==============================================================================*/
#include "tensorflow/c/experimental/gradients/nn_grad.h"

#include "tensorflow/c/eager/c_api_test_util.h"
#include "tensorflow/c/eager/unified_api_testutil.h"
#include "tensorflow/c/experimental/gradients/grad_test_helper.h"
#include "tensorflow/c/experimental/gradients/tape/tape_context.h"
#include "tensorflow/c/experimental/ops/nn_ops.h"
#include "tensorflow/c/tf_status_helper.h"

      .SetShapeFn(tensorflow::shape_inference::UnknownShape)
ATTR_TEST_REGISTER_OP(string);
ATTR_TEST_REGISTER_OP(int);
ATTR_TEST_REGISTER_OP(float);
ATTR_TEST_REGISTER_OP(bool);
ATTR_TEST_REGISTER_OP(type);
ATTR_TEST_REGISTER_OP(shape);
ATTR_TEST_REGISTER_OP(tensor);
#undef ATTR_TEST_REGISTER_OP

class CApiAttributesTest : public ::testing::Test {
 protected:
  CApiAttributesTest()

// A create function. This will never actually get called in this test, it's
// just nice to know that it compiles.
void* create(TF_OpKernelConstruction* ctx) {
  TF_DataType type;
  TF_Status* s = TF_NewStatus();
  TF_OpKernelConstruction_GetAttrType(ctx, "foobar", &type, s);
  TF_DeleteStatus(s);
  return NULL;
}

// A compute function. This will never actually get called in this test, it's
// just nice to know that it compiles.

#include "tensorflow/c/experimental/gradients/array_grad.h"

#include "tensorflow/c/eager/c_api_test_util.h"
#include "tensorflow/c/eager/c_api_unified_experimental_internal.h"
#include "tensorflow/c/eager/unified_api_testutil.h"
#include "tensorflow/c/experimental/gradients/grad_test_helper.h"
#include "tensorflow/c/experimental/gradients/tape/tape_context.h"
#include "tensorflow/c/experimental/ops/array_ops.h"

  ASSERT_EQ(errors::OK, s.code()) << s.message();
}

TEST_P(UnifiedAPI, TestUnknownShapeTracing) {
  if (!UseFunction()) {
    GTEST_SKIP() << "Tracing only test.";
  }
  if (UseMlir()) {
    // TODO(b/173074167): Remove this.
    GTEST_SKIP() << "MlirTensor::Shape is not implemented yet.";
  }
  AbstractContextPtr ctx(BuildFunction("test_fn"));
  AbstractTensorHandlePtr x;
  {

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

#include "tensorflow/c/eager/c_api_test_util.h"

#include <memory>
#include <string>
#include <vector>

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

    [height, width, depth])`, and `tf.random_crop` works for any rank (not just
    3-D images). The C++ `RandomCrop` op has been replaced with pure Python.
*   Renamed `tf.test.GetTempDir` and `tf.test.IsBuiltWithCuda` to
    `tf.test.get_temp_dir` and `tf.test.is_built_with_cuda` for PEP-8
    compatibility.
*   `parse_example`'s interface has changed, the old interface is accessible in

#include "tensorflow/c/eager/unified_api_testutil.h"
#include "tensorflow/c/experimental/ops/math_ops.h"
#include "tensorflow/c/tf_status_helper.h"
#include "tensorflow/core/platform/errors.h"
#include "tensorflow/core/platform/test.h"

namespace tensorflow {
namespace gradients {
namespace internal {
namespace {
using std::vector;

class CustomGradientTest
    : public ::testing::TestWithParam<std::tuple<const char*, bool, bool>> {

==============================================================================*/
#include "tensorflow/c/experimental/gradients/grad_test_helper.h"

#include "tensorflow/c/eager/gradient_checker.h"
#include "tensorflow/c/experimental/gradients/tape/tape_context.h"
#include "tensorflow/core/platform/test.h"

namespace tensorflow {
namespace gradients {
namespace internal {

void CompareNumericalAndAutodiffGradients(

# CPU PYCPP:
test:linux_cpu_pycpp_test_filters --test_tag_filters=-no_oss,-oss_excluded,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only
test:linux_cpu_pycpp_test_filters --build_tag_filters=-no_oss,-oss_excluded,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only
test:linux_cpu_pycpp_test_filters --test_lang_filters=cc,py --test_size_filters=small,medium