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author | Michele Di Giorgio <michele.digiorgio@arm.com> | 2021-04-28 16:03:32 +0100 |
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committer | Michele Di Giorgio <michele.digiorgio@arm.com> | 2021-04-29 16:19:20 +0000 |
commit | 223aba9ff116ecc7db7963ddb6a7213eee04b18c (patch) | |
tree | 0528c22e74b25f9fd1fd41e8f29651b0fce09102 /src | |
parent | 9f6111a9e0746d5995fd9dc46420af5b316be734 (diff) | |
download | ComputeLibrary-223aba9ff116ecc7db7963ddb6a7213eee04b18c.tar.gz |
Remove stale/solved TODOs
Change-Id: I5c440f4c6ca4186adcfa926e6b7d924086671f29
Signed-off-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5520
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Manuel Bottini <manuel.bottini@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'src')
-rw-r--r-- | src/core/CL/cl_kernels/softmax_layer.cl | 4 | ||||
-rw-r--r-- | src/core/CL/cl_kernels/softmax_layer_quantized.cl | 4 | ||||
-rw-r--r-- | src/core/NEON/NEMath.inl | 3 | ||||
-rw-r--r-- | src/graph/GraphManager.cpp | 2 | ||||
-rw-r--r-- | src/graph/backends/CL/CLFunctionsFactory.cpp | 1 | ||||
-rw-r--r-- | src/runtime/NEON/functions/NEGEMMConvolutionLayer.cpp | 2 |
6 files changed, 2 insertions, 14 deletions
diff --git a/src/core/CL/cl_kernels/softmax_layer.cl b/src/core/CL/cl_kernels/softmax_layer.cl index 01f5de47cf..4d2d89dd73 100644 --- a/src/core/CL/cl_kernels/softmax_layer.cl +++ b/src/core/CL/cl_kernels/softmax_layer.cl @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2020 Arm Limited. + * Copyright (c) 2017-2021 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -306,7 +306,6 @@ __kernel void softmax_layer_max_shift_exp_sum_parallel( } #ifdef NON_MULTIPLE_OF_GRID_SIZE // How many work-items needed to complete the computation. - //TODO: Optimize this calculation (avoid %). int boundary_workitems = (SRC_WIDTH % (GRID_SIZE * VECTOR_SIZE)) / VECTOR_SIZE; if(lid < boundary_workitems) { @@ -417,7 +416,6 @@ __kernel void softmax_layer_max_shift_exp_sum_parallel( sum1D += data; } #ifdef NON_MULTIPLE_OF_GRID_SIZE - //TODO: Optimize the calculation (avoid %). boundary_workitems = (SRC_WIDTH % (GRID_SIZE * VECTOR_SIZE)) / VECTOR_SIZE; if(lid < boundary_workitems) { diff --git a/src/core/CL/cl_kernels/softmax_layer_quantized.cl b/src/core/CL/cl_kernels/softmax_layer_quantized.cl index b7a6e00dfa..4d5006d804 100644 --- a/src/core/CL/cl_kernels/softmax_layer_quantized.cl +++ b/src/core/CL/cl_kernels/softmax_layer_quantized.cl @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2020 Arm Limited. + * Copyright (c) 2017-2021 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -324,7 +324,6 @@ __kernel void softmax_layer_max_shift_exp_sum_quantized_parallel( } #ifdef NON_MULTIPLE_OF_GRID_SIZE // How many work-items needed to complete the computation. - //TODO: Optimize this calculation (avoid %). int boundary_workitems = (SRC_WIDTH % (GRID_SIZE * VECTOR_SIZE)) / VECTOR_SIZE; if(lid < boundary_workitems) { @@ -429,7 +428,6 @@ __kernel void softmax_layer_max_shift_exp_sum_quantized_parallel( sum1D = sum1D + select(0, data_fp, data_diff >= (VEC_INT)(DIFF_MIN)); } #ifdef NON_MULTIPLE_OF_GRID_SIZE - //TODO: Optimize the calculation (avoid %). boundary_workitems = (SRC_WIDTH % (GRID_SIZE * VECTOR_SIZE)) / VECTOR_SIZE; if(lid < boundary_workitems) { diff --git a/src/core/NEON/NEMath.inl b/src/core/NEON/NEMath.inl index da9d038139..29df5433bb 100644 --- a/src/core/NEON/NEMath.inl +++ b/src/core/NEON/NEMath.inl @@ -495,7 +495,6 @@ inline float16x8_t vtaylor_polyq_f16(float16x8_t x, const std::array<float16x8_t inline float16x8_t vexpq_f16(float16x8_t x) { - // TODO (COMPMID-1535) : Revisit FP16 approximations const float32x4_t x_high = vcvt_f32_f16(vget_high_f16(x)); const float32x4_t x_low = vcvt_f32_f16(vget_low_f16(x)); @@ -505,7 +504,6 @@ inline float16x8_t vexpq_f16(float16x8_t x) inline float16x8_t vlogq_f16(float16x8_t x) { - // TODO (COMPMID-1535) : Revisit FP16 approximations const float32x4_t x_high = vcvt_f32_f16(vget_high_f16(x)); const float32x4_t x_low = vcvt_f32_f16(vget_low_f16(x)); @@ -515,7 +513,6 @@ inline float16x8_t vlogq_f16(float16x8_t x) inline float16x8_t vpowq_f16(float16x8_t val, float16x8_t n) { - // TODO (giaiod01) - COMPMID-1535 float32x4_t n0_f32 = vcvt_f32_f16(vget_low_f16(n)); float32x4_t n1_f32 = vcvt_f32_f16(vget_high_f16(n)); float32x4_t val0_f32 = vcvt_f32_f16(vget_low_f16(val)); diff --git a/src/graph/GraphManager.cpp b/src/graph/GraphManager.cpp index ab7aac6230..e357f10401 100644 --- a/src/graph/GraphManager.cpp +++ b/src/graph/GraphManager.cpp @@ -55,7 +55,6 @@ void GraphManager::finalize_graph(Graph &graph, GraphContext &ctx, PassManager & pm.run_type(graph, IGraphMutator::MutationType::IR); // Force target to all graph construct - // TODO (COMPMID-2014) : Support heterogeneous execution Target forced_target = target; // In case CLVK is selected, use the CL backend and @@ -77,7 +76,6 @@ void GraphManager::finalize_graph(Graph &graph, GraphContext &ctx, PassManager & force_target_to_graph(graph, forced_target); // Setup backend context - // TODO (COMPMID-2014) : Setup all backends needed by the graph setup_requested_backend_context(ctx, forced_target); // Configure all tensors diff --git a/src/graph/backends/CL/CLFunctionsFactory.cpp b/src/graph/backends/CL/CLFunctionsFactory.cpp index a3e7261721..1cd3f9f9c7 100644 --- a/src/graph/backends/CL/CLFunctionsFactory.cpp +++ b/src/graph/backends/CL/CLFunctionsFactory.cpp @@ -83,7 +83,6 @@ struct CLFusedLayerTypes using FuseBatchNormalization = CLFuseBatchNormalization; }; -// TODO (isagot01): Remove once we support heterogeneous scheduling at function level /** Wrapper for the CPP Function in the OpenCL backend **/ class CPPWrapperFunction : public IFunction { diff --git a/src/runtime/NEON/functions/NEGEMMConvolutionLayer.cpp b/src/runtime/NEON/functions/NEGEMMConvolutionLayer.cpp index 900330e4a6..2876c254fa 100644 --- a/src/runtime/NEON/functions/NEGEMMConvolutionLayer.cpp +++ b/src/runtime/NEON/functions/NEGEMMConvolutionLayer.cpp @@ -524,7 +524,6 @@ Status NEGEMMConvolutionLayer::validate(const ITensorInfo *input, const ITensorI { // Create tensor info for im2col reshaped inputs // For CPU, the batch size is on the fourth dimension - // TODO (giaiod01): Auto-initialize the output shape of im2col COMPMID-1482 TensorShape shape_im2col = input->tensor_shape(); shape_im2col.set(0, mat_weights_rows); shape_im2col.set(1, conv_w * conv_h); @@ -532,7 +531,6 @@ Status NEGEMMConvolutionLayer::validate(const ITensorInfo *input, const ITensorI im2col_reshaped_info = TensorInfo(shape_im2col, 1, data_type); im2col_reshaped_info.set_quantization_info(input->quantization_info()); - ARM_COMPUTE_RETURN_ON_ERROR(NEIm2ColKernel::validate(input, &im2col_reshaped_info, Size2D(kernel_width, kernel_height), conv_info, append_bias, dilation)); gemm_input_to_use = &im2col_reshaped_info; } |