arm_compute v17.10
Change-Id: If1489af40eccd0219ede8946577afbf04db31b29
diff --git a/src/graph/nodes/FullyConnectedLayer.cpp b/src/graph/nodes/FullyConnectedLayer.cpp
index 8d244cb..6b21810 100644
--- a/src/graph/nodes/FullyConnectedLayer.cpp
+++ b/src/graph/nodes/FullyConnectedLayer.cpp
@@ -24,6 +24,7 @@
#include "arm_compute/graph/nodes/FullyConnectedLayer.h"
#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/Logger.h"
#include "arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h"
#include "arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h"
#include "support/ToolchainSupport.h"
@@ -33,7 +34,17 @@
namespace
{
-template <typename FullyConnectedType, typename TensorType, Hint hint>
+TensorShape calculate_fullyconnected_layer_output_shape(const TensorShape &input_shape, unsigned int output_neurons)
+{
+ // Note: Only 1D batch space is supported at the moment
+ unsigned int batches = input_shape[1];
+ if(input_shape.num_dimensions() > 2)
+ {
+ batches = input_shape[3];
+ }
+ return TensorShape(output_neurons, batches);
+}
+template <typename FullyConnectedType, typename TensorType, TargetHint target_hint>
std::unique_ptr<arm_compute::IFunction> instantiate_function(ITensor *input, Tensor &weights, Tensor &biases, ITensor *output)
{
bool weights_are_loaded = weights.tensor() != nullptr;
@@ -42,8 +53,8 @@
auto conv = arm_compute::support::cpp14::make_unique<FullyConnectedType>();
conv->configure(
dynamic_cast<TensorType *>(input),
- dynamic_cast<TensorType *>(weights.set_target(hint)),
- dynamic_cast<TensorType *>(biases.set_target(hint)),
+ dynamic_cast<TensorType *>(weights.set_target(target_hint)),
+ dynamic_cast<TensorType *>(biases.set_target(target_hint)),
dynamic_cast<TensorType *>(output));
if(!weights_are_loaded)
{
@@ -57,23 +68,23 @@
return std::move(conv);
}
-template <Hint hint>
+template <TargetHint target_hint>
std::unique_ptr<arm_compute::IFunction> instantiate(ITensor *input, Tensor &weights, Tensor &biases, ITensor *output);
template <>
-std::unique_ptr<arm_compute::IFunction> instantiate<Hint::OPENCL>(ITensor *input, Tensor &weights, Tensor &biases, ITensor *output)
+std::unique_ptr<arm_compute::IFunction> instantiate<TargetHint::OPENCL>(ITensor *input, Tensor &weights, Tensor &biases, ITensor *output)
{
- return instantiate_function<arm_compute::CLFullyConnectedLayer, arm_compute::CLTensor, Hint::OPENCL>(input, weights, biases, output);
+ return instantiate_function<arm_compute::CLFullyConnectedLayer, arm_compute::CLTensor, TargetHint::OPENCL>(input, weights, biases, output);
}
template <>
-std::unique_ptr<arm_compute::IFunction> instantiate<Hint::NEON>(ITensor *input, Tensor &weights, Tensor &biases, ITensor *output)
+std::unique_ptr<arm_compute::IFunction> instantiate<TargetHint::NEON>(ITensor *input, Tensor &weights, Tensor &biases, ITensor *output)
{
- return instantiate_function<arm_compute::NEFullyConnectedLayer, arm_compute::Tensor, Hint::NEON>(input, weights, biases, output);
+ return instantiate_function<arm_compute::NEFullyConnectedLayer, arm_compute::Tensor, TargetHint::NEON>(input, weights, biases, output);
}
} // namespace
-std::unique_ptr<arm_compute::IFunction> FullyConnectedLayer::instantiate_node(Hint hint, ITensor *input, ITensor *output)
+std::unique_ptr<arm_compute::IFunction> FullyConnectedLayer::instantiate_node(GraphContext &ctx, ITensor *input, ITensor *output)
{
if(_weights.tensor() == nullptr)
{
@@ -95,36 +106,31 @@
_biases.set_info(TensorInfo(TensorShape(_num_neurons), input->info()->num_channels(), input->info()->data_type(), input->info()->fixed_point_position()));
}
- arm_compute::auto_init_if_empty(*output->info(), TensorShape(_num_neurons, input->info()->dimension(1)), input->info()->num_channels(), input->info()->data_type(),
- input->info()->fixed_point_position());
+ // Auto configure output
+ arm_compute::auto_init_if_empty(*output->info(),
+ calculate_fullyconnected_layer_output_shape(input->info()->tensor_shape(), _num_neurons),
+ input->info()->num_channels(), input->info()->data_type(), input->info()->fixed_point_position());
std::unique_ptr<arm_compute::IFunction> func;
- _hint = hint;
- _input = input;
- _output = output;
+ _target_hint = ctx.hints().target_hint();
- if(_hint == Hint::OPENCL)
+ if(_target_hint == TargetHint::OPENCL)
{
- func = instantiate<Hint::OPENCL>(input, _weights, _biases, output);
+ func = instantiate<TargetHint::OPENCL>(input, _weights, _biases, output);
+ ARM_COMPUTE_LOG("Instantiating CLFullyConnectedLayer");
}
else
{
- func = instantiate<Hint::NEON>(input, _weights, _biases, output);
+ func = instantiate<TargetHint::NEON>(input, _weights, _biases, output);
+ ARM_COMPUTE_LOG("Instantiating NEFullyConnectedLayer");
}
+ ARM_COMPUTE_LOG(" Type: " << input->info()->data_type()
+ << " Input Shape: " << input->info()->tensor_shape()
+ << " Weights shape: " << _weights.info().tensor_shape()
+ << " Biases Shape: " << _biases.info().tensor_shape()
+ << " Output Shape: " << output->info()->tensor_shape()
+ << std::endl);
+
return func;
}
-
-void FullyConnectedLayer::print_info()
-{
- if(_hint == Hint::OPENCL)
- {
- std::cout << "Instantiating CLFullyConnectedLayer";
- }
- else
- {
- std::cout << "Instantiating NEFullyConnectedLayer";
- }
- std::cout << " Type: " << _input->info()->data_type() << " Input Shape: " << _input->info()->tensor_shape() << " Weights shape: " << _weights.info().tensor_shape() << " Biases Shape: " <<
- _biases.info().tensor_shape() << " Output Shape: " << _output->info()->tensor_shape() << std::endl;
-}