/* Copyright 2015 Google Inc. 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.
==============================================================================*/

#ifndef TENSORFLOW_FRAMEWORK_TENSOR_TESTUTIL_H_
#define TENSORFLOW_FRAMEWORK_TENSOR_TESTUTIL_H_

#include <gtest/gtest.h>
#include "tensorflow/core/lib/gtl/array_slice.h"
#include "tensorflow/core/platform/logging.h"
#include "tensorflow/core/public/tensor.h"

namespace tensorflow {
namespace test {

// Constructs a scalar tensor with 'val'.
template <typename T>
Tensor AsScalar(const T& val) {
  Tensor ret(DataTypeToEnum<T>::value, {});
  ret.scalar<T>()() = val;
  return ret;
}

// Constructs a flat tensor with 'vals'.
template <typename T>
Tensor AsTensor(gtl::ArraySlice<T> vals) {
  Tensor ret(DataTypeToEnum<T>::value, {static_cast<int64>(vals.size())});
  std::copy_n(vals.data(), vals.size(), ret.flat<T>().data());
  return ret;
}

// Constructs a tensor of "shape" with values "vals".
template <typename T>
Tensor AsTensor(gtl::ArraySlice<T> vals, const TensorShape& shape) {
  Tensor ret;
  CHECK(ret.CopyFrom(AsTensor(vals), shape));
  return ret;
}

// Fills in '*tensor' with 'vals'. E.g.,
//   Tensor x(&alloc, DT_FLOAT, TensorShape({2, 2}));
//   test::FillValues<float>(&x, {11, 21, 21, 22});
template <typename T>
void FillValues(Tensor* tensor, gtl::ArraySlice<T> vals) {
  auto flat = tensor->flat<T>();
  CHECK_EQ(flat.size(), vals.size());
  if (flat.size() > 0) {
    std::copy_n(vals.data(), vals.size(), flat.data());
  }
}

// Fills in '*tensor' with a sequence of value of val, val+1, val+2, ...
//   Tensor x(&alloc, DT_FLOAT, TensorShape({2, 2}));
//   test::FillIota<float>(&x, 1.0);
template <typename T>
void FillIota(Tensor* tensor, const T& val) {
  auto flat = tensor->flat<T>();
  std::iota(flat.data(), flat.data() + flat.size(), val);
}

// Fills in '*tensor' with a sequence of value of fn(0), fn(1), ...
//   Tensor x(&alloc, DT_FLOAT, TensorShape({2, 2}));
//   test::FillFn<float>(&x, [](int i)->float { return i*i; });
template <typename T>
void FillFn(Tensor* tensor, std::function<T(int)> fn) {
  auto flat = tensor->flat<T>();
  for (int i = 0; i < flat.size(); ++i) flat(i) = fn(i);
}

// Expects "x" and "y" are tensors of the same type, same shape, and
// identical values.
template <typename T>
void ExpectTensorEqual(const Tensor& x, const Tensor& y);

// Expects "x" and "y" are tensors of the same type, same shape, and
// approxmiate equal values, each within "abs_err".
template <typename T>
void ExpectTensorNear(const Tensor& x, const Tensor& y, const T& abs_err);

// Expects "x" and "y" are tensors of the same type (float or double),
// same shape and element-wise difference between x and y is no more
// than atol + rtol * abs(x).
void ExpectClose(const Tensor& x, const Tensor& y, double atol = 1e-6,
                 double rtol = 1e-6);

// Implementation details.

namespace internal {

template <typename T>
struct is_floating_point_type {
  static const bool value = std::is_same<T, float>::value ||
                            std::is_same<T, double>::value ||
                            std::is_same<T, std::complex<float> >::value ||
                            std::is_same<T, std::complex<double> >::value;
};

template <typename T>
static void ExpectEqual(const T& a, const T& b) {
  EXPECT_EQ(a, b);
}

template <>
void ExpectEqual<float>(const float& a, const float& b) {
  EXPECT_FLOAT_EQ(a, b);
}

template <>
void ExpectEqual<double>(const double& a, const double& b) {
  EXPECT_DOUBLE_EQ(a, b);
}

template <>
void ExpectEqual<complex64>(const complex64& a, const complex64& b) {
  EXPECT_FLOAT_EQ(a.real(), b.real()) << a << " vs. " << b;
  EXPECT_FLOAT_EQ(a.imag(), b.imag()) << a << " vs. " << b;
}

inline void AssertSameTypeDims(const Tensor& x, const Tensor& y) {
  ASSERT_EQ(x.dtype(), y.dtype());
  ASSERT_TRUE(x.IsSameSize(y))
      << "x.shape [" << x.shape().DebugString() << "] vs "
      << "y.shape [ " << y.shape().DebugString() << "]";
}

template <typename T, bool is_fp = is_floating_point_type<T>::value>
struct Expector;

template <typename T>
struct Expector<T, false> {
  static void Equal(const T& a, const T& b) { ExpectEqual(a, b); }

  static void Equal(const Tensor& x, const Tensor& y) {
    ASSERT_EQ(x.dtype(), DataTypeToEnum<T>::v());
    AssertSameTypeDims(x, y);
    auto a = x.flat<T>();
    auto b = y.flat<T>();
    for (int i = 0; i < a.size(); ++i) {
      ExpectEqual(a(i), b(i));
    }
  }
};

// Partial specialization for float and double.
template <typename T>
struct Expector<T, true> {
  static void Equal(const T& a, const T& b) { ExpectEqual(a, b); }

  static void Equal(const Tensor& x, const Tensor& y) {
    ASSERT_EQ(x.dtype(), DataTypeToEnum<T>::v());
    AssertSameTypeDims(x, y);
    auto a = x.flat<T>();
    auto b = y.flat<T>();
    for (int i = 0; i < a.size(); ++i) {
      ExpectEqual(a(i), b(i));
    }
  }

  static void Near(const T& a, const T& b, const double abs_err) {
    if (a != b) {  // Takes care of inf.
      EXPECT_LE(std::abs(a - b), abs_err) << "a = " << a << " b = " << b;
    }
  }

  static void Near(const Tensor& x, const Tensor& y, const double abs_err) {
    ASSERT_EQ(x.dtype(), DataTypeToEnum<T>::v());
    AssertSameTypeDims(x, y);
    auto a = x.flat<T>();
    auto b = y.flat<T>();
    for (int i = 0; i < a.size(); ++i) {
      Near(a(i), b(i), abs_err);
    }
  }
};

}  // namespace internal

template <typename T>
void ExpectTensorEqual(const Tensor& x, const Tensor& y) {
  internal::Expector<T>::Equal(x, y);
}

template <typename T>
void ExpectTensorNear(const Tensor& x, const Tensor& y, const double abs_err) {
  static_assert(internal::is_floating_point_type<T>::value,
                "T is not a floating point types.");
  internal::Expector<T>::Near(x, y, abs_err);
}

}  // namespace test
}  // namespace tensorflow

#endif  // TENSORFLOW_FRAMEWORK_TENSOR_TESTUTIL_H_
