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author | Georgios Pinitas <georgios.pinitas@arm.com> | 2019-05-21 13:32:43 +0100 |
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committer | Georgios Pinitas <georgios.pinitas@arm.com> | 2019-06-03 14:51:29 +0000 |
commit | 4c5469b192665c94118a8a558787cb9cec2d0765 (patch) | |
tree | 168aa969de8243bdbb1f25247dd9f54d037ae32c /src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp | |
parent | 43a129e94df41f9ac8bc78b702da5a387ada0494 (diff) | |
download | ComputeLibrary-4c5469b192665c94118a8a558787cb9cec2d0765.tar.gz |
COMPMID-2225: Add interface support for new quantized data types.
Add support for:
-QSYMM8, 8-bit quantized symmetric
-QSYMM8_PER_CHANNEL, 8-bit quantized symmetric with per channel quantization
Change-Id: I00c4ff98e44af37419470af61419ee95d0de2463
Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1236
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp')
-rw-r--r-- | src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp | 22 |
1 files changed, 13 insertions, 9 deletions
diff --git a/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp b/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp index 3bb69b1ffc..4bc8439d93 100644 --- a/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp +++ b/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp @@ -72,7 +72,7 @@ void NEDepthwiseConvolutionLayer3x3::configure_generic(ITensor _memory_group.manage(&_accumulator); _accumulator.allocator()->init(TensorInfo(accum_shape, 1, DataType::S32, output->info()->quantization_info())); _accumulator.info()->set_data_layout(accum_layout); - zero_value = PixelValue(static_cast<uint32_t>(input->info()->quantization_info().offset)); + zero_value = PixelValue(static_cast<uint32_t>(input->info()->quantization_info().uniform().offset)); } if(!_is_nchw) @@ -109,13 +109,15 @@ void NEDepthwiseConvolutionLayer3x3::configure_generic(ITensor // Configure biases accumulation if(_is_quantized) { - const QuantizationInfo output_quant_info = (output->info()->total_size() == 0) ? input->info()->quantization_info() : output->info()->quantization_info(); + const UniformQuantizationInfo iq_info = input->info()->quantization_info().uniform(); + const UniformQuantizationInfo wq_info = weights->info()->quantization_info().uniform(); + const UniformQuantizationInfo oq_info = (output->info()->total_size() == 0) ? iq_info : output->info()->quantization_info().uniform(); - float multiplier = input->info()->quantization_info().scale * weights->info()->quantization_info().scale / output_quant_info.scale; + float multiplier = (iq_info.scale * wq_info.scale) / oq_info.scale; int output_multiplier; int output_shift; quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift); - _output_stage_kernel.configure(&_accumulator, biases, _is_nchw ? output : &_permuted_output, output_multiplier, output_shift, output_quant_info.offset); + _output_stage_kernel.configure(&_accumulator, biases, _is_nchw ? output : &_permuted_output, output_multiplier, output_shift, oq_info.offset); _accumulator.allocator()->allocate(); } else if(_has_bias) @@ -459,13 +461,15 @@ void NEDepthwiseConvolutionLayer::configure(ITensor *input, const ITensor *weigh // Output staged configuration if(_is_quantized) { - const QuantizationInfo output_quant_info = output->info()->quantization_info(); + const UniformQuantizationInfo iq_info = input->info()->quantization_info().uniform(); + const UniformQuantizationInfo wq_info = weights->info()->quantization_info().uniform(); + const UniformQuantizationInfo oq_info = output->info()->quantization_info().uniform(); - float multiplier = input->info()->quantization_info().scale * weights->info()->quantization_info().scale / output_quant_info.scale; + float multiplier = (iq_info.scale * wq_info.scale) / oq_info.scale; int output_multiplier; int output_shift; quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift); - _output_stage_kernel.configure(&_output_reshaped, biases, output_to_use, output_multiplier, output_shift, output_quant_info.offset); + _output_stage_kernel.configure(&_output_reshaped, biases, output_to_use, output_multiplier, output_shift, oq_info.offset); _output_reshaped.allocator()->allocate(); } @@ -483,8 +487,8 @@ void NEDepthwiseConvolutionLayer::configure(ITensor *input, const ITensor *weigh PixelValue zero_w(static_cast<int32_t>(0)); if(_is_quantized) { - zero_in = PixelValue(static_cast<int32_t>(input->info()->quantization_info().offset)); - zero_w = PixelValue(static_cast<int32_t>(weights->info()->quantization_info().offset)); + zero_in = PixelValue(static_cast<int32_t>(input->info()->quantization_info().uniform().offset)); + zero_w = PixelValue(static_cast<int32_t>(weights->info()->quantization_info().uniform().offset)); } BorderSize border_size = _v2mm_kernel.border_size(); _v2mm_input_fill_border.configure(&_input_reshaped, border_size, BorderMode::CONSTANT, zero_in); |