Make ClDirectConvolutionKernel stateless

ClDirectorConvolution triggers ClActivation (if enabled)

Remove static tuner as the interface need to be changed base on new api. Remove functions in ClScaleKernel specific for static Tuner.

Solves: COMPMID-4010

Signed-off-by: Sheri Zhang <sheri.zhang@arm.com>
Change-Id: I7861c3462fda323a6fe1891834068a462245cb1b
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5262
Reviewed-by: Sang-Hoon Park <sang-hoon.park@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 0 insertions, 305 deletions

diff --git a/src/runtime/CL/tuners/BifrostTuner.cpp b/src/runtime/CL/tuners/BifrostTuner.cpp
deleted file mode 100644
index fe95829cca..0000000000
--- a/src/runtime/CL/tuners/BifrostTuner.cpp
+++ /dev/null
@@ -1,305 +0,0 @@
-/*
- * 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 "arm_compute/runtime/CL/tuners/BifrostTuner.h"
-
-#include "arm_compute/core/CL/CLHelpers.h"
-#include "src/core/CL/CLKernels.h"
-#include "support/Cast.h"
-
-#include "src/core/gpu/cl/kernels/ClPoolingKernel.h"
-#include "src/core/gpu/cl/kernels/ClScaleKernel.h"
-
-namespace arm_compute
-{
-namespace tuners
-{
-namespace
-{
-/** Tunes a @ref CLDirectConvolutionLayerKernel for a bifrost target
- *
- * @param[in] k Kernels to tune
- */
-void tune_direct_convolution_kernel(CLDirectConvolutionLayerKernel &k)
-{
-    cl::NDRange lws_hint = k.lws_hint();
-
-    const GPUTarget    gpu_target    = k.get_target();
-    const DataType     dt            = k._input->info()->data_type();
-    const TensorShape  weights_shape = k._weights->info()->tensor_shape();
-    const TensorShape  inputs_shape  = k._input->info()->tensor_shape();
-    const size_t       kernel_size   = weights_shape.x();
-    const unsigned int stride_x      = k._conv_stride_x;
-    const unsigned int stride_y      = k._conv_stride_y;
-
-    if(gpu_target_is_in(gpu_target, GPUTarget::G71, GPUTarget::G72) && (kernel_size <= 5) && (stride_x == 1) && (stride_y == 1) && (dt == DataType::F32))
-    {
-        // Through extensive experimentation with over 30 representative tensor
-        // shapes, we found a small number of local work size configurations
-        // that result in nearly optimal execution times. Selecting the right
-        // lws for a given shape, however, required a complex decision tree,
-        // until we constructed a simple feature as described below.
-        //
-        // We started from the number of multiply-accumulate operations for a
-        // convolution layer, which is equal to the product of the input
-        // dimensions 0..2 and the weights dimensions 0..2.  Unfortunately,
-        // this resulted in ties between distinct shapes that required distinct
-        // lws configurations. Replacing the width of the input with the kernel
-        // size, however, resulted in nearly optimal predictions. We use underscores
-        // in variable names to indicate when they are intentionally misleading.
-        const size_t product_of_weights_dimensions = weights_shape[0] * weights_shape[1] * weights_shape[2];
-        const size_t product_of_input_dimensions_  = inputs_shape[0] * inputs_shape[1] * inputs_shape[2];
-        const float  mega_ops_                     = 1e-6 * product_of_weights_dimensions * product_of_input_dimensions_;
-
-        switch(kernel_size)
-        {
-            case 1:
-            {
-                if(mega_ops_ < 1.f)
-                {
-                    lws_hint = cl::NDRange(1, 1, 8);
-                }
-                else if(mega_ops_ < 7.f)
-                {
-                    lws_hint = cl::NDRange(1, 1, 4);
-                }
-                else
-                {
-                    lws_hint = cl::NDRange(1, 1, 2);
-                }
-                break;
-            }
-            case 3:
-            {
-                if(mega_ops_ < 1.f)
-                {
-                    lws_hint = cl::NDRange(1, 1, 8);
-                }
-                else if(mega_ops_ < 13.f)
-                {
-                    lws_hint = cl::NDRange(2, 1, 4);
-                }
-                else if(mega_ops_ < 50.f)
-                {
-                    lws_hint = cl::NDRange(3, 1, 4);
-                }
-                else
-                {
-                    lws_hint = cl::NDRange(2, 1, 6);
-                }
-                break;
-            }
-            case 5:
-            {
-                if(mega_ops_ < 2.f || mega_ops_ > 80.f)
-                {
-                    lws_hint = cl::NDRange(2, 1, 4);
-                }
-                else
-                {
-                    lws_hint = cl::NDRange(2, 1, 8);
-                }
-                break;
-            }
-            default:
-                break;
-        }
-        k.set_lws_hint(lws_hint);
-    }
-}
-
-void tune_col2im_kernel(CLCol2ImKernel &k)
-{
-    cl::NDRange     lws_hint   = k.lws_hint();
-    const GPUTarget gpu_target = k.get_target();
-
-    // Configure the local work size for Bifrost with a value obtained
-    // via exhaustive autotuning over 30 representative tensor shapes.
-    if(gpu_target_is_in(gpu_target,
-                        GPUTarget::G71, GPUTarget::G72, GPUTarget::G76,
-                        GPUTarget::G51, GPUTarget::G51BIG, GPUTarget::G51LIT,
-                        GPUTarget::G52, GPUTarget::G52LIT))
-    {
-        if((k._convolved_dims.width == 7) || (k._convolved_dims.width == 14))
-        {
-            lws_hint = cl::NDRange(1, 7, 1);
-        }
-        else
-        {
-            lws_hint = cl::NDRange(1, 8, 1);
-        }
-    }
-
-    k.set_lws_hint(lws_hint);
-}
-
-void tune_im2col_kernel(CLIm2ColKernel &k)
-{
-    cl::NDRange     lws_hint   = k.lws_hint();
-    const GPUTarget gpu_target = k.get_target();
-
-    // Local work size optimized for the 11x11 AlexNet convolution on Bifrost.
-    if(gpu_target_is_in(gpu_target,
-                        GPUTarget::G71, GPUTarget::G72, GPUTarget::G76,
-                        GPUTarget::G51, GPUTarget::G51BIG, GPUTarget::G51LIT,
-                        GPUTarget::G52, GPUTarget::G52LIT)
-       && k._kernel_dims.width == 11)
-    {
-        const bool is_square_kernel = (k._kernel_dims.width == k._kernel_dims.height);
-        if(!is_square_kernel && k._kernel_dims.width > 1 && !k._conv_info.has_padding())
-        {
-            lws_hint = cl::NDRange(1, 1, 1);
-        }
-    }
-    k.set_lws_hint(lws_hint);
-}
-
-void tune_gemm_kernel(CLGEMMMatrixMultiplyKernel &k)
-{
-    cl::NDRange     lws_hint   = k.lws_hint();
-    const GPUTarget gpu_target = k.get_target();
-
-    // Configure LWS hint
-    switch(gpu_target)
-    {
-        case GPUTarget::G71:
-        case GPUTarget::G72:
-        case GPUTarget::G51:
-        case GPUTarget::G51BIG:
-        case GPUTarget::G51LIT:
-        case GPUTarget::G52:
-        case GPUTarget::G52LIT:
-        case GPUTarget::G76:
-            if(k._input1->info()->dimension(1) == 24)
-            {
-                // LWS optimized for the 11x11 AlexNet convolution on Bifrost.
-                lws_hint = cl::NDRange(2, 2);
-            }
-            else if(k._output->info()->dimension(1) == 196)
-            {
-                lws_hint = cl::NDRange(1, 7);
-            }
-            else
-            {
-                lws_hint = cl::NDRange(8, 8);
-            }
-            break;
-        default:
-            lws_hint = cl::NullRange;
-    }
-
-    k.set_lws_hint(lws_hint);
-}
-
-void tune_pooling_kernel(opencl::kernels::ClPoolingKernel &k)
-{
-    cl::NDRange     lws_hint   = k.lws_hint();
-    const GPUTarget gpu_target = k.get_target();
-
-    // Configure the local work size (hint) from the first two dimensions of the global work size.
-    // On Bifrost, this works for up to 35x35xC filters, for which the pooling_layer_3_optimized
-    // kernel is launched with gws=(9, 33, C). In any case, the hint will be ignored if it is
-    // invalid (e.g. exceeds the maximum workgroup size that the kernel can be launched with).
-    if(k._pool_info.data_layout == DataLayout::NCHW)
-    {
-        if(gpu_target_is_in(gpu_target,
-                            GPUTarget::G71, GPUTarget::G72, GPUTarget::G76,
-                            GPUTarget::G51, GPUTarget::G51BIG, GPUTarget::G51LIT,
-                            GPUTarget::G52, GPUTarget::G52LIT))
-        {
-            cl::NDRange gws = ICLKernel::gws_from_window(k.window());
-            lws_hint        = cl::NDRange(gws[0], gws[1], 1);
-        }
-    }
-
-    k.set_lws_hint(lws_hint);
-}
-
-void tune_scale_kernel(opencl::kernels::ClScaleKernel &k)
-{
-    cl::NDRange               lws_hint      = k.lws_hint();
-    const GPUTarget           gpu_target    = k.get_target();
-    const DataType            dt            = k.get_data_type();
-    const InterpolationPolicy interpolation = k.get_interpolation_policy();
-
-    // Configure the local work size for Bifrost, interpolation (bilinear) and datatype F32.
-    // The value are obtained via exhaustive autotuning.
-    if(gpu_target_is_in(gpu_target, GPUTarget::G71, GPUTarget::G72) && (dt == DataType::F32) && (interpolation == InterpolationPolicy::BILINEAR))
-    {
-        const auto dim_0 = k.get_output_x_dim();
-        if(dim_0 == 480)
-        {
-            lws_hint = cl::NDRange(2, 1);
-        }
-        else if(dim_0 == 3120)
-        {
-            lws_hint = cl::NDRange(2, 8);
-        }
-        else if(dim_0 == 4160)
-        {
-            lws_hint = cl::NDRange(4, 8);
-        }
-        k.set_lws_hint(lws_hint);
-    }
-}
-} // namespace
-
-void BifrostTuner::tune_kernel_static(ICLKernel &kernel)
-{
-    if(dynamic_cast<CLDirectConvolutionLayerKernel *>(&kernel) != nullptr)
-    {
-        tune_direct_convolution_kernel(*utils::cast::polymorphic_downcast<CLDirectConvolutionLayerKernel *>(&kernel));
-    }
-    else if(dynamic_cast<CLCol2ImKernel *>(&kernel) != nullptr)
-    {
-        tune_col2im_kernel(*utils::cast::polymorphic_downcast<CLCol2ImKernel *>(&kernel));
-    }
-    else if(dynamic_cast<CLIm2ColKernel *>(&kernel) != nullptr)
-    {
-        tune_im2col_kernel(*utils::cast::polymorphic_downcast<CLIm2ColKernel *>(&kernel));
-    }
-    else if(dynamic_cast<CLGEMMMatrixMultiplyKernel *>(&kernel) != nullptr)
-    {
-        tune_gemm_kernel(*utils::cast::polymorphic_downcast<CLGEMMMatrixMultiplyKernel *>(&kernel));
-    }
-    else if(dynamic_cast<opencl::kernels::ClPoolingKernel *>(&kernel) != nullptr)
-    {
-        tune_pooling_kernel(*utils::cast::polymorphic_downcast<opencl::kernels::ClPoolingKernel *>(&kernel));
-    }
-    else if(dynamic_cast<opencl::kernels::ClScaleKernel *>(&kernel) != nullptr)
-    {
-        tune_scale_kernel(*utils::cast::polymorphic_downcast<opencl::kernels::ClScaleKernel *>(&kernel));
-    }
-}
-
-void BifrostTuner::tune_kernel_dynamic(ICLKernel &kernel)
-{
-    ARM_COMPUTE_UNUSED(kernel);
-}
-
-void BifrostTuner::tune_kernel_dynamic(ICLKernel &kernel, ITensorPack &tensors)
-{
-    ARM_COMPUTE_UNUSED(kernel, tensors);
-}
-} // namespace tuners
-} // namespace arm_compute
\ No newline at end of file