COMPMID-554 Add Nodes
- BatchNormalization
- DepthConvert
- Dequantization
- Flatten
- Quantization
- Reshape
Change-Id: Ie01a04b7a6cc8e2b5481cf2345268e6871580d7f
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/91618
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
diff --git a/src/graph/operations/CLSimpleOperations.cpp b/src/graph/operations/CLSimpleOperations.cpp
index b4c217b..a42fada 100644
--- a/src/graph/operations/CLSimpleOperations.cpp
+++ b/src/graph/operations/CLSimpleOperations.cpp
@@ -106,6 +106,90 @@
return std::move(batch_norm);
}
+/* DepthConvert Layer */
+REGISTER_SIMPLE_OPERATION(CLDepthConvertLayerOperation, OPENCL, 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::ICLTensor *>(ctx.input(0)) == nullptr);
+ ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ICLTensor *>(ctx.output(0)) == nullptr);
+
+ // Extract IO and info
+ auto *in = dynamic_cast<arm_compute::ICLTensor *>(ctx.input(0));
+ auto *out = dynamic_cast<arm_compute::ICLTensor *>(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::CLDepthConvert>();
+ depthconvert->configure(in, out, conv_policy, shift);
+
+ // Log info
+ ARM_COMPUTE_LOG_GRAPH_INFO("Instantiating CLDepthConvertLayer"
+ << " 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(CLDequantizationLayerOperation, OPENCL, 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::ICLTensor *>(ctx.input(0)) == nullptr);
+ ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ICLTensor *>(ctx.output(0)) == nullptr);
+ ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ICLTensor *>(ctx.output(1)) == nullptr);
+
+ // Extract IO and info
+ auto *in = dynamic_cast<arm_compute::ICLTensor *>(ctx.input(0));
+ auto *out = dynamic_cast<arm_compute::ICLTensor *>(ctx.output(0));
+ auto *min_max = dynamic_cast<arm_compute::ICLTensor *>(ctx.output(1));
+
+ // Create and configure function
+ auto dequantization = arm_compute::support::cpp14::make_unique<arm_compute::CLDequantizationLayer>();
+ dequantization->configure(in, out, min_max);
+
+ // Log info
+ ARM_COMPUTE_LOG_GRAPH_INFO("Instantiating CLDequantizationLayer"
+ << " 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(CLFlattenLayerOperation, OPENCL, 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::ICLTensor *>(ctx.input(0)) == nullptr);
+ ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ICLTensor *>(ctx.output(0)) == nullptr);
+
+ // Extract IO and info
+ auto *in = dynamic_cast<arm_compute::ICLTensor *>(ctx.input(0));
+ auto *out = dynamic_cast<arm_compute::ICLTensor *>(ctx.output(0));
+
+ // Create and configure function
+ auto flatten = arm_compute::support::cpp14::make_unique<arm_compute::CLFlattenLayer>();
+ 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(CLFloorLayerOperation, OPENCL, OperationType::FloorLayer)
{
@@ -250,6 +334,58 @@
return std::move(pool);
}
+/* Quantization Layer */
+REGISTER_SIMPLE_OPERATION(CLQuantizationLayerOperation, OPENCL, 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::ICLTensor *>(ctx.input(0)) == nullptr);
+ ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ICLTensor *>(ctx.output(0)) == nullptr);
+
+ // Extract IO and info
+ auto *in = dynamic_cast<arm_compute::ICLTensor *>(ctx.input(0));
+ auto *out = dynamic_cast<arm_compute::ICLTensor *>(ctx.output(0));
+
+ // Create and configure function
+ auto quantization = arm_compute::support::cpp14::make_unique<arm_compute::CLQuantizationLayer>();
+ 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(CLReshapeLayerOperation, OPENCL, 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::ICLTensor *>(ctx.input(0)) == nullptr);
+ ARM_COMPUTE_ERROR_ON(dynamic_cast<arm_compute::ICLTensor *>(ctx.output(0)) == nullptr);
+
+ // Extract IO and info
+ auto *in = dynamic_cast<arm_compute::ICLTensor *>(ctx.input(0));
+ auto *out = dynamic_cast<arm_compute::ICLTensor *>(ctx.output(0));
+
+ // Create and configure function
+ auto reshape = arm_compute::support::cpp14::make_unique<arm_compute::CLReshapeLayer>();
+ 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(CLSoftmaxLayerOperation, OPENCL, OperationType::SoftmaxLayer)
{