diff options
| -rw-r--r-- | src/core/NEON/kernels/NEGEMMLowpOffsetContributionOutputStageKernel.cpp | 10 | ||||
| -rw-r--r-- | src/runtime/NEON/functions/NEFullyConnectedLayer.cpp | 8 |
2 files changed, 9 insertions, 9 deletions
diff --git a/src/core/NEON/kernels/NEGEMMLowpOffsetContributionOutputStageKernel.cpp b/src/core/NEON/kernels/NEGEMMLowpOffsetContributionOutputStageKernel.cpp index 86abb2d65c..5d2df6d2c9 100644 --- a/src/core/NEON/kernels/NEGEMMLowpOffsetContributionOutputStageKernel.cpp +++ b/src/core/NEON/kernels/NEGEMMLowpOffsetContributionOutputStageKernel.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2019 ARM Limited. + * Copyright (c) 2019-2020 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -909,11 +909,11 @@ get_configured_function(const ITensor *mm_result, const ITensor *vector_sum_row, && mm_result->info()->tensor_shape().y() != vector_sum_row->info()->tensor_shape().x(); // Check if we need to clamp the result using min and max - PixelValue type_min = 0; - PixelValue type_max = 0; + PixelValue type_min{}; + PixelValue type_max{}; std::tie(type_min, type_max) = get_min_max(output->info()->data_type()); - int type_min_int = type_min.get<int>(); - int type_max_int = type_max.get<int>(); + int32_t type_min_int = type_min.get<int32_t>(); + int32_t type_max_int = type_max.get<int32_t>(); const bool is_bounded_relu = !(output_stage.gemmlowp_min_bound == type_min_int && output_stage.gemmlowp_max_bound == type_max_int); // Check if we need to perform fixed point requantization diff --git a/src/runtime/NEON/functions/NEFullyConnectedLayer.cpp b/src/runtime/NEON/functions/NEFullyConnectedLayer.cpp index 01746eb3db..4c264e4832 100644 --- a/src/runtime/NEON/functions/NEFullyConnectedLayer.cpp +++ b/src/runtime/NEON/functions/NEFullyConnectedLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2019 ARM Limited. + * Copyright (c) 2017-2020 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -357,9 +357,9 @@ Status NEFullyConnectedLayer::validate(const ITensorInfo *input, const ITensorIn const UniformQuantizationInfo wq_info = weights->quantization_info().uniform(); const UniformQuantizationInfo oq_info = output->quantization_info().uniform(); - float multiplier = (iq_info.scale * wq_info.scale) / oq_info.scale; - int output_multiplier; - int output_shift; + float multiplier = (iq_info.scale * wq_info.scale) / oq_info.scale; + int32_t output_multiplier; + int32_t output_shift; ARM_COMPUTE_RETURN_ON_ERROR(quantization::calculate_quantized_multiplier(multiplier, &output_multiplier, &output_shift)); ARM_COMPUTE_RETURN_ON_ERROR(NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint::validate(&gemmlowp_output, biases, output)); } |