text: /* Copyright 2016 The TensorFlow Authors. 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 <complex>
  #include <string>
  
  #include "tensorflow/core/framework/fake_input.h"
  #include "tensorflow/core/framework/node_def_builder.h"
  #include "tensorflow/core/framework/tensor.h"
  #include "tensorflow/core/framework/tensor_shape.h"
  #include "tensorflow/core/framework/types.h"
  #include "tensorflow/core/framework/types.pb.h"
  #include "tensorflow/core/kernels/ops_testutil.h"
  #include "tensorflow/core/lib/core/status.h"
  #include "tensorflow/core/lib/io/path.h"
  #include "tensorflow/core/platform/env.h"
  #include "tensorflow/core/platform/test.h"
  #include "tensorflow/core/platform/types.h"
  #include "tensorflow/core/util/tensor_bundle/tensor_bundle.h"
  
  namespace tensorflow {
  namespace {
  
  class SaveV2OpTest : public OpsTestBase {
   protected:
    void MakeOp() {
      TF_ASSERT_OK(NodeDefBuilder("myop", "SaveV2")
                       .Input(FakeInput())  // prefix
                       .Input(FakeInput())  // tensor_names
                       .Input(FakeInput())  // shape_and_slices
                       .Input(FakeInput({DT_BOOL, DT_INT32, DT_FLOAT, DT_DOUBLE,
                                         DT_QINT8, DT_QINT32, DT_UINT8, DT_INT8,
                                         DT_INT16, DT_INT64, DT_COMPLEX64,
                                         DT_COMPLEX128, DT_HALF}))  // tensors
                       .Finalize(node_def()));
      TF_ASSERT_OK(InitOp());
    }
  };
  
  TEST_F(SaveV2OpTest, Simple) {
    const string prefix = io::JoinPath(testing::TmpDir(), "tensor_simple");
    const string tensornames[] = {
        "tensor_bool",  "tensor_int",    "tensor_float",     "tensor_double",
        "tensor_qint8", "tensor_qint32", "tensor_uint8",     "tensor_int8",
        "tensor_int16", "tensor_int64",  "tensor_complex64", "tensor_complex128",
        "tensor_half"};
  
    MakeOp();
    // Add a file name
    AddInput<string>(TensorShape({}),
                     [&prefix](int x) -> string { return prefix; });
  
    // Add the tensor names
    AddInput<string>(TensorShape({13}),
                     [&tensornames](int x) -> string { return tensornames[x]; });
  
    // Add the slice specs
    AddInput<string>(TensorShape({13}), [&tensornames](int x) -> string {
      return "" /* saves in full */;
    });
  
    // Add a 1-d bool tensor
    AddInput<bool>(TensorShape({2}), [](int x) -> bool { return x != 0; });
  
    // Add a 1-d integer tensor
    AddInput<int32>(TensorShape({10}), [](int x) -> int32 { return x + 1; });
  
    // Add a 2-d float tensor
    AddInput<float>(TensorShape({2, 4}),
                    [](int x) -> float { return static_cast<float>(x) / 10; });
  
    // Add a 2-d double tensor
    AddInput<double>(TensorShape({2, 4}),
                     [](int x) -> double { return static_cast<double>(x) / 20; });
  
    // Add a 2-d qint8 tensor
    AddInput<qint8>(TensorShape({3, 2}),
                    [](int x) -> qint8 { return *reinterpret_cast<qint8*>(&x); });
  
    // Add a 2-d qint32 tensor
    AddInput<qint32>(TensorShape({2, 3}), [](int x) -> qint32 {
      return *reinterpret_cast<qint32*>(&x) * qint8(2);
    });
  
    // Add a 1-d uint8 tensor
    AddInput<uint8>(TensorShape({11}), [](int x) -> uint8 { return x + 1; });
  
    // Add a 1-d int8 tensor
    AddInput<int8>(TensorShape({7}), [](int x) -> int8 { return x - 7; });
  
    // Add a 1-d int16 tensor
    AddInput<int16>(TensorShape({7}), [](int x) -> int16 { return x - 8; });
  
    // Add a 1-d int64 tensor
    AddInput<int64>(TensorShape({9}), [](int x) -> int64 { return x - 9; });
  
    // Add a 2-d complex64 tensor
    AddInput<complex64>(TensorShape({2, 3}), [](int x) -> complex64 {
      return complex64(100 + x, 200 + x);
    });
  
    // Add a 2-d complex128 tensor
    AddInput<complex128>(TensorShape({2, 3}), [](int x) -> complex128 {
      return complex128(100 + x, 200 + x);
    });
  
    // Add a 2-d half tensor
    AddInput<Eigen::half>(TensorShape({2, 4}), [](int x) -> Eigen::half {
      return static_cast<Eigen::half>(x) / Eigen::half(2);
    });
    TF_ASSERT_OK(RunOpKernel());
  
    // Check that the checkpoint file is properly written
    BundleReader reader(Env::Default(), prefix);
    TF_EXPECT_OK(reader.status());
  
    // We expect to find all saved tensors
    {
      // The 1-d bool tensor
      TensorShape shape;
      TF_EXPECT_OK(reader.LookupTensorShape("tensor_bool", &shape));
      TensorShape expected({2});
      EXPECT_TRUE(shape.IsSameSize(expected));
  
      // We expect the tensor value to be correct.
      Tensor val;
      TF_EXPECT_OK(reader.Lookup("tensor_bool", &val));
      EXPECT_EQ(DT_BOOL, val.dtype());
      for (int i = 0; i < 2; ++i) {
        EXPECT_EQ((i != 0), val.template flat<bool>()(i));
      }
    }
  
    {
      // The 1-d integer tensor
      TensorShape shape;
      TF_EXPECT_OK(reader.LookupTensorShape("tensor_int", &shape));
      TensorShape expected({10});
      EXPECT_TRUE(shape.IsSameSize(expected));
  
      // We expect the tensor value to be correct.
      Tensor val;
      TF_EXPECT_OK(reader.Lookup("tensor_int", &val));
      EXPECT_EQ(DT_INT32, val.dtype());
      for (int i = 0; i < 10; ++i) {
        EXPECT_EQ(i + 1, val.template flat<int>()(i));
      }
    }
  
    {
      // The 2-d float tensor
      TensorShape shape;
      TF_EXPECT_OK(reader.LookupTensorShape("tensor_float", &shape));
      TensorShape expected({2, 4});
      EXPECT_TRUE(shape.IsSameSize(expected));
  
      // We expect the tensor value to be correct.
      Tensor val;
      TF_EXPECT_OK(reader.Lookup("tensor_float", &val));
      EXPECT_EQ(DT_FLOAT, val.dtype());
      for (int i = 0; i < 8; ++i) {
        EXPECT_EQ(static_cast<float>(i) / 10, val.template flat<float>()(i));
      }
    }
  
    {
      // The 2-d double tensor
      TensorShape shape;
      TF_EXPECT_OK(reader.LookupTensorShape("tensor_double", &shape));
      TensorShape expected({2, 4});
      EXPECT_TRUE(shape.IsSameSize(expected));
  
      // We expect the tensor value to be correct.
      Tensor val;
      TF_EXPECT_OK(reader.Lookup("tensor_double", &val));
      EXPECT_EQ(DT_DOUBLE, val.dtype());
      for (int i = 0; i < 8; ++i) {
        EXPECT_EQ(static_cast<double>(i) / 20, val.template flat<double>()(i));
      }
    }
  
    {
      // The 2-d qint8 tensor
      TensorShape shape;
      TF_EXPECT_OK(reader.LookupTensorShape("tensor_qint8", &shape));
      TensorShape expected({3, 2});
      EXPECT_TRUE(shape.IsSameSize(expected));
  
      // We expect the tensor value to be correct.
      Tensor val;
      TF_EXPECT_OK(reader.Lookup("tensor_qint8", &val));
      EXPECT_EQ(DT_QINT8, val.dtype());
      for (int i = 0; i < 6; ++i) {
        EXPECT_EQ(*reinterpret_cast<qint8*>(&i), val.template flat<qint8>()(i));
      }
    }
  
    {
      // The 2-d qint32 tensor
      TensorShape shape;
      TF_EXPECT_OK(reader.LookupTensorShape("tensor_qint32", &shape));
      TensorShape expected({2, 3});
      EXPECT_TRUE(shape.IsSameSize(expected));
  
      // We expect the tensor value to be correct.
      Tensor val;
      TF_EXPECT_OK(reader.Lookup("tensor_qint32", &val));
      EXPECT_EQ(DT_QINT32, val.dtype());
      for (int i = 0; i < 6; ++i) {
        EXPECT_EQ(*reinterpret_cast<qint32*>(&i) * qint8(2),
                  val.template flat<qint32>()(i));
      }
    }
  
    {
      // The 1-d uint8 tensor
      TensorShape shape;
      TF_EXPECT_OK(reader.LookupTensorShape("tensor_uint8", &shape));
      TensorShape expected({11});
      EXPECT_TRUE(shape.IsSameSize(expected));
  
      // We expect the tensor value to be correct.
      Tensor val;
      TF_EXPECT_OK(reader.Lookup("tensor_uint8", &val));
      EXPECT_EQ(DT_UINT8, val.dtype());
      for (int i = 0; i < 11; ++i) {
        EXPECT_EQ(i + 1, val.template flat<uint8>()(i));
      }
    }
  
    {
      // The 1-d int8 tensor
      TensorShape shape;
      TF_EXPECT_OK(reader.LookupTensorShape("tensor_int8", &shape));
      TensorShape expected({7});
      EXPECT_TRUE(shape.IsSameSize(expected));
  
      // We expect the tensor value to be correct.
      Tensor val;
      TF_EXPECT_OK(reader.Lookup("tensor_int8", &val));
      EXPECT_EQ(DT_INT8, val.dtype());
      for (int i = 0; i < 7; ++i) {
        EXPECT_EQ(i - 7, val.template flat<int8>()(i));
      }
    }
  
    {
      // The 1-d int16 tensor
      TensorShape shape;
      TF_EXPECT_OK(reader.LookupTensorShape("tensor_int16", &shape));
      TensorShape expected({7});
      EXPECT_TRUE(shape.IsSameSize(expected));
  
      // We expect the tensor value to be correct.
      Tensor val;
      TF_EXPECT_OK(reader.Lookup("tensor_int16", &val));
      EXPECT_EQ(DT_INT16, val.dtype());
      for (int i = 0; i < 7; ++i) {
        EXPECT_EQ(i - 8, val.template flat<int16>()(i));
      }
    }
  
    {
      // The 1-d int64 tensor
      TensorShape shape;
      TF_EXPECT_OK(reader.LookupTensorShape("tensor_int64", &shape));
      TensorShape expected({9});
      EXPECT_TRUE(shape.IsSameSize(expected));
  
      // We expect the tensor value to be correct.
      Tensor val;
      TF_EXPECT_OK(reader.Lookup("tensor_int64", &val));
      EXPECT_EQ(DT_INT64, val.dtype());
      for (int i = 0; i < 9; ++i) {
        EXPECT_EQ(i - 9, val.template flat<int64>()(i));
      }
    }
  
    {
      // The 2-d complex64 tensor
      TensorShape shape;
      TF_EXPECT_OK(reader.LookupTensorShape("tensor_complex64", &shape));
      TensorShape expected({2, 3});
      EXPECT_TRUE(shape.IsSameSize(expected));
  
      // We expect the tensor value to be correct.
      Tensor val;
      TF_EXPECT_OK(reader.Lookup("tensor_complex64", &val));
      EXPECT_EQ(DT_COMPLEX64, val.dtype());
      for (int i = 0; i < 6; ++i) {
        EXPECT_EQ(100 + i, val.template flat<complex64>()(i).real());
        EXPECT_EQ(200 + i, val.template flat<complex64>()(i).imag());
      }
    }
  
    {
      // The 2-d complex128 tensor
      TensorShape shape;
      TF_EXPECT_OK(reader.LookupTensorShape("tensor_complex128", &shape));
      TensorShape expected({2, 3});
      EXPECT_TRUE(shape.IsSameSize(expected));
  
      // We expect the tensor value to be correct.
      Tensor val;
      TF_EXPECT_OK(reader.Lookup("tensor_complex128", &val));
      EXPECT_EQ(DT_COMPLEX128, val.dtype());
      for (int i = 0; i < 6; ++i) {
        EXPECT_EQ(100 + i, val.template flat<complex128>()(i).real());
        EXPECT_EQ(200 + i, val.template flat<complex128>()(i).imag());
      }
    }
    {
      // The 2-d half tensor
      TensorShape shape;
      TF_EXPECT_OK(reader.LookupTensorShape("tensor_half", &shape));
      TensorShape expected({2, 4});
      EXPECT_TRUE(shape.IsSameSize(expected));
  
      // We expect the tensor value to be correct.
      Tensor val;
      TF_EXPECT_OK(reader.Lookup("tensor_half", &val));
      EXPECT_EQ(DT_HALF, val.dtype());
      for (int i = 0; i < 8; ++i) {
        EXPECT_EQ(static_cast<Eigen::half>(i) / Eigen::half(2),
                  val.template flat<Eigen::half>()(i));
      }
    }
  }
  
  }  // namespace
  }  // namespace tensorflow
  