arm_compute/core/CL/gemm/CLGEMMHelpers.h" +#include "arm_compute/core/CL/CLHelpers.h" #include "arm_compute/core/CL/CLKernelLibrary.h" +#include "arm_compute/core/CL/OpenCL.h" +#include "arm_compute/core/ITensorInfo.h" #include @@ -32,24 +35,13 @@ namespace arm_compute namespace cl_gemm { std::pair configure_lhs_rhs_info(unsigned int m, unsigned int n, unsigned int m0, unsigned int n0, unsigned int k0, unsigned int v0, unsigned int h0, - bool lhs_interleave, bool rhs_interleave, bool lhs_transpose, bool rhs_transpose) + bool lhs_interleave, bool rhs_interleave, bool lhs_transpose, bool rhs_transpose, bool export_to_cl_image) { - GEMMLHSMatrixInfo lhs_info; - GEMMRHSMatrixInfo rhs_info; + v0 = ((m / (m0 * v0)) == 0) ? 1 : v0; + h0 = ((n / (n0 * h0)) == 0) ? 1 : h0; - // Configure GEMMLHSMatrixInfo - lhs_info.m0 = m0; - lhs_info.k0 = k0; - lhs_info.v0 = ((m / (lhs_info.m0 * v0)) == 0) ? 1 : v0; - lhs_info.interleave = lhs_interleave; - lhs_info.transpose = lhs_transpose; - - // Configure GEMMRHSMatrixInfo - rhs_info.n0 = n0; - rhs_info.k0 = lhs_info.k0; - rhs_info.h0 = ((n / (rhs_info.n0 * h0)) == 0) ? 1 : h0; - rhs_info.interleave = rhs_interleave; - rhs_info.transpose = rhs_transpose; + const GEMMLHSMatrixInfo lhs_info(m0, k0, v0, lhs_transpose, lhs_interleave); + const GEMMRHSMatrixInfo rhs_info(n0, k0, h0, rhs_transpose, rhs_interleave, export_to_cl_image); return std::make_pair(lhs_info, rhs_info); } @@ -66,5 +58,27 @@ void update_padding_for_cl_image(ITensorInfo *tensor) tensor->extend_padding(PaddingSize(0, padding, 0, 0)); } + +Status validate_image2d_support_on_rhs(const ITensorInfo &tensor_reshaped_info, const GEMMRHSMatrixInfo &rhs_info) +{ + if(rhs_info.export_to_cl_image) + { + ARM_COMPUTE_RETURN_ERROR_ON_MSG((rhs_info.n0 == 2) || (rhs_info.n0 == 3), "Export to cl_image only supported with n0 = 4, 8 or 16"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG((rhs_info.k0 == 2) || (rhs_info.k0 == 3), "Export to cl_image only supported with k0 = 4, 8 or 16"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(tensor_reshaped_info.data_type() != DataType::F32, "Export to cl_image only supported with F32 data type"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(!image2d_from_buffer_supported(CLKernelLibrary::get().get_device()), "The extension cl_khr_image2d_from_buffer is not supported on the target platform"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(get_cl_image_pitch_alignment(CLKernelLibrary::get().get_device()) == 0, "Impossible to retrieve the cl_image pitch alignment"); + + // Check the width and height of the output tensor. + // Since we cannot create a 3d image from a buffer, the third dimension is collapsed on the second dimension + const size_t max_image_w = CLKernelLibrary::get().get_device().getInfo(); + const size_t max_image_h = CLKernelLibrary::get().get_device().getInfo(); + + ARM_COMPUTE_RETURN_ERROR_ON_MSG(tensor_reshaped_info.tensor_shape()[0] > max_image_w * 4, "Not supported width for cl_image"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(tensor_reshaped_info.tensor_shape()[1] * tensor_reshaped_info.tensor_shape()[2] > max_image_h, "Not supported height for cl_image"); + } + + return Status{}; +} } // namespace cl_gemm -} // namespace arm_compute \ No newline at end of file +} // namespace arm_compute diff --git a/src/core/CL/gemm/reshaped/CLGEMMReshapedKernelConfigurationBifrost.cpp b/src/core/CL/gemm/reshaped/CLGEMMReshapedKernelConfigurationBifrost.cpp index f2954be7d2..a533f14d02 100644 --- a/src/core/CL/gemm/reshaped/CLGEMMReshapedKernelConfigurationBifrost.cpp +++ b/src/core/CL/gemm/reshaped/CLGEMMReshapedKernelConfigurationBifrost.cpp @@ -27,6 +27,9 @@ #include "arm_compute/core/CL/CLKernelLibrary.h" #include "arm_compute/core/CL/gemm/CLGEMMHelpers.h" #include "arm_compute/core/GPUTarget.h" +#include "arm_compute/core/TensorInfo.h" +#include "arm_compute/core/TensorShape.h" +#include "arm_compute/core/utils/misc/ShapeCalculator.h" #include #include @@ -35,6 +38,8 @@ namespace arm_compute { namespace cl_gemm { +using namespace arm_compute::misc::shape_calculator; + CLGEMMReshapedKernelConfigurationBifrost::CLGEMMReshapedKernelConfigurationBifrost(GPUTarget gpu) : ICLGEMMKernelConfiguration(gpu) { @@ -153,13 +158,48 @@ std::pair CLGEMMReshapedKernelConfiguratio ARM_COMPUTE_UNUSED(k); ARM_COMPUTE_UNUSED(b); + GEMMLHSMatrixInfo lhs_info_buf; + GEMMRHSMatrixInfo rhs_info_buf; + GEMMLHSMatrixInfo lhs_info_img; + GEMMRHSMatrixInfo rhs_info_img; + + // Get lhs_info/rhs_info in case of OpenCL buffer if(n <= 4) { - return configure_lhs_rhs_info(m, n, 4, 2, 8, 16, 16, true, false, false, true); + std::tie(lhs_info_buf, rhs_info_buf) = configure_lhs_rhs_info(m, n, 4, 2, 8, 16, 16, true, false, false, true); + } + else + { + std::tie(lhs_info_buf, rhs_info_buf) = configure_lhs_rhs_info(m, n, 4, 4, 2, 8, 16, false, false, false, true); + } + + // Get lhs_info/rhs_info in case of OpenCL image + // Condition on the GPU workload + if((m / 4) * (n / 4) >= 2560) + { + // Big workload + std::tie(lhs_info_img, rhs_info_img) = configure_lhs_rhs_info(m, n, 4, 4, 4, 2, 8, true, true, true, false, true); + } + else + { + // Small workload + std::tie(lhs_info_img, rhs_info_img) = configure_lhs_rhs_info(m, n, 2, 4, 4, 1, 1, true, true, true, false, true); + } + + const TensorInfo tensor_rhs_info(TensorShape(n, k, b), 1, DataType::F32); + const TensorShape shape = compute_rhs_reshaped_shape(tensor_rhs_info, rhs_info_img); + const TensorInfo tensor_reshaped_info(shape, 1, DataType::F32); + + // In case of vector by matrix with few work-items, we use the OpenCL buffer rather than the OpenCL image2d + const bool use_cl_image2d = (n <= 4) ? false : true; + + if(bool(validate_image2d_support_on_rhs(tensor_reshaped_info, rhs_info_img)) && use_cl_image2d) + { + return std::make_pair(lhs_info_img, rhs_info_img); } else { - return configure_lhs_rhs_info(m, n, 4, 4, 2, 8, 16, false, false, false, true); + return std::make_pair(lhs_info_buf, rhs_info_buf); } } diff --git a/src/core/CL/gemm/reshaped_only_rhs/CLGEMMReshapedOnlyRHSKernelConfigurationBifrost.cpp b/src/core/CL/gemm/reshaped_only_rhs/CLGEMMReshapedOnlyRHSKernelConfigurationBifrost.cpp index f662089c77..581c2d2199 100644 --- a/src/core/CL/gemm/reshaped_only_rhs/CLGEMMReshapedOnlyRHSKernelConfigurationBifrost.cpp +++ b/src/core/CL/gemm/reshaped_only_rhs/CLGEMMReshapedOnlyRHSKernelConfigurationBifrost.cpp @@ -27,6 +27,9 @@ #include "arm_compute/core/CL/CLKernelLibrary.h" #include "arm_compute/core/CL/gemm/CLGEMMHelpers.h" #include "arm_compute/core/GPUTarget.h" +#include "arm_compute/core/TensorInfo.h" +#include "arm_compute/core/TensorShape.h" +#include "arm_compute/core/utils/misc/ShapeCalculator.h" #include #include @@ -35,6 +38,8 @@ namespace arm_compute { namespace cl_gemm { +using namespace arm_compute::misc::shape_calculator; + CLGEMMReshapedOnlyRHSKernelConfigurationBifrost::CLGEMMReshapedOnlyRHSKernelConfigurationBifrost(GPUTarget gpu) : ICLGEMMKernelConfiguration(gpu) { @@ -139,14 +144,47 @@ std::pair CLGEMMReshapedOnlyRHSKernelConfi ARM_COMPUTE_UNUSED(k); ARM_COMPUTE_UNUSED(b); + GEMMLHSMatrixInfo lhs_info_buf; + GEMMRHSMatrixInfo rhs_info_buf; + GEMMLHSMatrixInfo lhs_info_img; + GEMMRHSMatrixInfo rhs_info_img; + + // Get lhs_info/rhs_info in case of OpenCL buffer if(m == 1) { const unsigned int h0 = std::max(n / 2, 1U); - return configure_lhs_rhs_info(m, n, 1, 2, 8, 1, h0, false, true, false, true); + std::tie(lhs_info_buf, rhs_info_buf) = configure_lhs_rhs_info(m, n, 1, 2, 8, 1, h0, false, true, false, true); } else { - return configure_lhs_rhs_info(m, n, 4, 4, 4, 1, 2, false, true, false, true); + std::tie(lhs_info_buf, rhs_info_buf) = configure_lhs_rhs_info(m, n, 4, 4, 4, 1, 2, false, true, false, true); + } + + // Get lhs_info/rhs_info in case of OpenCL image + if(m == 1) + { + std::tie(lhs_info_img, rhs_info_img) = configure_lhs_rhs_info(m, n, 1, 4, 4, 1, 4, false, true, false, false, true); + } + else + { + const int h0 = std::max(std::min(static_cast(n / 4), static_cast(16)), static_cast(1)); + std::tie(lhs_info_img, rhs_info_img) = configure_lhs_rhs_info(m, n, 4, 4, 4, 1, h0, false, true, false, false, true); + } + + const TensorInfo tensor_rhs_info(TensorShape(n, k, b), 1, DataType::F32); + const TensorShape shape = compute_rhs_reshaped_shape(tensor_rhs_info, rhs_info_img); + const TensorInfo tensor_reshaped_info(shape, 1, DataType::F32); + + // In case of vector by matrix with few work-items, we use the OpenCL buffer rather than the OpenCL image2d + const bool use_cl_image2d = (m == 1 && n <= 4096) ? false : true; + + if(bool(validate_image2d_support_on_rhs(tensor_reshaped_info, rhs_info_img)) && use_cl_image2d) + { + return std::make_pair(lhs_info_img, rhs_info_img); + } + else + { + return std::make_pair(lhs_info_buf, rhs_info_buf); } } diff --git a/src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedKernel.cpp b/src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedKernel.cpp index be73c85731..5a46a1e013 100644 --- a/src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedKernel.cpp +++ b/src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedKernel.cpp @@ -29,6 +29,7 @@ #include "arm_compute/core/CL/CLValidate.h" #include "arm_compute/core/CL/ICLTensor.h" #include "arm_compute/core/CL/OpenCL.h" +#include "arm_compute/core/CL/gemm/CLGEMMHelpers.h" #include "arm_compute/core/Error.h" #include "arm_compute/core/Helpers.h" #include "arm_compute/core/TensorInfo.h" @@ -79,23 +80,7 @@ Status validate_arguments(const ITensorInfo *input0, const ITensorInfo *input1, && (!gemm_info.broadcast_bias), "Bias addition only supported with broadcast mode in case the input or output has to be reinterpreted as 3D"); ARM_COMPUTE_RETURN_ERROR_ON_MSG(gemm_info.fp_mixed_precision && (input0->data_type() == DataType::F32), "Mixed precision only supported for F16 data type"); - - if(rhs_info.export_to_cl_image) - { - ARM_COMPUTE_RETURN_ERROR_ON_MSG((rhs_info.n0 == 2) || (rhs_info.n0 == 3), "Export to cl_image only supported with n0 = 4, 8 or 16"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG((rhs_info.k0 == 2) || (rhs_info.k0 == 3), "Export to cl_image only supported with k0 = 4, 8 or 16"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(input1->data_type() != DataType::F32, "Export to cl_image only supported with F32 data type"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(!image2d_from_buffer_supported(CLKernelLibrary::get().get_device()), "The extension cl_khr_image2d_from_buffer is not supported on the target platform"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(get_cl_image_pitch_alignment(CLKernelLibrary::get().get_device()) == 0, "Impossible to retrieve the cl_image pitch alignment"); - - // Check the width and height of the output tensor. - // Since we cannot create a 3d image from a buffer, the third dimension is collapsed with the second dimension - size_t max_image_w = CLKernelLibrary::get().get_device().getInfo(); - size_t max_image_h = CLKernelLibrary::get().get_device().getInfo(); - - ARM_COMPUTE_RETURN_ERROR_ON_MSG(input1->tensor_shape()[0] > max_image_w * 4, "Not supported width for cl_image"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(input1->tensor_shape()[1] * input1->tensor_shape()[2] > max_image_h, "Not supported height for cl_image"); - } + ARM_COMPUTE_RETURN_ON_ERROR(cl_gemm::validate_image2d_support_on_rhs(*input1, rhs_info)); const unsigned int m = gemm_info.m; const unsigned int n = gemm_info.n; diff --git a/src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.cpp b/src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.cpp index 8b4f930ea4..7d76ffd86c 100644 --- a/src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.cpp +++ b/src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.cpp @@ -26,6 +26,7 @@ #include "arm_compute/core/AccessWindowStatic.h" #include "arm_compute/core/CL/CLValidate.h" #include "arm_compute/core/CL/ICLTensor.h" +#include "arm_compute/core/CL/gemm/CLGEMMHelpers.h" #include "arm_compute/core/Error.h" #include "arm_compute/core/Helpers.h" #include "arm_compute/core/TensorInfo.h" @@ -65,23 +66,7 @@ Status validate_arguments(const ITensorInfo *input0, const ITensorInfo *input1, && (!gemm_info.broadcast_bias), "Bias addition only supported with broadcast mode in case the input or output has to be reinterpreted as 3D"); ARM_COMPUTE_RETURN_ERROR_ON_MSG(gemm_info.fp_mixed_precision, "Mixed precision not supported"); - - if(rhs_info.export_to_cl_image) - { - ARM_COMPUTE_RETURN_ERROR_ON_MSG((rhs_info.n0 == 2) || (rhs_info.n0 == 3), "Export to cl_image only supported with n0 = 4, 8 or 16"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG((rhs_info.k0 == 2) || (rhs_info.k0 == 3), "Export to cl_image only supported with k0 = 4, 8 or 16"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(input1->data_type() != DataType::F32, "Export to cl_image only supported with F32 data type"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(!image2d_from_buffer_supported(CLKernelLibrary::get().get_device()), "The extension cl_khr_image2d_from_buffer is not supported on the target platform"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(get_cl_image_pitch_alignment(CLKernelLibrary::get().get_device()) == 0, "Impossible to retrieve the cl_image pitch alignment"); - - // Check the width and height of the output tensor. - // Since we cannot create a 3d image from a buffer, the third dimension is collapsed with the second dimension - size_t max_image_w = CLKernelLibrary::get().get_device().getInfo(); - size_t max_image_h = CLKernelLibrary::get().get_device().getInfo(); - - ARM_COMPUTE_RETURN_ERROR_ON_MSG(input1->tensor_shape()[0] > max_image_w * 4, "Not supported width for cl_image"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(input1->tensor_shape()[1] * input1->tensor_shape()[2] > max_image_h, "Not supported height for cl_image"); - } + ARM_COMPUTE_RETURN_ON_ERROR(cl_gemm::validate_image2d_support_on_rhs(*input1, rhs_info)); const unsigned int m = gemm_info.m; const unsigned int n = gemm_info.n; diff --git a/src/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.cpp b/src/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.cpp index c57066ae03..c1993b72b9 100644 --- a/src/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.cpp +++ b/src/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.cpp @@ -58,21 +58,8 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, c if(rhs_info.export_to_cl_image) { - ARM_COMPUTE_RETURN_ERROR_ON_MSG((rhs_info.n0 == 2) || (rhs_info.n0 == 3), "Export to cl_image only supported with n0 = 4, 8 or 16"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG((rhs_info.k0 == 2) || (rhs_info.k0 == 3), "Export to cl_image only supported with k0 = 4, 8 or 16"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->data_type() != DataType::F32, "Export to cl_image only supported with F32 data type"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(!image2d_from_buffer_supported(CLKernelLibrary::get().get_device()), "The extension cl_khr_image2d_from_buffer is not supported on the target platform"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(get_cl_image_pitch_alignment(CLKernelLibrary::get().get_device()) == 0, "Impossible to retrieve the cl_image pitch alignment"); - - TensorShape output_shape = compute_rhs_reshaped_shape(*input, rhs_info); - - // Check the width and height of the output tensor. - // Since we cannot create a 3d image from a buffer, the third dimension is collapsed with the second dimension - size_t max_image_w = CLKernelLibrary::get().get_device().getInfo(); - size_t max_image_h = CLKernelLibrary::get().get_device().getInfo(); - - ARM_COMPUTE_RETURN_ERROR_ON_MSG(output_shape[0] > max_image_w * 4, "Not supported width for cl_image"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(output_shape[1] * output_shape[2] > max_image_h, "Not supported height for cl_image"); + const TensorInfo tensor_reshaped_info(compute_rhs_reshaped_shape(*input, rhs_info), 1, DataType::F32); + ARM_COMPUTE_RETURN_ON_ERROR(cl_gemm::validate_image2d_support_on_rhs(tensor_reshaped_info, rhs_info)); } ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input); -- cgit v1.2.1