[FullyConnected] Added NHWC support for FC_Layer inference part.

This also contains the unit tests to evaluate.

**Self evaluation:**
    1. Build test:   [X]Passed [ ]Failed [ ]Skipped
    2. Run test:     [X]Passed [ ]Failed [ ]Skipped

Signed-off-by: Adwaith Anand <adwaith.a@samsung.com>

diff --git a/nntrainer/layers/fc_layer.cpp b/nntrainer/layers/fc_layer.cpp
index 3b7cdeb..afe228e 100644 (file)
--- a/nntrainer/layers/fc_layer.cpp
+++ b/nntrainer/layers/fc_layer.cpp
@@ -66,17 +66,22 @@ void FullyConnectedLayer::finalize(InitLayerContext &context) {
   context.setEffDimFlagInputDimension(0, 0b1001);
   context.setDynDimFlagInputDimension(0, 0b1000);
 
+  bool is_nchw = (getTensorType() == Tformat::NCHW) ? true : false;
   /** set output dimensions */
   auto const &in_dim = context.getInputDimensions()[0];
   output_dims[0] = in_dim;
-  output_dims[0].width(unit);
+  is_nchw ? output_dims[0].width(unit) : output_dims[0].channel(unit);
   context.setOutputDimensions(output_dims);
 
   /** set weight specifications */
   // @todo : This NCHW format setting is just temporal, it needs to be set by
   // global configuration
-  TensorDim bias_dim(1, 1, 1, unit, getTensorType(), 0b0001);
-  TensorDim weight_dim(1, 1, in_dim.width(), unit, getTensorType(), 0b0011);
+
+  TensorDim bias_dim(1, is_nchw ? 1 : unit, 1, is_nchw ? unit : 1,
+                     getTensorType(), is_nchw ? 0b0001 : 0b0100);
+  TensorDim weight_dim(1, is_nchw ? 1 : unit, is_nchw ? in_dim.width() : 1,
+                       is_nchw ? unit : in_dim.channel(), getTensorType(),
+                       is_nchw ? 0b0011 : 0b0101);
 
   weight_idx[FCParams::weight] = context.requestWeight(
     weight_dim, weight_initializer, weight_regularizer,

diff --git a/nntrainer/layers/layer_devel.h b/nntrainer/layers/layer_devel.h
index 23cf09f..98b1206 100644 (file)
--- a/nntrainer/layers/layer_devel.h
+++ b/nntrainer/layers/layer_devel.h
@@ -255,11 +255,9 @@ public:
    * @param     Tensor Type : NCHW or NHWC
    */
   void setTensorType(const std::string &values) {
-    if (values.compare("NCHW") || values.compare("nchw")) {
-      tensor_type = ml::train::TensorDim::Format::NCHW;
-    } else {
-      tensor_type = ml::train::TensorDim::Format::NHWC;
-    }
+    tensor_type = (values.compare("NCHW") == 0 || values.compare("nchw") == 0)
+                    ? ml::train::TensorDim::Format::NCHW
+                    : ml::train::TensorDim::Format::NHWC;
   }
 
   /**

diff --git a/nntrainer/layers/layer_node.cpp b/nntrainer/layers/layer_node.cpp
index 4bee254..d489e1e 100644 (file)
--- a/nntrainer/layers/layer_node.cpp
+++ b/nntrainer/layers/layer_node.cpp
@@ -249,9 +249,10 @@ void LayerNode::setOutputConnection(unsigned nth, const std::string &name,
 }
 
 void LayerNode::setTensorType(const std::string &type_) {
-  TensorDim::Format type = (type_.compare("NCHW") || type_.compare("nchw"))
-                             ? TensorDim::Format::NCHW
-                             : TensorDim::Format::NHWC;
+  TensorDim::Format type =
+    (type_.compare("NCHW") == 0 || type_.compare("nchw") == 0)
+      ? TensorDim::Format::NCHW
+      : TensorDim::Format::NHWC;
   getLayer()->setTensorType(type);
 }
 

diff --git a/test/unittest/layers/layers_golden_tests.cpp b/test/unittest/layers/layers_golden_tests.cpp
index 8189468..a320e64 100644 (file)
--- a/test/unittest/layers/layers_golden_tests.cpp
+++ b/test/unittest/layers/layers_golden_tests.cpp
@@ -50,6 +50,10 @@ static InitLayerContext createInitContext(Layer *layer,
   std::vector<shape_parser_> parsed;
   from_string(input_shape_str, parsed);
 
+  for (auto &p : parsed) {
+    p.get().setFormat(layer->getTensorType());
+  }
+
   InitLayerContext context({parsed.begin(), parsed.end()}, {true}, false,
                            "golden_test");
   layer->finalize(context);

diff --git a/test/unittest/layers/unittest_layers_fully_connected.cpp b/test/unittest/layers/unittest_layers_fully_connected.cpp
index c25168a..adace85 100644 (file)
--- a/test/unittest/layers/unittest_layers_fully_connected.cpp
+++ b/test/unittest/layers/unittest_layers_fully_connected.cpp
@@ -38,6 +38,30 @@ auto fc_basic_no_decay = LayerGoldenTestParamType(
   {"unit=5", "weight_decay=0.0", "bias_decay=0.0"}, "3:1:1:10",
   "fc_plain.nnlayergolden", LayerGoldenTestParamOptions::DEFAULT, "nchw");
 
+auto fc_basic_plain_nhwc = LayerGoldenTestParamType(
+  nntrainer::createLayer<nntrainer::FullyConnectedLayer>, {"unit=5"},
+  "3:10:1:1", "fc_plain.nnlayergolden",
+  LayerGoldenTestParamOptions::SKIP_CALC_DERIV |
+    LayerGoldenTestParamOptions::SKIP_CALC_GRAD,
+  "nhwc");
+
+auto fc_basic_single_batch_nhwc = LayerGoldenTestParamType(
+  nntrainer::createLayer<nntrainer::FullyConnectedLayer>, {"unit=4"},
+  "1:10:1:1", "fc_single_batch.nnlayergolden",
+  LayerGoldenTestParamOptions::SKIP_CALC_DERIV |
+    LayerGoldenTestParamOptions::SKIP_CALC_GRAD,
+  "nhwc");
+
+auto fc_basic_no_decay_nhwc = LayerGoldenTestParamType(
+  nntrainer::createLayer<nntrainer::FullyConnectedLayer>,
+  {"unit=5", "weight_decay=0.0", "bias_decay=0.0"}, "3:10:1:1",
+  "fc_plain.nnlayergolden",
+  LayerGoldenTestParamOptions::SKIP_CALC_DERIV |
+    LayerGoldenTestParamOptions::SKIP_CALC_GRAD,
+  "nhwc");
+
 GTEST_PARAMETER_TEST(FullyConnected, LayerGoldenTest,
                      ::testing::Values(fc_basic_plain, fc_basic_single_batch,
-                                       fc_basic_no_decay));
+                                       fc_basic_no_decay, fc_basic_plain_nhwc,
+                                       fc_basic_single_batch_nhwc,
+                                       fc_basic_no_decay_nhwc));