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authorMichele Di Giorgio <michele.digiorgio@arm.com>2020-07-06 11:27:21 +0100
committerMichele Di Giorgio <michele.digiorgio@arm.com>2020-07-20 12:39:29 +0000
commitf6f7876e9ee8b58a8a6b335b032d554412fa3983 (patch)
tree669c86bfc60ec99965151022a4112c53116b06c0 /src/runtime/CL/functions/CLLSTMLayerQuantized.cpp
parent954051f449788f22eb605b126f71af923950ca29 (diff)
downloadComputeLibrary-f6f7876e9ee8b58a8a6b335b032d554412fa3983.tar.gz
COMPMID-3532: Align data type support between doxygen and implementation - CL
Also removes some unused code. Change-Id: I85687c40999c3cdf9e6fccfcd020b0901a9515fe Signed-off-by: Michele Di Giorgio <michele.digiorgio@arm.com> Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/3581 Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'src/runtime/CL/functions/CLLSTMLayerQuantized.cpp')
-rw-r--r--src/runtime/CL/functions/CLLSTMLayerQuantized.cpp3
1 files changed, 1 insertions, 2 deletions
diff --git a/src/runtime/CL/functions/CLLSTMLayerQuantized.cpp b/src/runtime/CL/functions/CLLSTMLayerQuantized.cpp
index a36e7dba22..e30b1dbb86 100644
--- a/src/runtime/CL/functions/CLLSTMLayerQuantized.cpp
+++ b/src/runtime/CL/functions/CLLSTMLayerQuantized.cpp
@@ -28,9 +28,7 @@
#include "arm_compute/core/Validate.h"
#include "arm_compute/core/utils/quantization/AsymmHelpers.h"
-#include <cmath>
#include <memory>
-#include <tuple>
namespace arm_compute
{
@@ -275,6 +273,7 @@ Status CLLSTMLayerQuantized::validate(const ITensorInfo *input,
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, input_to_input_weights, input_to_forget_weights, input_to_cell_weights, input_to_output_weights, recurrent_to_input_weights,
recurrent_to_forget_weights, recurrent_to_cell_weights, recurrent_to_output_weights, input_gate_bias, forget_gate_bias, cell_bias, output_gate_bias, cell_state_in,
output_state_in, cell_state_out, output_state_out);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(input, DataType::QASYMM8);
const int input_size = input->dimension(0);
const int batch_size = input->dimension(1);