build --action_env PYTHON_BIN_PATH="/usr/local/bin/python3"
build --python_path="/usr/local/bin/python3"

# Build TensorFlow v2
build --define=tf_api_version=2 --action_env=TF2_BEHAVIOR=1

# Prevent double-compilation of some TF code, ref. b/183279666 (internal)
# > TF's gen_api_init_files has a genrule to run the core TensorFlow code
# > on the host machine. If we don't have --distinct_host_configuration=false,

  TF_DeleteStatus(s);
}

TEST(CAPI, DataTypeEnum) {
  EXPECT_EQ(TF_FLOAT, static_cast<TF_DataType>(tensorflow::DT_FLOAT));
  EXPECT_EQ(TF_DOUBLE, static_cast<TF_DataType>(tensorflow::DT_DOUBLE));
  EXPECT_EQ(TF_INT32, static_cast<TF_DataType>(tensorflow::DT_INT32));
  EXPECT_EQ(TF_UINT8, static_cast<TF_DataType>(tensorflow::DT_UINT8));

  return StatusFromTF_Status(plugin_status.get());
}

Status ModularFileSystem::SetOption(const std::string& name,
                                    const std::vector<double>& values) {
  if (ops_->set_filesystem_configuration == nullptr) {
    return errors::Unimplemented(
        "Filesystem does not support SetConfiguration()");
  }
  if (values.empty()) {

index fcf956a..e2c5d29 100644
--- a/sysdeps/ieee754/dbl-64/k_rem_pio2.c
+++ b/sysdeps/ieee754/dbl-64/k_rem_pio2.c
@@ -172,7 +172,8 @@ int __kernel_rem_pio2(double *x, double *y, int e0, int nx, int prec, const int3
 
     /* compute q[0],q[1],...q[jk] */
 	for (i=0;i<=jk;i++) {
-	    for(j=0,fw=0.0;j<=jx;j++) fw += x[j]*f[jx+i-j]; q[i] = fw;

namespace gradients {
namespace internal {

void CompareNumericalAndAutodiffGradients(
    Model model, Model grad_model, AbstractContext* ctx,
    absl::Span<AbstractTensorHandle* const> inputs, bool use_function,
    double abs_error) {
  auto num_inputs = inputs.size();
  std::vector<AbstractTensorHandle*> outputs(num_inputs);
  auto s = RunModel(grad_model, ctx, inputs, absl::MakeSpan(outputs),
                    /*use_function=*/use_function);

  switch (data_type) {
    case TF_DataType::TF_BOOL:
      dtype.code = DLDataTypeCode::kDLBool;
      break;
    case TF_DataType::TF_HALF:
    case TF_DataType::TF_FLOAT:
    case TF_DataType::TF_DOUBLE:
      dtype.code = DLDataTypeCode::kDLFloat;
      break;
    case TF_DataType::TF_INT8:
    case TF_DataType::TF_INT16:
    case TF_DataType::TF_INT32:
    case TF_DataType::TF_INT64:

TEST_P(UnifiedCAPI, TestBasicGraph) {
  std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status(
      TF_NewStatus(), TF_DeleteStatus);

  // Start a new function / execution context.
  string fn_name = "double";
  TF_ExecutionContext* graph_ctx =
      TF_CreateFunction(fn_name.c_str(), status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());

  auto* placeholder_t =

# Build TensorFlow v2
build --define=tf_api_version=2 --action_env=TF2_BEHAVIOR=1

# Use lld as the linker
build --linkopt="-fuse-ld=lld"
build --linkopt="-lm"
build --linkopt="-Wl,--undefined-version"

# Prevent double-compilation of some TF code, ref. b/183279666 (internal)
# > TF's gen_api_init_files has a genrule to run the core TensorFlow code
# > on the host machine. If we don't have --distinct_host_configuration=false,

  TF_DeleteStatus(status);
  return th;
}

TFE_TensorHandle* DoubleTestMatrixTensorHandle(TFE_Context* ctx) {
  int64_t dims[] = {2, 2};
  double data[] = {1.0, 2.0, 3.0, 4.0};
  TF_Status* status = TF_NewStatus();
  TF_Tensor* t = TFE_AllocateHostTensor(ctx, TF_DOUBLE, &dims[0],
                                        sizeof(dims) / sizeof(int64_t), status);
  memcpy(TF_TensorData(t), &data[0], TF_TensorByteSize(t));

void CompareNumericalAndManualGradients(
    Model model, AbstractContext* ctx,
    absl::Span<AbstractTensorHandle* const> inputs, int input_index,
    float* expected_grad, int num_grad, bool use_function,
    double abs_error = 1e-2) {
  Status s;
  AbstractTensorHandlePtr numerical_grad;
  {
    AbstractTensorHandle* numerical_grad_raw;
    s = CalcNumericalGrad(ctx, model, inputs, input_index, use_function,