diff options
Diffstat (limited to 'src/graph/operations/NESimpleOperations.cpp')
| -rw-r--r-- | src/graph/operations/NESimpleOperations.cpp | 136 |
1 files changed, 136 insertions, 0 deletions
diff --git a/src/graph/operations/NESimpleOperations.cpp b/src/graph/operations/NESimpleOperations.cpp index 59f252ae44..12f8c6c76b 100644 --- a/src/graph/operations/NESimpleOperations.cpp +++ b/src/graph/operations/NESimpleOperations.cpp @@ -106,6 +106,90 @@ REGISTER_SIMPLE_OPERATION(NEBatchNormalizationLayerOperation, NEON, OperationTyp return std::move(batch_norm); } +/* DepthConvert Layer */ +REGISTER_SIMPLE_OPERATION(NEDepthConvertLayerOperation, NEON, OperationType::DepthConvertLayer) +{ + ARM_COMPUTE_ERROR_ON(ctx.num_inputs() != 1); + ARM_COMPUTE_ERROR_ON(ctx.num_outputs() != 1); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.input(0)) == nullptr); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.output(0)) == nullptr); + + // Extract IO and info + auto *in = dynamic_cast<arm_compute::ITensor *>(ctx.input(0)); + auto *out = dynamic_cast<arm_compute::ITensor *>(ctx.output(0)); + const auto conv_policy = ctx.parameter<ConvertPolicy>("ConvertPolicy"); + const auto shift = ctx.parameter<uint32_t>("shift"); + + // Create and configure function + auto depthconvert = arm_compute::support::cpp14::make_unique<arm_compute::NEDepthConvert>(); + depthconvert->configure(in, out, conv_policy, shift); + + // Log info + ARM_COMPUTE_LOG_GRAPH_INFO("Instantiating NEDepthConvertLayer" + << " Data Type: " << in->info()->data_type() + << " Input shape: " << in->info()->tensor_shape() + << " Output shape: " << out->info()->tensor_shape() + << " shift: " << shift + << std::endl); + + return std::move(depthconvert); +} + +/* DeQuantizationLayer Layer */ +REGISTER_SIMPLE_OPERATION(NEDequantizationLayerOperation, NEON, OperationType::DequantizationLayer) +{ + ARM_COMPUTE_ERROR_ON(ctx.num_inputs() != 1); + ARM_COMPUTE_ERROR_ON(ctx.num_outputs() != 2); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.input(0)) == nullptr); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.output(0)) == nullptr); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.output(1)) == nullptr); + + // Extract IO and info + auto *in = dynamic_cast<arm_compute::ITensor *>(ctx.input(0)); + auto *out = dynamic_cast<arm_compute::ITensor *>(ctx.output(0)); + auto *min_max = dynamic_cast<arm_compute::ITensor *>(ctx.output(1)); + + // Create and configure function + auto dequantization = arm_compute::support::cpp14::make_unique<arm_compute::NEDequantizationLayer>(); + dequantization->configure(in, out, min_max); + + // Log info + ARM_COMPUTE_LOG_GRAPH_INFO("Instantiating NEDequantizationLayer" + << " Data Type: " << in->info()->data_type() + << " Input shape: " << in->info()->tensor_shape() + << " Output shape: " << out->info()->tensor_shape() + << " Min max shape: " << min_max->info()->tensor_shape() + << std::endl); + + return std::move(dequantization); +} + +/* Flatten Layer */ +REGISTER_SIMPLE_OPERATION(NEFlattenLayerOperation, NEON, OperationType::FlattenLayer) +{ + ARM_COMPUTE_ERROR_ON(ctx.num_inputs() != 1); + ARM_COMPUTE_ERROR_ON(ctx.num_outputs() != 1); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.input(0)) == nullptr); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.output(0)) == nullptr); + + // Extract IO and info + auto *in = dynamic_cast<arm_compute::ITensor *>(ctx.input(0)); + auto *out = dynamic_cast<arm_compute::ITensor *>(ctx.output(0)); + + // Create and configure function + auto flatten = arm_compute::support::cpp14::make_unique<arm_compute::NEFlattenLayer>(); + flatten->configure(in, out); + + // Log info + ARM_COMPUTE_LOG_GRAPH_INFO("Instantiating NEFlattenLayer" + << " Data Type: " << in->info()->data_type() + << " Input shape: " << in->info()->tensor_shape() + << " Output shape: " << out->info()->tensor_shape() + << std::endl); + + return std::move(flatten); +} + /* Floor Layer */ REGISTER_SIMPLE_OPERATION(NEFloorLayerOperation, NEON, OperationType::FloorLayer) { @@ -250,6 +334,58 @@ REGISTER_SIMPLE_OPERATION(NEPoolingLayerOperation, NEON, OperationType::PoolingL return std::move(pool); } +/* Quantization Layer */ +REGISTER_SIMPLE_OPERATION(NEQuantizationLayerOperation, NEON, OperationType::QuantizationLayer) +{ + ARM_COMPUTE_ERROR_ON(ctx.num_inputs() != 1); + ARM_COMPUTE_ERROR_ON(ctx.num_outputs() != 1); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.input(0)) == nullptr); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.output(0)) == nullptr); + + // Extract IO and info + auto *in = dynamic_cast<arm_compute::ITensor *>(ctx.input(0)); + auto *out = dynamic_cast<arm_compute::ITensor *>(ctx.output(0)); + + // Create and configure function + auto quantization = arm_compute::support::cpp14::make_unique<arm_compute::NEQuantizationLayer>(); + quantization->configure(in, out); + + // Log info + ARM_COMPUTE_LOG_GRAPH_INFO("Instantiating NEQuantizationLayer" + << " Data Type: " << in->info()->data_type() + << " Input shape: " << in->info()->tensor_shape() + << " Output shape: " << out->info()->tensor_shape() + << std::endl); + + return std::move(quantization); +} + +/* Reshape Layer */ +REGISTER_SIMPLE_OPERATION(NEReshapeLayerOperation, NEON, OperationType::ReshapeLayer) +{ + ARM_COMPUTE_ERROR_ON(ctx.num_inputs() != 1); + ARM_COMPUTE_ERROR_ON(ctx.num_outputs() != 1); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.input(0)) == nullptr); + ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ITensor *>(ctx.output(0)) == nullptr); + + // Extract IO and info + auto *in = dynamic_cast<arm_compute::ITensor *>(ctx.input(0)); + auto *out = dynamic_cast<arm_compute::ITensor *>(ctx.output(0)); + + // Create and configure function + auto reshape = arm_compute::support::cpp14::make_unique<arm_compute::NEReshapeLayer>(); + reshape->configure(in, out); + + // Log info + ARM_COMPUTE_LOG_GRAPH_INFO("Instantiating NEReshapeLayer" + << " Data Type: " << in->info()->data_type() + << " Input shape: " << in->info()->tensor_shape() + << " Output shape: " << out->info()->tensor_shape() + << std::endl); + + return std::move(reshape); +} + /* Softmax Layer */ REGISTER_SIMPLE_OPERATION(NESoftmaxLayerOperation, NEON, OperationType::SoftmaxLayer) { |