diff options
Diffstat (limited to 'src/cpu')
-rw-r--r-- | src/cpu/operators/CpuFullyConnected.cpp | 50 | ||||
-rw-r--r-- | src/cpu/operators/CpuFullyConnected.h | 6 | ||||
-rw-r--r-- | src/cpu/operators/CpuGemm.cpp | 15 |
3 files changed, 53 insertions, 18 deletions
diff --git a/src/cpu/operators/CpuFullyConnected.cpp b/src/cpu/operators/CpuFullyConnected.cpp index 1e1598a8ee..af630154cf 100644 --- a/src/cpu/operators/CpuFullyConnected.cpp +++ b/src/cpu/operators/CpuFullyConnected.cpp @@ -166,7 +166,8 @@ CpuFullyConnected::CpuFullyConnected() _is_prepared(false), _enable_fast_math(false), _fixed_format(false), - _weight_format(arm_compute::WeightFormat::UNSPECIFIED) + _weight_format(arm_compute::WeightFormat::UNSPECIFIED), + _dynamic_weights(false) { } @@ -189,7 +190,7 @@ void CpuFullyConnected::configure_mm(const ITensorInfo *src, const ITensorInfo * const Status status = get_gemmlowp_output_stage_info(&src_info, &weights_info, dst, act, gemmlowp_output_stage_info); ARM_COMPUTE_ERROR_ON(status.error_code() != ErrorCode::OK); - GEMMInfo gemm_info; + GEMMInfo gemm_info(false, false, !_dynamic_weights /* Reshape weights only for the first run */); gemm_info.set_gemmlowp_output_stage(gemmlowp_output_stage_info); gemm_info.set_activation_info(act); gemm_info.set_fast_math(_enable_fast_math); @@ -199,7 +200,7 @@ void CpuFullyConnected::configure_mm(const ITensorInfo *src, const ITensorInfo * else { // Configure matrix multiply kernel - GEMMInfo gemm_info(false, false, true /* Reshape weights only for the first run */); + GEMMInfo gemm_info(false, false, !_dynamic_weights /* 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); @@ -256,6 +257,7 @@ void CpuFullyConnected::configure(const ITensorInfo *src, const ITensorInfo *wei _enable_fast_math = fc_info.enable_fast_math; _fixed_format = weights_info.weight_format() != WeightFormat::UNSPECIFIED; _weight_format = weights_info.weight_format(); + _dynamic_weights = !weights->are_values_constant() && _needs_weights_reshape; // With the Fully Connected layer we can have 4 different cases: // 1) Convolution layer -> Fully Connected layer without batches @@ -329,15 +331,32 @@ 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, - _reshaped_weights.total_size()); - _aux_mem[ConvertedWeights] = MemoryInfo(offset_int_vec(ConvertedWeights), MemoryLifetime::Prepare, _converted_weights.total_size()); + // Keep all the auxiliary tensors in case of dynamic weights as they are recalculated every time. + _aux_mem[TransposedWeights] = MemoryInfo( + offset_int_vec(TransposedWeights), + _dynamic_weights ? MemoryLifetime::Temporary : + (_is_quantized_asymmetric && biases && !(biases->are_values_constant())) ? MemoryLifetime::Persistent : + MemoryLifetime::Prepare, + _reshaped_weights.total_size()); + + _aux_mem[ConvertedWeights] = MemoryInfo( + offset_int_vec(ConvertedWeights), + _dynamic_weights ? MemoryLifetime::Temporary : MemoryLifetime::Prepare, + _converted_weights.total_size()); } else { - _aux_mem[TransposedWeights] = MemoryInfo(offset_int_vec(TransposedWeights), _needs_weights_conversion ? MemoryLifetime::Prepare : MemoryLifetime::Persistent, _reshaped_weights.total_size()); - _aux_mem[ConvertedWeights] = MemoryInfo(offset_int_vec(ConvertedWeights), MemoryLifetime::Persistent, _converted_weights.total_size()); + _aux_mem[TransposedWeights] = MemoryInfo( + offset_int_vec(TransposedWeights), + _dynamic_weights ? MemoryLifetime::Temporary : + _needs_weights_conversion ? MemoryLifetime::Prepare : + MemoryLifetime::Persistent, + _reshaped_weights.total_size()); + + _aux_mem[ConvertedWeights] = MemoryInfo( + offset_int_vec(ConvertedWeights), + _dynamic_weights ? MemoryLifetime::Temporary : MemoryLifetime::Persistent, + _converted_weights.total_size()); } _aux_mem[FlattenedSrc] = MemoryInfo(offset_int_vec(FlattenedSrc), MemoryLifetime::Temporary, _flattened_src.total_size()); } @@ -375,7 +394,6 @@ Status CpuFullyConnected::validate(const ITensorInfo *src, const ITensorInfo *we ARM_COMPUTE_RETURN_ERROR_ON(weights->num_dimensions() > 2); ARM_COMPUTE_RETURN_ERROR_ON(fc_info.activation_info.enabled() && is_data_type_quantized(src->data_type()) && fc_info.activation_info.activation() != ActivationLayerInfo::ActivationFunction::RELU && fc_info.activation_info.activation() != ActivationLayerInfo::ActivationFunction::BOUNDED_RELU && fc_info.activation_info.activation() != ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU); - ARM_COMPUTE_RETURN_ERROR_ON(!weights->are_values_constant() && (!fc_info.are_weights_reshaped || fc_info.transpose_weights)); bool weights_reshaped = fc_info.transpose_weights ? fc_info.are_weights_reshaped : true; bool is_fc_after_conv = true; @@ -459,6 +477,11 @@ void CpuFullyConnected::run(ITensorPack &tensors) { prepare(tensors); +#ifdef ARM_COMPUTE_ASSERTS_ENABLED + ++_asrt_run_count; + ARM_COMPUTE_ERROR_ON(_dynamic_weights && _asrt_prepare_count != _asrt_run_count); +#endif // ARM_COMPUTE_ASSERTS_ENABLED + auto src = tensors.get_const_tensor(ACL_SRC_0); CpuAuxTensorHandler flattened_src(offset_int_vec(FlattenedSrc), _flattened_src, tensors, false); @@ -491,8 +514,13 @@ void CpuFullyConnected::run(ITensorPack &tensors) void CpuFullyConnected::prepare(ITensorPack &tensors) { - if(!_is_prepared) + if(!_is_prepared || _dynamic_weights) { +#ifdef ARM_COMPUTE_ASSERTS_ENABLED + ++_asrt_prepare_count; + ARM_COMPUTE_ERROR_ON(!_dynamic_weights && _asrt_prepare_count > 1); +#endif // ARM_COMPUTE_ASSERTS_ENABLED + auto weights = tensors.get_const_tensor(ACL_SRC_1); CpuAuxTensorHandler reshaped_weights(offset_int_vec(TransposedWeights), _reshaped_weights, tensors, false); diff --git a/src/cpu/operators/CpuFullyConnected.h b/src/cpu/operators/CpuFullyConnected.h index 9cd67f2ca6..a5a464f67a 100644 --- a/src/cpu/operators/CpuFullyConnected.h +++ b/src/cpu/operators/CpuFullyConnected.h @@ -155,6 +155,12 @@ private: bool _enable_fast_math; bool _fixed_format; arm_compute::WeightFormat _weight_format; + bool _dynamic_weights; + +#ifdef ARM_COMPUTE_ASSERTS_ENABLED + int _asrt_run_count{}; + int _asrt_prepare_count{}; +#endif // ARM_COMPUTE_ASSERTS_ENABLED }; } // namespace cpu } // namespace arm_compute diff --git a/src/cpu/operators/CpuGemm.cpp b/src/cpu/operators/CpuGemm.cpp index 545d59f410..f914bceec3 100644 --- a/src/cpu/operators/CpuGemm.cpp +++ b/src/cpu/operators/CpuGemm.cpp @@ -64,7 +64,7 @@ void CpuGemm::configure(const ITensorInfo *a, const ITensorInfo *b, const ITenso ARM_COMPUTE_LOG_PARAMS(a, b, c, d, alpha, beta, gemm_info); const cpu::AsmGemmInfo asm_info = init_assembly_metadata(gemm_info); - const bool is_c_bias = gemm_info.reshape_b_only_on_first_run(); + const bool is_c_bias = beta == 1 && c != nullptr; bool run_optimised = bool(cpu::CpuGemmAssemblyDispatch::validate(a, b, (is_c_bias) ? c : nullptr, d, asm_info)) && gemm_info.reshape_b_only_on_first_run(); // Check if we need to reshape the matrix B only on the first run @@ -72,8 +72,8 @@ void CpuGemm::configure(const ITensorInfo *a, const ITensorInfo *b, const ITenso _reshape_b_only_on_first_run = gemm_info.reshape_b_only_on_first_run(); _run_vector_matrix_multiplication = a->dimension(1) < 2; _run_alpha_scale = alpha != 1.f; - _run_bias_addition = c != nullptr && gemm_info.reshape_b_only_on_first_run(); - _run_addition = beta != 0 && c != nullptr && !gemm_info.reshape_b_only_on_first_run(); + _run_bias_addition = is_c_bias; + _run_addition = beta != 0 && beta != 1 && c != nullptr; _run_activation = gemm_info.activation_info().enabled() && (!run_optimised || (run_optimised && !cpu::CpuGemmAssemblyDispatch::is_activation_supported(gemm_info.activation_info()))); if(run_optimised) @@ -153,12 +153,13 @@ void CpuGemm::configure(const ITensorInfo *a, const ITensorInfo *b, const ITenso Status CpuGemm::validate(const ITensorInfo *a, const ITensorInfo *b, const ITensorInfo *c, const ITensorInfo *d, float alpha, float beta, const GEMMInfo &gemm_info) { ARM_COMPUTE_UNUSED(alpha); - const bool is_c_bias = gemm_info.reshape_b_only_on_first_run(); + const bool is_c_bias = beta == 1 && c != nullptr; + const bool run_addition = c != nullptr && beta != 0 && beta != 1; ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(a); ARM_COMPUTE_RETURN_ERROR_ON_CPU_BF16_UNSUPPORTED(a); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(a, 1, DataType::BFLOAT16, DataType::F16, DataType::F32); - + if (is_fixed_format_fast_math(gemm_info.weight_format())) { ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(a, DataType::F32); @@ -177,7 +178,7 @@ Status CpuGemm::validate(const ITensorInfo *a, const ITensorInfo *b, const ITens ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(a, d); } - if(c != nullptr && !is_c_bias) + if(run_addition) { ARM_COMPUTE_RETURN_ERROR_ON(gemm_info.depth_output_gemm3d() != 0); ARM_COMPUTE_RETURN_ERROR_ON(gemm_info.reinterpret_input_as_3d()); @@ -265,7 +266,7 @@ Status CpuGemm::validate(const ITensorInfo *a, const ITensorInfo *b, const ITens } // Validate matrix addition kernel - if(beta != 0 && c != nullptr && !is_c_bias) + if(run_addition) { ARM_COMPUTE_RETURN_ON_ERROR(cpu::kernels::CpuGemmMatrixAdditionKernel::validate(c, d, beta)); } |