*    dA =  U
     *    dB = -U
     *
     */

    // Grad for A
    DCHECK(grad_outputs[0]);
    grad_inputs[0] = grad_outputs[0];
    grad_inputs[0]->Ref();

    // Grad for B
    // negate the upstream grad
    std::string name = "Neg_Sub_Grad_B";
    TF_RETURN_IF_ERROR(
        ops::Neg(ctx, grad_outputs[0], &grad_inputs[1], name.c_str()));

    return absl::OkStatus();
  }

  Run({{func_feed, Int32Tensor(3)}}, func_op, -3);
  VerifyFDef({"neg"}, {{"feed", DT_INT32}}, {{"negated_num", DT_INT32}},
             {{"feed", "neg:0"}, {"neg:y:0", "negated_num"}}, {});
}

TEST_F(CApiFunctionTest, OutputNames_SameNameAsInput) {
  /*
   *                   |
   *                   v
   *                 negate
   *                   |
   *                   v
   */
  // Define

// Monitoring Counter APIs.
// These APIs de-templated monitoring Counter for swig.

typedef struct TFE_MonitoringCounterCell TFE_MonitoringCounterCell;

// Atomically increments the value of the cell. The value must be non-negative.
TF_CAPI_EXPORT extern void TFE_MonitoringCounterCellIncrementBy(
    TFE_MonitoringCounterCell* cell, int64_t value);

// Retrieves the current value of the cell.

    *   Update `Fingerprint64Map` to use aliases
    *   Add legacy string flat hash map op kernels.
    *   Add support for `add_metric` in the graph function mode.
    *   Updating cosine similarity loss - removed the negate sign from cosine
        similarity.
    *   Changed default for gradient accumulation for TPU embeddings to true.
    *   Adds summary trace API for collecting graph and profile information.

/// tied with TensorFlow releases and should have their own versioning metadata
/// in addition with the data discussed in this section. Each plugin author can
/// use a custom scheme, but it should only relate to changes in plugin code.
/// This section only touches metadata related to the versioning of this
/// interface that is shared by all possible plugins.
///

  TF_ShapeAndType& shape = shape_list->items[index];
  DCHECK(shape.dims == nullptr) << "Shape at " << index << " is already set!";
  DCHECK(num_dims >= 0) << "Number of dimensions cannot be negative!";
  shape.num_dims = num_dims;
  shape.dims = new int64_t[num_dims];
  memcpy(shape.dims, dims, sizeof(int64_t) * num_dims);
}

void TF_ShapeAndTypeListSetUnknownShape(TF_ShapeAndTypeList* shape_list,

  ASSERT_EQ(TF_GetCode(status.get()), TF_OK) << TF_Message(status.get());

  TensorHandlePtr negative_one_cpu(FloatTensorHandle(3., status.get()));
  ASSERT_EQ(TF_GetCode(status.get()), TF_OK) << TF_Message(status.get());
  components[0] = negative_one_cpu.get();
  components[1] = negative_one_cpu.get();
  TensorHandlePtr first_negative_one = CreatePerDeviceValues(
      context.get(), components, first_device_name, status.get());