1 files changed, 239 insertions, 0 deletions
diff --git a/contrib/convacl/src/nnapi_acl_conv.cc b/contrib/convacl/src/nnapi_acl_conv.cc
new file mode 100644
index 000000000..091d19497
--- /dev/null
+++ b/contrib/convacl/src/nnapi_acl_conv.cc
@@ -0,0 +1,239 @@
+/*
+ * Copyright (c) 2018 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.
+ */
+
+/*
+ * Copyright (c) 2018 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#include <NeuralNetworks.h>
+#include <stdexcept>
+#include <iostream>
+#include <string>
+#include <map>
+#include <cassert>
+#include <memory>
+#include <boost/format.hpp>
+// ACL Headers
+#include <arm_compute/graph.h>
+
+#include "util/environment.h"
+#include "io_accessor.h"
+
+//
+// Asynchronous Event
+//
+struct ANeuralNetworksEvent
+{
+};
+
+int ANeuralNetworksEvent_wait(ANeuralNetworksEvent* event)
+{
+  return ANEURALNETWORKS_NO_ERROR;
+}
+
+void ANeuralNetworksEvent_free(ANeuralNetworksEvent* event)
+{
+  delete event;
+}
+
+//
+// Memory
+//
+struct ANeuralNetworksMemory
+{
+  // 1st approach - Store all the data inside ANeuralNetworksMemory object
+  // 2nd approach - Store metadata only, and defer data loading as much as possible
+};
+
+int ANeuralNetworksMemory_createFromFd(size_t size, int protect, int fd, size_t offset, ANeuralNetworksMemory** memory)
+{
+  *memory = new ANeuralNetworksMemory;
+  return ANEURALNETWORKS_NO_ERROR;
+}
+
+void ANeuralNetworksMemory_free(ANeuralNetworksMemory* memory)
+{
+  delete memory;
+}
+
+//
+// Model
+//
+struct ANeuralNetworksModel
+{
+  // ANeuralNetworksModel should be a factory for Graph IR (a.k.a ISA Frontend)
+  // TODO Record # of operands
+  uint32_t numOperands;
+
+  ANeuralNetworksModel() : numOperands(0)
+  {
+    // DO NOTHING
+  }
+};
+
+int ANeuralNetworksModel_create(ANeuralNetworksModel** model)
+{
+  *model = new ANeuralNetworksModel;
+  return ANEURALNETWORKS_NO_ERROR;
+}
+
+void ANeuralNetworksModel_free(ANeuralNetworksModel* model)
+{
+  delete model;
+}
+
+int ANeuralNetworksModel_addOperand(ANeuralNetworksModel* model, const ANeuralNetworksOperandType *type)
+{
+  model->numOperands += 1;
+  return ANEURALNETWORKS_NO_ERROR;
+}
+
+int ANeuralNetworksModel_setOperandValue(ANeuralNetworksModel* model, int32_t index, const void* buffer, size_t length)
+{
+  return ANEURALNETWORKS_NO_ERROR;
+}
+
+int ANeuralNetworksModel_setOperandValueFromMemory(ANeuralNetworksModel* model, int32_t index, const ANeuralNetworksMemory* memory, size_t offset, size_t length)
+{
+  return ANEURALNETWORKS_NO_ERROR;
+}
+
+int ANeuralNetworksModel_addOperation(ANeuralNetworksModel* model, ANeuralNetworksOperationType type, uint32_t inputCount, const uint32_t* inputs, uint32_t outputCount, const uint32_t* outputs)
+{
+  return ANEURALNETWORKS_NO_ERROR;
+}
+
+int ANeuralNetworksModel_identifyInputsAndOutputs(ANeuralNetworksModel* model, uint32_t inputCount, const uint32_t* inputs, uint32_t outputCount, const uint32_t* outputs)
+{
+  return ANEURALNETWORKS_NO_ERROR;
+}
+
+int ANeuralNetworksModel_finish(ANeuralNetworksModel* model)
+{
+  return ANEURALNETWORKS_NO_ERROR;
+}
+
+//
+// Compilation
+//
+struct ANeuralNetworksCompilation
+{
+  // ANeuralNetworksCompilation should hold a compiled IR
+};
+
+int ANeuralNetworksCompilation_create(ANeuralNetworksModel* model, ANeuralNetworksCompilation** compilation)
+{
+  *compilation = new ANeuralNetworksCompilation;
+  return ANEURALNETWORKS_NO_ERROR;
+}
+
+int ANeuralNetworksCompilation_finish(ANeuralNetworksCompilation* compilation)
+{
+  return ANEURALNETWORKS_NO_ERROR;
+}
+
+//
+// Execution
+//
+struct ANeuralNetworksExecution
+{
+  // ANeuralNetworksExecution corresponds to NPU::Interp::Session
+
+  arm_compute::graph::frontend::Stream graph{0, "ACL_CONV"};
+};
+
+int ANeuralNetworksExecution_create(ANeuralNetworksCompilation* compilation, ANeuralNetworksExecution** execution)
+{
+  std::cout << __FUNCTION__ << " +++" << std::endl;
+  *execution = new ANeuralNetworksExecution;
+
+  using arm_compute::DataType;
+  using arm_compute::graph::Target;
+  using arm_compute::graph::TensorDescriptor;
+  using arm_compute::TensorShape;
+  using arm_compute::graph::frontend::InputLayer;
+  using arm_compute::graph::frontend::OutputLayer;
+
+  ANeuralNetworksExecution* execlocal = *execution;
+  arm_compute::graph::frontend::Stream& graph = execlocal->graph;
+
+  Target target_hint = nnfw::util::get_env_int("NNFW_ACL_USENEON")
+                           ? Target::NEON : Target::CL;
+  bool autoinc = nnfw::util::get_env_bool("NNFW_TEST_AUTOINC");
+
+  graph << target_hint
+        << InputLayer(TensorDescriptor(TensorShape(3U, 3U, 1U, 1U), DataType::F32),
+                  std::unique_ptr<InputAccessor>(new InputAccessor(autoinc)))
+        << arm_compute::graph::frontend::ConvolutionLayer(
+              3U, 3U, 1U,
+              std::unique_ptr<WeightAccessor>(new WeightAccessor(autoinc)),
+              std::unique_ptr<BiasAccessor>(new BiasAccessor()),
+              arm_compute::PadStrideInfo(1, 1, 0, 0))
+        << OutputLayer(
+              std::unique_ptr<OutputAccessor>(new OutputAccessor()));
+
+  std::cout << __FUNCTION__ << " ---" << std::endl;
+  return ANEURALNETWORKS_NO_ERROR;
+}
+
+// ANeuralNetworksExecution_setInput and ANeuralNetworksExecution_setOutput specify HOST buffer for input/output
+int ANeuralNetworksExecution_setInput(ANeuralNetworksExecution* execution, int32_t index, const ANeuralNetworksOperandType* type, const void* buffer, size_t length)
+{
+  return ANEURALNETWORKS_NO_ERROR;
+}
+
+int ANeuralNetworksExecution_setOutput(ANeuralNetworksExecution* execution, int32_t index, const ANeuralNetworksOperandType* type, const void* buffer, size_t length)
+{
+  return ANEURALNETWORKS_NO_ERROR;
+}
+
+int ANeuralNetworksExecution_startCompute(ANeuralNetworksExecution* execution, ANeuralNetworksEvent** event)
+{
+  std::cout << __FUNCTION__ << " +++" << std::endl;
+  *event = new ANeuralNetworksEvent;
+
+  // graph.run() fails with segment fail when only target_hint is added.
+  // after fix adding 'Tensor' we may call graph.run()
+  arm_compute::graph::frontend::Stream& graph = execution->graph;
+  graph.run();
+
+  std::cout << __FUNCTION__ << " ---" << std::endl;
+  return ANEURALNETWORKS_NO_ERROR;
+}
+
+void ANeuralNetworksExecution_free(ANeuralNetworksExecution* execution)
+{
+  delete execution;
+}