1 files changed, 135 insertions, 0 deletions
diff --git a/compiler/tflchef/core/src/Data/Gaussian.cpp b/compiler/tflchef/core/src/Data/Gaussian.cpp
new file mode 100644
index 000000000..c515d1104
--- /dev/null
+++ b/compiler/tflchef/core/src/Data/Gaussian.cpp
@@ -0,0 +1,135 @@
+/*
+ * 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.
+ */
+
+#include "Gaussian.h"
+#include "LexicalCast.h"
+
+#include <random>
+#include <chrono>
+
+#include <cassert>
+#include <stdexcept>
+
+std::vector<uint8_t> GaussianFloat32DataChef::generate(int32_t count) const
+{
+  // TODO Support seed value override
+  int seed = std::chrono::system_clock::now().time_since_epoch().count();
+
+  std::minstd_rand rand{seed};
+  std::normal_distribution<float> dist{_mean, _stddev};
+
+  std::vector<uint8_t> res;
+
+  for (uint32_t n = 0; n < count; ++n)
+  {
+    auto const value = dist(rand);
+    auto const arr = reinterpret_cast<const uint8_t *>(&value);
+
+    for (uint32_t b = 0; b < sizeof(float); ++b)
+    {
+      res.emplace_back(arr[b]);
+    }
+  }
+
+  return res;
+}
+
+std::vector<uint8_t> GaussianInt32DataChef::generate(int32_t count) const
+{
+  // TODO Support seed value override
+  int seed = std::chrono::system_clock::now().time_since_epoch().count();
+
+  std::minstd_rand rand{seed};
+  std::normal_distribution<float> dist{_mean, _stddev};
+
+  std::vector<uint8_t> res;
+
+  for (uint32_t n = 0; n < count; ++n)
+  {
+    auto const value = static_cast<int32_t>(dist(rand));
+    auto const arr = reinterpret_cast<const uint8_t *>(&value);
+
+    for (uint32_t b = 0; b < sizeof(int32_t); ++b)
+    {
+      res.emplace_back(arr[b]);
+    }
+  }
+
+  return res;
+}
+
+std::vector<uint8_t> GaussianUint8DataChef::generate(int32_t count) const
+{
+  // TODO Support seed value override
+  int seed = std::chrono::system_clock::now().time_since_epoch().count();
+
+  std::minstd_rand rand{seed};
+  std::normal_distribution<float> dist{_mean, _stddev};
+
+  std::vector<uint8_t> res;
+
+  for (uint32_t n = 0; n < count; ++n)
+  {
+    auto const value = static_cast<uint8_t>(dist(rand));        // uint8_t for data type
+    auto const arr = reinterpret_cast<const uint8_t *>(&value); // uint8_t for byte streaming
+
+    for (uint32_t b = 0; b < sizeof(uint8_t); ++b)
+    {
+      res.emplace_back(arr[b]);
+    }
+  }
+
+  return res;
+}
+
+std::unique_ptr<DataChef> GaussianFloat32DataChefFactory::create(const Arguments &args) const
+{
+  if (args.count() != 2)
+  {
+    throw std::runtime_error{"invalid argument count: two arguments (mean/stddev) are expected"};
+  }
+
+  auto const mean = to_number<float>(args.value(0));
+  auto const stddev = to_number<float>(args.value(1));
+
+  return std::unique_ptr<DataChef>{new GaussianFloat32DataChef{mean, stddev}};
+}
+
+std::unique_ptr<DataChef> GaussianInt32DataChefFactory::create(const Arguments &args) const
+{
+  if (args.count() != 2)
+  {
+    throw std::runtime_error{"invalid argument count: two arguments (mean/stddev) are expected"};
+  }
+
+  auto const mean = to_number<float>(args.value(0));
+  auto const stddev = to_number<float>(args.value(1));
+
+  return std::unique_ptr<DataChef>{new GaussianInt32DataChef{mean, stddev}};
+}
+
+std::unique_ptr<DataChef> GaussianUint8DataChefFactory::create(const Arguments &args) const
+{
+  if (args.count() != 2)
+  {
+    throw std::runtime_error{"invalid argument count: two arguments (mean/stddev) are expected"};
+  }
+
+  auto const mean = to_number<float>(args.value(0));
+  auto const stddev = to_number<float>(args.value(1));
+
+  return std::unique_ptr<DataChef>{new GaussianUint8DataChef{mean, stddev}};
+}