// Looks up the ID of a Gradient.
  int64_t TensorId(AbstractTensorHandle* tensor) const override;

  // Converts a Gradient to a TapeTensor.
  TapeTensor TapeTensorFromGradient(AbstractTensorHandle* g) const override;

  void MarkAsResult(AbstractTensorHandle* gradient) const override;

  void DeleteGradient(AbstractTensorHandle* gradient) const override;

 private:

  ASSERT_EQ(TF_INVALID_ARGUMENT, TF_GetCode(s_)) << TF_Message(s_);
}

TEST_F(CApiGradientsTest, GradientsPrefix_2ndGradientsMatchingNodeOf1st) {
  BuildGraphAndAddGradientsWithPrefixes("gradients", "gradients/MatMul");
  ASSERT_EQ(TF_INVALID_ARGUMENT, TF_GetCode(s_)) << TF_Message(s_);
}

TEST_F(CApiGradientsTest, GradientsPrefix_1stGradientsMatchingNodeOf2nd) {

        ":c_api_unified_internal",
        "//tensorflow/c/experimental/gradients/tape:tape_operation",
        "//tensorflow/core/lib/llvm_rtti",
        "//tensorflow/core/platform:errors",
    ],
)

cc_library(
    name = "gradients_internal",
    srcs = [
        "gradients.cc",
    ],
    hdrs = [
        "gradients.h",
        "gradients_internal.h",
    ],
    visibility = [

        "//tensorflow/c/eager:tfe_context_internal",
        "//tensorflow/c/eager:tfe_op_internal",
        "//tensorflow/c/eager:tfe_tensorhandle_internal",
        "//tensorflow/c/experimental/gradients",
        "//tensorflow/c/experimental/gradients/tape",
        "//tensorflow/c/experimental/next_pluggable_device:c_api",
        "//tensorflow/c/experimental/ops",
        "//tensorflow/c:c_api_experimental",

    }

    // Update g->name_map with the name_map from the scope, which will contain
    // the new gradient ops.
    for (int i = first_new_node_id; i < g->graph.num_node_ids(); ++i) {
      Node* n = g->graph.FindNodeId(i);
      if (n == nullptr) continue;

      // Adding the gradients to the graph can alter the prefix to prevent
      // name collisions only if this prefix has not been provided explicitly

    tensorflow/contrib/solvers. Initial version has lanczos bidiagonalization,
    conjugate gradients and CGLS.
*   Added gradients for `matrix_solve_ls` and `self_adjoint_eig`.
*   Large cleanup to add second order gradient for ops with C++ gradients and
    improve existing gradients such that most ops can now be differentiated
    multiple times.
*   Added a solver for ordinary differential equations,

  DefineFunction("MyGrad", &grad_func);

  // Make grad_func be a gradient of func1 and func2
  TF_GraphCopyFunction(host_graph_, func1, grad_func, s_);
  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
  TF_GraphCopyFunction(host_graph_, func2, grad_func, s_);
  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);

  // Verify that functions and their gradients are in host graph's GraphDef
  GraphDef gdef;

    justify-content: center;
    padding: 3rem 2rem;
    text-align: center;
    height: 100%;
    background: linear-gradient(180deg, #fafbfc 0%, #ffffff 100%);
}

.empty-state-icon {
    width: 80px;
    height: 80px;
    border-radius: 50%;
    background: linear-gradient(135deg, #0052cc 0%, #2684ff 100%);
    display: flex;
    align-items: center;
    justify-content: center;

}

std::vector<std::pair<string, string>> GetGradDefs(
    const tensorflow::GraphDef& graph_def) {
  std::vector<std::pair<string, string>> grads;
  for (const tensorflow::GradientDef& grad : graph_def.library().gradient()) {
    grads.emplace_back(grad.function_name(), grad.gradient_func());
  }
  std::sort(grads.begin(), grads.end());
  return grads;
}