Make all CL Concatenate kernels and functions state-less
Resolves COMPMID-3995
Change-Id: I84172bed20924f1d9ae3b4d14d7b321e9494296e
Signed-off-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/4887
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
diff --git a/src/core/gpu/cl/kernels/ClWidthConcatenate4TensorsKernel.cpp b/src/core/gpu/cl/kernels/ClWidthConcatenate4TensorsKernel.cpp
new file mode 100644
index 0000000..4b49652
--- /dev/null
+++ b/src/core/gpu/cl/kernels/ClWidthConcatenate4TensorsKernel.cpp
@@ -0,0 +1,186 @@
+/*
+ * Copyright (c) 2018-2021 Arm Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#include "src/core/gpu/cl/kernels/ClWidthConcatenate4TensorsKernel.h"
+
+#include "arm_compute/core/CL/CLHelpers.h"
+#include "arm_compute/core/CL/CLKernelLibrary.h"
+#include "arm_compute/core/CL/ICLTensor.h"
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/Utils.h"
+#include "src/core/CL/CLValidate.h"
+#include "src/core/helpers/WindowHelpers.h"
+#include "src/core/utils/helpers/tensor_info.h"
+#include "support/Cast.h"
+
+#include "support/StringSupport.h"
+
+namespace arm_compute
+{
+namespace opencl
+{
+namespace kernels
+{
+namespace
+{
+Status validate_arguments(const ITensorInfo *src1, const ITensorInfo *src2, const ITensorInfo *src3, const ITensorInfo *src4, const ITensorInfo *dst)
+{
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src1, src2, src3, src4, dst);
+ ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(src1);
+ ARM_COMPUTE_RETURN_ERROR_ON(src1->data_type() == DataType::UNKNOWN);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src1, src2, src3, src4, dst);
+ ARM_COMPUTE_RETURN_ERROR_ON(src1->dimension(0) + src2->dimension(0) + src3->dimension(0) + src4->dimension(0) > dst->dimension(0));
+
+ for(size_t i = 1; i < Coordinates::num_max_dimensions; ++i)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON(src1->dimension(i) != dst->dimension(i));
+ ARM_COMPUTE_RETURN_ERROR_ON(src2->dimension(i) != dst->dimension(i));
+ ARM_COMPUTE_RETURN_ERROR_ON(src3->dimension(i) != dst->dimension(i));
+ ARM_COMPUTE_RETURN_ERROR_ON(src4->dimension(i) != dst->dimension(i));
+ }
+ ARM_COMPUTE_RETURN_ERROR_ON(src1->num_dimensions() > 4);
+
+ return Status{};
+}
+} // namespace
+
+ClWidthConcatenate4TensorsKernel::ClWidthConcatenate4TensorsKernel()
+{
+}
+
+Status ClWidthConcatenate4TensorsKernel::validate(const ITensorInfo *src1, const ITensorInfo *src2, const ITensorInfo *src3, const ITensorInfo *src4, const ITensorInfo *dst)
+{
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(src1, src2, src3, src4, dst));
+ return Status{};
+}
+
+void ClWidthConcatenate4TensorsKernel::configure(const CLCompileContext &compile_context,
+ ITensorInfo *src1, ITensorInfo *src2,
+ ITensorInfo *src3, ITensorInfo *src4,
+ ITensorInfo *dst)
+{
+ ARM_COMPUTE_ERROR_ON_NULLPTR(src1, src2, src3, src4, dst);
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src1, src2, src3, src4, dst));
+
+ auto padding_info = get_padding_info({ src1, src2, src3, src4, dst });
+ const unsigned int min_dimension = std::min(std::min(src1->dimension(0), src2->dimension(0)), std::min(src3->dimension(0), src4->dimension(0)));
+ const unsigned int num_elems_processed_per_iteration = adjust_vec_size(8, min_dimension);
+ const unsigned int vec_size_leftover = dst->dimension(0) % num_elems_processed_per_iteration;
+
+ // Add build options
+ CLBuildOptions build_opts;
+ build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(src1->data_type()));
+ build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration));
+ build_opts.add_option("-DVEC_SIZE_LEFTOVER=" + support::cpp11::to_string(vec_size_leftover));
+ build_opts.add_option("-DDEPTH=" + support::cpp11::to_string(src1->dimension(2)));
+ build_opts.add_option("-DINPUT1_WIDTH=" + support::cpp11::to_string(src1->dimension(0)));
+ build_opts.add_option("-DINPUT2_WIDTH=" + support::cpp11::to_string(src2->dimension(0)));
+ build_opts.add_option("-DINPUT3_WIDTH=" + support::cpp11::to_string(src3->dimension(0)));
+ build_opts.add_option("-DINPUT4_WIDTH=" + support::cpp11::to_string(src4->dimension(0)));
+ build_opts.add_option("-DELEMENT_SIZE=" + support::cpp11::to_string(src1->element_size()));
+ build_opts.add_option("-DINPUT1_ROTATE_N=" + support::cpp11::to_string((src1->dimension(0) - vec_size_leftover) % num_elems_processed_per_iteration));
+ build_opts.add_option("-DINPUT2_ROTATE_N=" + support::cpp11::to_string((src1->dimension(0) + src2->dimension(0) - vec_size_leftover) % num_elems_processed_per_iteration));
+ build_opts.add_option("-DINPUT3_ROTATE_N=" + support::cpp11::to_string((src1->dimension(0) + src2->dimension(0) + src3->dimension(0) - vec_size_leftover) % num_elems_processed_per_iteration));
+
+ // If soources have different quantization info set quantization parameters needed for the re-quantization process
+ const bool have_different_qinfo = helpers::tensor_info::tensors_have_different_quantization_info(dst, src1, src2, src3, src4);
+ if(is_data_type_quantized_asymmetric(src1->data_type()) && have_different_qinfo)
+ {
+ const UniformQuantizationInfo iq1_info = src1->quantization_info().uniform();
+ const UniformQuantizationInfo iq2_info = src2->quantization_info().uniform();
+ const UniformQuantizationInfo iq3_info = src3->quantization_info().uniform();
+ const UniformQuantizationInfo iq4_info = src4->quantization_info().uniform();
+ const UniformQuantizationInfo oq_info = dst->quantization_info().uniform();
+
+ build_opts.add_option("-DOFFSET_IN1=" + float_to_string_with_full_precision(iq1_info.offset));
+ build_opts.add_option("-DSCALE_IN1=" + float_to_string_with_full_precision(iq1_info.scale));
+ build_opts.add_option("-DOFFSET_IN2=" + float_to_string_with_full_precision(iq2_info.offset));
+ build_opts.add_option("-DSCALE_IN2=" + float_to_string_with_full_precision(iq2_info.scale));
+ build_opts.add_option("-DOFFSET_IN3=" + float_to_string_with_full_precision(iq3_info.offset));
+ build_opts.add_option("-DSCALE_IN3=" + float_to_string_with_full_precision(iq3_info.scale));
+ build_opts.add_option("-DOFFSET_IN4=" + float_to_string_with_full_precision(iq4_info.offset));
+ build_opts.add_option("-DSCALE_IN4=" + float_to_string_with_full_precision(iq4_info.scale));
+ build_opts.add_option("-DOFFSET_OUT=" + float_to_string_with_full_precision(oq_info.offset));
+ build_opts.add_option("-DSCALE_OUT=" + float_to_string_with_full_precision(oq_info.scale));
+ }
+
+ // Create kernel
+ _kernel = create_kernel(compile_context, "concatenate_width_x4", build_opts.options());
+
+ // Configure kernel window
+ Window win = calculate_max_window(*dst, Steps(num_elems_processed_per_iteration));
+ ICLKernel::configure_internal(win.collapse(win, Window::DimZ));
+
+ // Set dst valid region
+ dst->set_valid_region(ValidRegion(Coordinates(), dst->tensor_shape()));
+ ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
+
+ // Set config_id for enabling LWS tuning
+ _config_id = "concatenate_width_x4_";
+ _config_id += lower_string(string_from_data_type(src1->data_type()));
+ _config_id += "_";
+ _config_id += support::cpp11::to_string(src1->dimension(0));
+ _config_id += "_";
+ _config_id += support::cpp11::to_string(src1->dimension(1));
+ _config_id += "_";
+ _config_id += support::cpp11::to_string(src2->dimension(0));
+ _config_id += "_";
+ _config_id += support::cpp11::to_string(src2->dimension(1));
+ _config_id += "_";
+ _config_id += support::cpp11::to_string(src3->dimension(0));
+ _config_id += "_";
+ _config_id += support::cpp11::to_string(src3->dimension(1));
+ _config_id += "_";
+ _config_id += support::cpp11::to_string(src4->dimension(0));
+ _config_id += "_";
+ _config_id += support::cpp11::to_string(src4->dimension(1));
+}
+
+void ClWidthConcatenate4TensorsKernel::run_op(ITensorPack &tensors, const Window &window, ::cl::CommandQueue &queue)
+{
+ ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+ ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
+
+ const auto src0 = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_VEC));
+ const auto src1 = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_VEC + 1));
+ const auto src2 = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_VEC + 2));
+ const auto src3 = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_VEC + 3));
+ auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST));
+
+ Window slice = window.first_slice_window_4D();
+
+ do
+ {
+ unsigned int idx = 0;
+ add_4D_tensor_argument(idx, src0, slice);
+ add_4D_tensor_argument(idx, src1, slice);
+ add_4D_tensor_argument(idx, src2, slice);
+ add_4D_tensor_argument(idx, src3, slice);
+ add_4D_tensor_argument(idx, dst, slice);
+ enqueue(queue, *this, window, lws_hint());
+ }
+ while(window.slide_window_slice_4D(slice));
+}
+} // namespace kernels
+} // namespace opencl
+} // namespace arm_compute