1 files changed, 91 insertions, 0 deletions
diff --git a/compute/ARMComputeEx/src/runtime/NEON/functions/NEFullyConnectedReshapingLayer.cpp b/compute/ARMComputeEx/src/runtime/NEON/functions/NEFullyConnectedReshapingLayer.cpp
new file mode 100644
index 000000000..fcac3c7ae
--- /dev/null
+++ b/compute/ARMComputeEx/src/runtime/NEON/functions/NEFullyConnectedReshapingLayer.cpp
@@ -0,0 +1,91 @@
+/*
+ * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "arm_compute/runtime/NEON/functions/NEFullyConnectedReshapingLayer.h"
+
+#include <arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h>
+#include <arm_compute/runtime/NEON/functions/NEFullyConnectedHybridLayer.h>
+#include <arm_compute/runtime/NEON/functions/NEFullyConnectedLayerEx.h>
+
+using namespace arm_compute;
+
+void NEFullyConnectedReshapingLayer::configure(const arm_compute::ITensor *input,
+                                               const arm_compute::ITensor *weights,
+                                               const arm_compute::ITensor *biases,
+                                               arm_compute::ITensor *output, bool needs_reshape,
+                                               const arm_compute::TensorShape &reshape,
+                                               KernelType kernel_type)
+{
+  _input = input;
+  _weights = weights;
+  _biases = biases;
+  _output = output;
+  _needs_reshape = needs_reshape;
+
+  const ITensor *input_to_use = input;
+  if (_needs_reshape)
+  {
+    // reshape
+    auto_init_if_empty(*_neon_buffer.info(), _input->info()->clone()->set_tensor_shape(reshape));
+    _neon_reshape.configure(_input, &_neon_buffer);
+    input_to_use = &_neon_buffer;
+  }
+
+  _neon_fc = [&]() {
+    if (kernel_type == KernelType::GENERAL)
+    {
+      auto fc = new arm_compute::NEFullyConnectedLayerEx{_memory_manager};
+      fc->configure(input_to_use, _weights, _biases, _output);
+      return std::unique_ptr<arm_compute::IFunction>(fc);
+    }
+    else
+    {
+      assert(kernel_type == KernelType::PREPROCESSED_WEIGHTS);
+
+      bool is_hybrid = input->info()->data_type() == DataType::F32 &&
+                       weights->info()->data_type() == DataType::S8;
+
+      if (is_hybrid)
+      {
+        auto fc = new arm_compute::NEFullyConnectedHybridLayer{_memory_manager};
+        fc->configure(input_to_use, _weights, _biases, _output);
+        return std::unique_ptr<arm_compute::IFunction>(fc);
+      }
+      else
+      {
+        auto fc = new arm_compute::NEFullyConnectedLayer{_memory_manager};
+        fc->configure(input_to_use, _weights, _biases, _output);
+        return std::unique_ptr<arm_compute::IFunction>(fc);
+      }
+    }
+  }();
+
+  // NOTE _neon_buffer is inaccessible from outside, and thus it is safe to invoke allocate here.
+  if (_needs_reshape)
+  {
+    _neon_buffer.allocator()->allocate();
+  }
+}
+
+void NEFullyConnectedReshapingLayer::run(void)
+{
+  if (_needs_reshape)
+    _neon_reshape.run();
+
+  _neon_fc->run();
+}
+
+void NEFullyConnectedReshapingLayer::prepare(void) { _neon_fc->prepare(); }