2 files changed, 4 insertions, 4 deletions
diff --git a/src/runtime/GLES_COMPUTE/functions/GCConvolutionLayer.cpp b/src/runtime/GLES_COMPUTE/functions/GCConvolutionLayer.cpp
index 67b2ae9d61..5cfd72f724 100644
--- a/src/runtime/GLES_COMPUTE/functions/GCConvolutionLayer.cpp
+++ b/src/runtime/GLES_COMPUTE/functions/GCConvolutionLayer.cpp
@@ -149,7 +149,7 @@ void GCConvolutionLayer::configure(const IGCTensor *input, const IGCTensor *weig
     shape_im2col.set(2, 1);
 
     // FIXME: input->clone() doesn't work with subtensors for grouped convolutions.
-    TensorInfo im2col_reshaped_info(shape_im2col, 1, dt, input->info()->fixed_point_position());
+    TensorInfo im2col_reshaped_info(shape_im2col, 1, dt);
     _input_im2col_reshaped.allocator()->init(im2col_reshaped_info);
     _memory_group.manage(&_input_im2col_reshaped);
 
@@ -160,7 +160,7 @@ void GCConvolutionLayer::configure(const IGCTensor *input, const IGCTensor *weig
     const DataType gemm_data_type = dt;
 
     // FIXME: input->clone() doesn't work with subtensors for grouped convolutions.
-    TensorInfo info_gemm(shape_gemm, 1, gemm_data_type, input->info()->fixed_point_position());
+    TensorInfo info_gemm(shape_gemm, 1, gemm_data_type);
     _gemm_output.allocator()->init(info_gemm);
     _memory_group.manage(&_gemm_output);
 
diff --git a/src/runtime/GLES_COMPUTE/functions/GCSoftmaxLayer.cpp b/src/runtime/GLES_COMPUTE/functions/GCSoftmaxLayer.cpp
index 1748a5952b..0c8769b38f 100644
--- a/src/runtime/GLES_COMPUTE/functions/GCSoftmaxLayer.cpp
+++ b/src/runtime/GLES_COMPUTE/functions/GCSoftmaxLayer.cpp
@@ -42,11 +42,11 @@ void GCSoftmaxLayer::configure(const IGCTensor *input, IGCTensor *output, float
     ARM_COMPUTE_ERROR_ON(beta != 1.0f);
 
     // Create intermediate tensors shapes
-    _tmp.allocator()->init(TensorInfo(input->info()->tensor_shape(), input->info()->num_channels(), input->info()->data_type(), input->info()->fixed_point_position()));
+    _tmp.allocator()->init(TensorInfo(input->info()->tensor_shape(), input->info()->num_channels(), input->info()->data_type()));
 
     TensorShape shape = input->info()->tensor_shape();
     shape.set(0, 1);
-    TensorInfo tensor_info_max_sum(shape, input->info()->num_channels(), input->info()->data_type(), input->info()->fixed_point_position());
+    TensorInfo tensor_info_max_sum(shape, input->info()->num_channels(), input->info()->data_type());
     _max.allocator()->init(tensor_info_max_sum);
     _sum.allocator()->init(tensor_info_max_sum);