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| author | ramelg01 <ramy.elgammal@arm.com> | 2021-09-29 10:05:09 +0100 |
|---|---|---|
| committer | ramy.elgammal <ramy.elgammal@arm.com> | 2021-10-01 18:41:10 +0000 |
| commit | 6d891575e0c4432e170db7746037934299a0f2ca (patch) | |
| tree | e5db0d214169c6c5602f43734ee592e00370fef9 /src/runtime/CL/functions/CLRNNLayer.cpp | |
| parent | 93f7c3fe1a9c8c98265c50376cacd5fd9ebb7a72 (diff) | |
| download | ComputeLibrary-6d891575e0c4432e170db7746037934299a0f2ca.tar.gz | |
Provide logging for configure functions in all CL functions
Partially Resolves: COMPMID-4718
Signed-off-by: Ramy Elgammal <ramy.elgammal@arm.com>
Change-Id: I59943081de0f3105bdbfc78af53971a0de8cd53e
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/6332
Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'src/runtime/CL/functions/CLRNNLayer.cpp')
| -rw-r--r-- | src/runtime/CL/functions/CLRNNLayer.cpp | 3 |
1 files changed, 3 insertions, 0 deletions
diff --git a/src/runtime/CL/functions/CLRNNLayer.cpp b/src/runtime/CL/functions/CLRNNLayer.cpp index 20deef4edf..6f122866b2 100644 --- a/src/runtime/CL/functions/CLRNNLayer.cpp +++ b/src/runtime/CL/functions/CLRNNLayer.cpp @@ -30,6 +30,8 @@ #include "arm_compute/runtime/CL/CLScheduler.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" +#include "src/common/utils/Log.h" + namespace arm_compute { using namespace arm_compute::misc::shape_calculator; @@ -83,6 +85,7 @@ void CLRNNLayer::configure(const CLCompileContext &compile_context, const ICLTen { ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, recurrent_weights, bias, hidden_state, output); ARM_COMPUTE_ERROR_THROW_ON(CLRNNLayer::validate(input->info(), weights->info(), recurrent_weights->info(), bias->info(), hidden_state->info(), output->info(), info)); + ARM_COMPUTE_LOG_PARAMS(input, weights, recurrent_weights, bias, hidden_state, output, info); const int idx_height = get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::HEIGHT); TensorShape shape = compute_rnn_shape(recurrent_weights->info(), hidden_state->info()->dimension(idx_height)); |