COMPMID-549 Create a Logger for GraphAPI

Change-Id: If912d8232e12cd496923d55d386898450dac09e2
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/89897
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>

6 files changed, 71 insertions, 134 deletions

diff --git a/src/graph/nodes/ActivationLayer.cpp b/src/graph/nodes/ActivationLayer.cpp
index da2dac04e2..5cd2a0bcc2 100644
--- a/src/graph/nodes/ActivationLayer.cpp
+++ b/src/graph/nodes/ActivationLayer.cpp
@@ -23,6 +23,7 @@
  */
 #include "arm_compute/graph/nodes/ActivationLayer.h"
 
+#include "arm_compute/core/Logger.h"
 #include "arm_compute/runtime/CL/CLTensor.h"
 #include "arm_compute/runtime/CL/functions/CLActivationLayer.h"
 #include "arm_compute/runtime/NEON/functions/NEActivationLayer.h"
@@ -71,36 +72,24 @@ std::unique_ptr<arm_compute::IFunction> ActivationLayer::instantiate_node(GraphC
 {
     std::unique_ptr<arm_compute::IFunction> func;
     _target_hint = ctx.hints().target_hint();
-    _input       = input;
-    _output      = output;
 
     if(_target_hint == TargetHint::OPENCL)
     {
         func = instantiate<TargetHint::OPENCL>(input, output, _activation_info);
+        ARM_COMPUTE_LOG("Instantiating CLActivationLayer");
     }
     else
     {
         func = instantiate<TargetHint::NEON>(input, output, _activation_info);
+        ARM_COMPUTE_LOG("Instantiating NEActivationLayer");
     }
-    return func;
-}
 
-void ActivationLayer::print_info()
-{
-    if(_target_hint == TargetHint::OPENCL)
-    {
-        std::cout << "Instantiating CLActivationLayer";
-    }
-    else
-    {
-        std::cout << "Instantiating NEActivationLayer";
-    }
-
-    std::cout << " Data Type: " << _input->info()->data_type()
-              << " Input shape: " << _input->info()->tensor_shape()
-              << " Output shape: " << _output->info()->tensor_shape()
-              << " Activation function: " << _activation_info.activation()
-              << " a: " << _activation_info.a()
-              << " b: " << _activation_info.b()
-              << std::endl;
+    ARM_COMPUTE_LOG(" Data Type: " << input->info()->data_type()
+                    << " Input shape: " << input->info()->tensor_shape()
+                    << " Output shape: " << output->info()->tensor_shape()
+                    << " Activation function: " << _activation_info.activation()
+                    << " a: " << _activation_info.a()
+                    << " b: " << _activation_info.b()
+                    << std::endl);
+    return func;
 }
diff --git a/src/graph/nodes/ConvolutionLayer.cpp b/src/graph/nodes/ConvolutionLayer.cpp
index a992095786..b47be8dc33 100644
--- a/src/graph/nodes/ConvolutionLayer.cpp
+++ b/src/graph/nodes/ConvolutionLayer.cpp
@@ -23,6 +23,7 @@
  */
 #include "arm_compute/graph/nodes/ConvolutionLayer.h"
 
+#include "arm_compute/core/Logger.h"
 #include "arm_compute/runtime/CL/functions/CLConvolutionLayer.h"
 #include "arm_compute/runtime/CL/functions/CLDirectConvolutionLayer.h"
 #include "arm_compute/runtime/IFunction.h"
@@ -184,8 +185,6 @@ std::unique_ptr<arm_compute::IFunction> ConvolutionLayer::instantiate_node(Graph
 
     std::unique_ptr<arm_compute::IFunction> func;
     _target_hint                                 = ctx.hints().target_hint();
-    _input                                       = input;
-    _output                                      = output;
     const ConvolutionMethodHint conv_method_hint = ctx.hints().convolution_method_hint();
 
     // Check if the weights and biases are loaded
@@ -197,19 +196,21 @@ std::unique_ptr<arm_compute::IFunction> ConvolutionLayer::instantiate_node(Graph
     _biases.set_target(_target_hint);
 
     // Calculate output shape
-    TensorShape output_shape = calculate_convolution_layer_output_shape(_input->info()->tensor_shape(), _weights.info().tensor_shape(), _conv_info);
+    TensorShape output_shape = calculate_convolution_layer_output_shape(input->info()->tensor_shape(), _weights.info().tensor_shape(), _conv_info);
 
     // Output auto inizialitation if not yet initialized
-    arm_compute::auto_init_if_empty(*_output->info(), output_shape, 1, _input->info()->data_type(), _input->info()->fixed_point_position());
+    arm_compute::auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type(), input->info()->fixed_point_position());
 
     // Create appropriate convolution function
     if(_num_groups == 1)
     {
-        func = instantiate_convolution(conv_method_hint);
+        func = instantiate_convolution(input, output, conv_method_hint);
+        ARM_COMPUTE_LOG("Instantiating CLConvolutionLayer");
     }
     else
     {
-        func = instantiate_grouped_convolution(conv_method_hint);
+        func = instantiate_grouped_convolution(input, output, conv_method_hint);
+        ARM_COMPUTE_LOG("Instantiating NEConvolutionLayer");
     }
 
     // Fill weights
@@ -223,49 +224,38 @@ std::unique_ptr<arm_compute::IFunction> ConvolutionLayer::instantiate_node(Graph
         _biases.allocate_and_fill_if_needed();
     }
 
-    return func;
-}
+    ARM_COMPUTE_LOG(" Data 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()
+                    << " PadStrideInfo: " << _conv_info
+                    << " Groups: " << _num_groups
+                    << " WeightsInfo: " << _weights_info
+                    << std::endl);
 
-void ConvolutionLayer::print_info()
-{
-    if(_target_hint == TargetHint::OPENCL)
-    {
-        std::cout << "Instantiating CLConvolutionLayer";
-    }
-    else
-    {
-        std::cout << "Instantiating NEConvolutionLayer";
-    }
-    std::cout << " Data 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()
-              << " PadStrideInfo: " << _conv_info
-              << " Groups: " << _num_groups
-              << " WeightsInfo: " << _weights_info
-              << std::endl;
+    return func;
 }
 
-std::unique_ptr<arm_compute::IFunction> ConvolutionLayer::instantiate_convolution(ConvolutionMethodHint conv_method_hint)
+std::unique_ptr<arm_compute::IFunction> ConvolutionLayer::instantiate_convolution(ITensor *input, ITensor *output, ConvolutionMethodHint conv_method_hint)
 {
     std::unique_ptr<arm_compute::IFunction> func;
     if(_target_hint == TargetHint::OPENCL)
     {
-        func = instantiate<TargetHint::OPENCL>(_input, _weights.tensor(), _biases.tensor(), _output, _conv_info, _weights_info, conv_method_hint);
+        func = instantiate<TargetHint::OPENCL>(input, _weights.tensor(), _biases.tensor(), output, _conv_info, _weights_info, conv_method_hint);
     }
     else
     {
-        func = instantiate<TargetHint::NEON>(_input, _weights.tensor(), _biases.tensor(), _output, _conv_info, _weights_info, conv_method_hint);
+        func = instantiate<TargetHint::NEON>(input, _weights.tensor(), _biases.tensor(), output, _conv_info, _weights_info, conv_method_hint);
     }
     return func;
 }
 
-std::unique_ptr<arm_compute::IFunction> ConvolutionLayer::instantiate_grouped_convolution(ConvolutionMethodHint conv_method_hint)
+std::unique_ptr<arm_compute::IFunction> ConvolutionLayer::instantiate_grouped_convolution(ITensor *input, ITensor *output, ConvolutionMethodHint conv_method_hint)
 {
     // Get tensor shapes
-    TensorShape input_shape   = _input->info()->tensor_shape();
-    TensorShape output_shape  = _output->info()->tensor_shape();
+    TensorShape input_shape   = input->info()->tensor_shape();
+    TensorShape output_shape  = output->info()->tensor_shape();
     TensorShape weights_shape = _weights.info().tensor_shape();
     TensorShape biases_shape  = _biases.info().tensor_shape();
 
@@ -309,8 +299,8 @@ std::unique_ptr<arm_compute::IFunction> ConvolutionLayer::instantiate_grouped_co
 
         // Create sub-tensors for input, output, weights and bias
         auto hint_to_use = (_target_hint == TargetHint::OPENCL) ? TargetHint::OPENCL : TargetHint::NEON;
-        _is[i]           = SubTensor(_input, input_shape, input_coord, hint_to_use);
-        _os[i]           = SubTensor(_output, output_shape, output_coord, hint_to_use);
+        _is[i]           = SubTensor(input, input_shape, input_coord, hint_to_use);
+        _os[i]           = SubTensor(output, output_shape, output_coord, hint_to_use);
         _ws[i]           = SubTensor(_weights.tensor(), weights_shape, weights_coord, hint_to_use);
         _bs[i]           = SubTensor(_biases.tensor(), biases_shape, biases_coord, hint_to_use);
 
diff --git a/src/graph/nodes/FullyConnectedLayer.cpp b/src/graph/nodes/FullyConnectedLayer.cpp
index c317660b20..6b21810a36 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"
@@ -112,35 +113,24 @@ std::unique_ptr<arm_compute::IFunction> FullyConnectedLayer::instantiate_node(Gr
 
     std::unique_ptr<arm_compute::IFunction> func;
     _target_hint = ctx.hints().target_hint();
-    _input       = input;
-    _output      = output;
 
     if(_target_hint == TargetHint::OPENCL)
     {
         func = instantiate<TargetHint::OPENCL>(input, _weights, _biases, output);
+        ARM_COMPUTE_LOG("Instantiating CLFullyConnectedLayer");
     }
     else
     {
         func = instantiate<TargetHint::NEON>(input, _weights, _biases, output);
+        ARM_COMPUTE_LOG("Instantiating NEFullyConnectedLayer");
     }
 
-    return func;
-}
+    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);
 
-void FullyConnectedLayer::print_info()
-{
-    if(_target_hint == TargetHint::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;
+    return func;
 }
diff --git a/src/graph/nodes/NormalizationLayer.cpp b/src/graph/nodes/NormalizationLayer.cpp
index 99d07dc8da..47f0891dfb 100644
--- a/src/graph/nodes/NormalizationLayer.cpp
+++ b/src/graph/nodes/NormalizationLayer.cpp
@@ -23,6 +23,7 @@
  */
 #include "arm_compute/graph/nodes/NormalizationLayer.h"
 
+#include "arm_compute/core/Logger.h"
 #include "arm_compute/runtime/CL/CLTensor.h"
 #include "arm_compute/runtime/CL/functions/CLNormalizationLayer.h"
 #include "arm_compute/runtime/NEON/functions/NENormalizationLayer.h"
@@ -71,35 +72,23 @@ std::unique_ptr<arm_compute::IFunction> NormalizationLayer::instantiate_node(Gra
 {
     std::unique_ptr<arm_compute::IFunction> func;
     _target_hint = ctx.hints().target_hint();
-    _input       = input;
-    _output      = output;
 
     if(_target_hint == TargetHint::OPENCL)
     {
         func = instantiate<TargetHint::OPENCL>(input, output, _norm_info);
+        ARM_COMPUTE_LOG("Instantiating CLNormalizationLayer");
     }
     else
     {
         func = instantiate<TargetHint::NEON>(input, output, _norm_info);
+        ARM_COMPUTE_LOG("Instantiating NENormalizationLayer");
     }
 
-    return func;
-}
+    ARM_COMPUTE_LOG(" Data Type: " << input->info()->data_type()
+                    << " Input shape: " << input->info()->tensor_shape()
+                    << " Output shape: " << output->info()->tensor_shape()
+                    << " Normalization info: " << _norm_info
+                    << std::endl);
 
-void NormalizationLayer::print_info()
-{
-    if(_target_hint == TargetHint::OPENCL)
-    {
-        std::cout << "Instantiating CLNormalizationLayer";
-    }
-    else
-    {
-        std::cout << "Instantiating NENormalizationLayer";
-    }
-
-    std::cout << " Data Type: " << _input->info()->data_type()
-              << " Input shape: " << _input->info()->tensor_shape()
-              << " Output shape: " << _output->info()->tensor_shape()
-              << " Normalization info: " << _norm_info
-              << std::endl;
+    return func;
 }
diff --git a/src/graph/nodes/PoolingLayer.cpp b/src/graph/nodes/PoolingLayer.cpp
index 2a5e4cb3d8..317cf4d14f 100644
--- a/src/graph/nodes/PoolingLayer.cpp
+++ b/src/graph/nodes/PoolingLayer.cpp
@@ -23,6 +23,7 @@
  */
 #include "arm_compute/graph/nodes/PoolingLayer.h"
 
+#include "arm_compute/core/Logger.h"
 #include "arm_compute/runtime/CL/CLTensor.h"
 #include "arm_compute/runtime/CL/functions/CLPoolingLayer.h"
 #include "arm_compute/runtime/NEON/functions/NEPoolingLayer.h"
@@ -71,34 +72,22 @@ std::unique_ptr<arm_compute::IFunction> PoolingLayer::instantiate_node(GraphCont
 {
     std::unique_ptr<arm_compute::IFunction> func;
     _target_hint = ctx.hints().target_hint();
-    _input       = input;
-    _output      = output;
 
     if(_target_hint == TargetHint::OPENCL)
     {
         func = instantiate<TargetHint::OPENCL>(input, output, _pool_info);
+        ARM_COMPUTE_LOG("Instantiating CLPoolingLayer");
     }
     else
     {
         func = instantiate<TargetHint::NEON>(input, output, _pool_info);
+        ARM_COMPUTE_LOG("Instantiating NEPoolingLayer");
     }
 
-    return func;
-}
+    ARM_COMPUTE_LOG(" Data Type: " << input->info()->data_type()
+                    << " Input shape: " << input->info()->tensor_shape()
+                    << " Output shape: " << output->info()->tensor_shape()
+                    << " Pooling info: " << _pool_info << std::endl);
 
-void PoolingLayer::print_info()
-{
-    if(_target_hint == TargetHint::OPENCL)
-    {
-        std::cout << "Instantiating CLPoolingLayer";
-    }
-    else
-    {
-        std::cout << "Instantiating NEPoolingLayer";
-    }
-
-    std::cout << " Data Type: " << _input->info()->data_type()
-              << " Input shape: " << _input->info()->tensor_shape()
-              << " Output shape: " << _output->info()->tensor_shape()
-              << " Pooling info: " << _pool_info << std::endl;
+    return func;
 }
diff --git a/src/graph/nodes/SoftmaxLayer.cpp b/src/graph/nodes/SoftmaxLayer.cpp
index 9e798ef7cc..86282448f7 100644
--- a/src/graph/nodes/SoftmaxLayer.cpp
+++ b/src/graph/nodes/SoftmaxLayer.cpp
@@ -23,6 +23,7 @@
  */
 #include "arm_compute/graph/nodes/SoftmaxLayer.h"
 
+#include "arm_compute/core/Logger.h"
 #include "arm_compute/runtime/CL/CLTensor.h"
 #include "arm_compute/runtime/CL/functions/CLSoftmaxLayer.h"
 #include "arm_compute/runtime/NEON/functions/NESoftmaxLayer.h"
@@ -65,33 +66,22 @@ std::unique_ptr<arm_compute::IFunction> SoftmaxLayer::instantiate_node(GraphCont
 {
     std::unique_ptr<arm_compute::IFunction> func;
     _target_hint = ctx.hints().target_hint();
-    _input       = input;
-    _output      = output;
 
     if(_target_hint == TargetHint::OPENCL)
     {
         func = instantiate<TargetHint::OPENCL>(input, output);
+        ARM_COMPUTE_LOG("Instantiating CLSoftmaxLayer");
     }
     else
     {
         func = instantiate<TargetHint::NEON>(input, output);
+        ARM_COMPUTE_LOG("Instantiating NESoftmaxLayer");
     }
 
-    return func;
-}
+    ARM_COMPUTE_LOG(" Data Type: " << input->info()->data_type()
+                    << " Input shape: " << input->info()->tensor_shape()
+                    << " Output shape: " << output->info()->tensor_shape()
+                    << std::endl);
 
-void SoftmaxLayer::print_info()
-{
-    if(_target_hint == TargetHint::OPENCL)
-    {
-        std::cout << "Instantiating CLSoftmaxLayer";
-    }
-    else
-    {
-        std::cout << "Instantiating NESoftmaxLayer";
-    }
-    std::cout << " Data Type: " << _input->info()->data_type()
-              << " Input shape: " << _input->info()->tensor_shape()
-              << " Output shape: " << _output->info()->tensor_shape()
-              << std::endl;
+    return func;
 }