diff options
Diffstat (limited to 'src/cpu/operators/CpuFullyConnected.cpp')
| -rw-r--r-- | src/cpu/operators/CpuFullyConnected.cpp | 43 |
1 files changed, 27 insertions, 16 deletions
diff --git a/src/cpu/operators/CpuFullyConnected.cpp b/src/cpu/operators/CpuFullyConnected.cpp index 6d77c614f7..3172644488 100644 --- a/src/cpu/operators/CpuFullyConnected.cpp +++ b/src/cpu/operators/CpuFullyConnected.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2021 Arm Limited. + * Copyright (c) 2021-2022 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -53,7 +53,7 @@ std::pair<PixelValue, PixelValue> get_quantized_asymmetric_output_min_max(const { PixelValue type_min{}; PixelValue type_max{}; - std::tie(type_min, type_max) = get_min_max(data_type); + std::tie(type_min, type_max) = get_min_max(data_type); const UniformQuantizationInfo q_unif = q_info.uniform(); if(act_info.enabled()) @@ -162,8 +162,9 @@ CpuFullyConnected::CpuFullyConnected() _is_fc_after_conv(false), _is_quantized_asymmetric(false), _is_prepared(false), - _enable_fast_math(false) - + _enable_fast_math(false), + _fixed_format(false), + _weight_format(arm_compute::WeightFormat::UNSPECIFIED) { } @@ -199,6 +200,8 @@ void CpuFullyConnected::configure_mm(const ITensorInfo *src, const ITensorInfo * GEMMInfo gemm_info(false, false, true /* Reshape weights only for the first run */); gemm_info.set_activation_info(act); gemm_info.set_fast_math(_enable_fast_math); + gemm_info.set_fixed_format(_fixed_format); + gemm_info.set_weight_format(_weight_format); _mm_gemm = std::make_unique<CpuGemm>(); _mm_gemm->configure(src, weights, biases, dst, 1.f, 1.0f, gemm_info); } @@ -229,7 +232,7 @@ void CpuFullyConnected::configure_fc_fc(const ITensorInfo *src, const ITensorInf } void CpuFullyConnected::configure(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, ITensorInfo *dst, - FullyConnectedLayerInfo fc_info) + FullyConnectedLayerInfo fc_info, const WeightsInfo &weights_info) { // Perform validate step ARM_COMPUTE_ERROR_ON_NULLPTR(src, weights, dst); @@ -248,6 +251,8 @@ void CpuFullyConnected::configure(const ITensorInfo *src, const ITensorInfo *wei _is_prepared = false; _trans_weights_idx = AuxTensorIdx::Count; _enable_fast_math = fc_info.enable_fast_math; + _fixed_format = weights_info.weight_format() != WeightFormat::UNSPECIFIED; + _weight_format = weights_info.weight_format(); // With the Fully Connected layer we can have 4 different cases: // 1) Convolution layer -> Fully Connected layer without batches @@ -261,9 +266,7 @@ void CpuFullyConnected::configure(const ITensorInfo *src, const ITensorInfo *wei const bool is_batched_fc_layer = dst->dimension(1) > 1; if(is_batched_fc_layer) { - _is_fc_after_conv = (TensorShape::num_max_dimensions >= 4) && (std::equal(src->tensor_shape().cbegin() + 3, - src->tensor_shape().cend(), - dst->tensor_shape().cbegin() + 1)); + _is_fc_after_conv = (TensorShape::num_max_dimensions >= 4) && (std::equal(src->tensor_shape().cbegin() + 3, src->tensor_shape().cend(), dst->tensor_shape().cbegin() + 1)); } else { @@ -323,12 +326,10 @@ void CpuFullyConnected::configure(const ITensorInfo *src, const ITensorInfo *wei { // Release permuted weights at the end of prepare as they are further transposed by the assembly dispatch // Do not release them if biases are dynamic and data type is quantized, since the weights tensor will be used for biases offset calculation - _aux_mem[TransposedWeights] = MemoryInfo(offset_int_vec(TransposedWeights), (_is_quantized_asymmetric - && biases && !(biases->are_values_constant())) ? - MemoryLifetime::Persistent : - MemoryLifetime::Prepare, + _aux_mem[TransposedWeights] = MemoryInfo(offset_int_vec(TransposedWeights), (_is_quantized_asymmetric && biases + && !(biases->are_values_constant())) ? MemoryLifetime::Persistent : MemoryLifetime::Prepare, _reshaped_weights.total_size()); - _aux_mem[ConvertedWeights] = MemoryInfo(offset_int_vec(ConvertedWeights), MemoryLifetime::Prepare, _converted_weights.total_size()); + _aux_mem[ConvertedWeights] = MemoryInfo(offset_int_vec(ConvertedWeights), MemoryLifetime::Prepare, _converted_weights.total_size()); } else { @@ -338,6 +339,18 @@ void CpuFullyConnected::configure(const ITensorInfo *src, const ITensorInfo *wei _aux_mem[FlattenedSrc] = MemoryInfo(offset_int_vec(FlattenedSrc), MemoryLifetime::Temporary, _flattened_src.total_size()); } +Status CpuFullyConnected::has_opt_impl(arm_compute::WeightFormat &expected_weight_format, const ITensorInfo *src, const ITensorInfo *weights, + const ITensorInfo *biases, const ITensorInfo *dst, FullyConnectedLayerInfo fc_info, WeightsInfo weights_info) +{ + GEMMInfo gemm_info(false, false, true /* Reshape weights only for the first run */); + gemm_info.set_activation_info(fc_info.activation_info); + gemm_info.set_fast_math(fc_info.enable_fast_math); + gemm_info.set_fixed_format(weights_info.weight_format() != WeightFormat::UNSPECIFIED); + gemm_info.set_weight_format(weights_info.weight_format()); + + return CpuGemm::has_opt_impl(expected_weight_format, src, weights, biases, dst, gemm_info); +} + Status CpuFullyConnected::validate(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *dst, FullyConnectedLayerInfo fc_info) { @@ -384,9 +397,7 @@ Status CpuFullyConnected::validate(const ITensorInfo *src, const ITensorInfo *we if(is_batched_fc_layer) { - is_fc_after_conv = (TensorShape::num_max_dimensions >= 4) && (std::equal(src->tensor_shape().cbegin() + 3, - src->tensor_shape().cend(), - dst->tensor_shape().cbegin() + 1)); + is_fc_after_conv = (TensorShape::num_max_dimensions >= 4) && (std::equal(src->tensor_shape().cbegin() + 3, src->tensor_shape().cend(), dst->tensor_shape().cbegin() + 1)); } else { |