ops->scheme = strdup(uri);
}

void TF_InitPlugin(TF_FilesystemPluginInfo* info) {
  info->plugin_memory_allocate = plugin_memory_allocate;
  info->plugin_memory_free = plugin_memory_free;
  info->num_schemes = 2;
  info->ops = static_cast<TF_FilesystemPluginOps*>(
      plugin_memory_allocate(info->num_schemes * sizeof(info->ops[0])));
  ProvideFilesystemSupportFor(&info->ops[0], "");

See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/

#include <array>
#include <memory>
#include <string>

#include "tensorflow/c/c_api.h"
#include "tensorflow/c/c_api_experimental.h"
#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_experimental.h"

TensorHandlePtr VectorFloatTensorHandle(const std::vector<float>& v,
                                        TF_Status* status) {
  const int num_bytes = v.size() * sizeof(float);
  float* values = new float[v.size()];
  memcpy(values, v.data(), num_bytes);
  int64_t dims = v.size();
  std::unique_ptr<TF_Tensor, decltype(&TF_DeleteTensor)> tensor(
      TF_NewTensor(TF_FLOAT, &dims, 1 /* num_dims */, values, num_bytes,

  ops->read_only_memory_region_ops = static_cast<TF_ReadOnlyMemoryRegionOps*>(
      plugin_memory_allocate(TF_READ_ONLY_MEMORY_REGION_OPS_SIZE));
  ops->read_only_memory_region_ops->cleanup =
      tf_read_only_memory_region::Cleanup;
  ops->read_only_memory_region_ops->data = tf_read_only_memory_region::Data;
  ops->read_only_memory_region_ops->length = tf_read_only_memory_region::Length;

      TFE_NewContextOptions(), TFE_DeleteContextOptions);
  std::unique_ptr<TF_Buffer, decltype(&TF_DeleteBuffer)> config(
      TF_CreateConfig(
          /*xla*/ false,
          /* gpu_memory_allow_growth */ true, /* num_cpu_devices */
          2),
      TF_DeleteBuffer);
  TFE_ContextOptionsSetConfig(opts.get(), config->data, config->length,
                              status.get());

See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/
#include <memory>

#include "tensorflow/c/eager/abstract_context.h"
#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_unified_experimental.h"
#include "tensorflow/c/eager/c_api_unified_experimental_internal.h"

  ASSERT_EQ(errors::OK, s.code()) << s.message();
  auto num_elem_numerical = TF_TensorElementCount(numerical_tensor);
  ASSERT_EQ(num_elem_numerical, num_grad);

  float* dnumerical = new float[num_elem_numerical]{0};
  memcpy(&dnumerical[0], TF_TensorData(numerical_tensor),
         TF_TensorByteSize(numerical_tensor));

  for (int j = 0; j < num_grad; j++) {
    ASSERT_NEAR(dnumerical[j], expected_grad[j], abs_error);
  }

  EXPECT_EQ(TF_FLOAT, TFE_TensorHandleDataType(h));

  TF_Tensor* t = TFE_TensorHandleResolve(h, status.get());
  ASSERT_EQ(16, TF_TensorByteSize(t));
  float data[4] = {0};
  memcpy(&data[0], TF_TensorData(t), TF_TensorByteSize(t));
  EXPECT_EQ(1.0, data[0]);
  EXPECT_EQ(2.0, data[1]);
  EXPECT_EQ(3.0, data[2]);
  EXPECT_EQ(4.0, data[3]);
  TF_DeleteTensor(t);
  TFE_DeleteTensorHandle(h);

  ASSERT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);
  TFE_DeleteTensorHandle(retval_task0);
  float product[4] = {0};
  EXPECT_EQ(sizeof(product), TF_TensorByteSize(t));
  memcpy(&product[0], TF_TensorData(t), TF_TensorByteSize(t));
  TF_DeleteTensor(t);
  EXPECT_EQ(7, product[0]);
  EXPECT_EQ(10, product[1]);
  EXPECT_EQ(15, product[2]);
  EXPECT_EQ(22, product[3]);

    ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

    memcpy(&result_data[0], TF_TensorData(f_t), TF_TensorByteSize(f_t));

    // Verify results for each output
    for (int j = 0; j < 4; j++) {
      ASSERT_EQ(result_data[j], expected_outputs[idx][j]);
    }

    TF_DeleteTensor(f_t);
  }

  // Free memory associated with add and MatMul outputs
  for (int idx = 0; idx < 3; ++idx) {