parent_op_(parent_op),
      tape_(tape),
      registry_(registry) {
  // TODO(b/172003047): Consider making AbstractOperation RefCounted.
  // parent_op_->Ref();
}
void TapeOperation::Release() {
  // TODO(srbs): Change to Unref().
  delete this;
}
TapeOperation::~TapeOperation() {
  // TODO(b/172003047): Consider making AbstractOperation RefCounted.
  // parent_op->Unref();
}

                                 status);
  EXPECT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);

  TFE_DeleteContextOptions(opts);
  TFE_DeleteContext(ctx);
  TF_DeleteStatus(status);

  w0.release();
  w1.release();
}

TEST(CAPI, ShareVariableAcrossContextsAfterUpdateContextWorksWithTimeout) {
  tensorflow::ServerDef server_def_0 = GetServerDef(3);

    switch (block->state) {
      case FetchState::ERROR:
        // TF_FALLTHROUGH_INTENDED
      case FetchState::CREATED:
        block->state = FetchState::FETCHING;
        block->mu.Unlock();  // Release the lock while making the API call.
        block->data.clear();
        block->data.resize(block_size_, 0);
        int64_t bytes_transferred;
        bytes_transferred = block_fetcher_(key.first, key.second, block_size_,

      with:
        title: '${{ github.event.inputs.release_branch }} cherry-pick: ${{ steps.cherrypick.outputs.SHORTSHA }} "${{ steps.cherrypick.outputs.TITLE }}"'
        committer: TensorFlow Release Automation <******@****.***>
        token: ${{ secrets.JENKINS_TOKEN }}
        base: ${{ github.event.inputs.release_branch }}
        branch: ${{ github.event.inputs.release_branch }}-${{ steps.cherrypick.outputs.SHORTSHA }}

// Accumulate runs the gradient computation immediately.
//
// Keeps references to Tensors watched via Watch and computed in Accumulate
// corresponding to output_tensors, and releases these references in its
// destructor. However, waiting until the destructor runs loses the memory
// efficiency of forward-mode autodiff. Instead, language bindings should call

do
  cp ../../../requirements_lock_"$VERSION".txt "requirements_lock_"$VERSION".txt"
  bazel run \
    --experimental_convenience_symlinks=ignore \
    --enable_bzlmod=false \
    //:requirements_"$VERSION"_release.update
  sed -i '/^#/d' requirements_lock_"$VERSION".txt
  mv "requirements_lock_"$VERSION".txt" ../../../requirements_lock_"$VERSION".txt
done

// Wraps a pointer to an operation implementation.
//
// WARNING: Since the underlying object could be ref-counted a user of this
// interface cannot destruct the underlying operation object. Instead, call
// TFE_DeleteOp who calls Release() on the operation pointer and deletes
// the TFE_Op structure.
typedef struct TFE_Op TFE_Op;

namespace tensorflow {

DEFINE_CONVERSION_FUNCTIONS(tensorflow::ImmediateExecutionOperation, TFE_Op);

//
// WARNING: Since the underlying object could be ref-counted a user of this
// interface cannot destruct the underlying handle object. Instead, call
// TFE_DeleteTensorHandle who calls Release() on the handle pointer and deletes
// the TFE_TensorHandle structure.
typedef struct TFE_TensorHandle TFE_TensorHandle;

namespace tensorflow {

DEFINE_CONVERSION_FUNCTIONS(tensorflow::ImmediateExecutionTensorHandle,

  ~ImmediateExecutionOperation() override {}
};

namespace internal {
struct ImmediateExecutionOperationDeleter {
  void operator()(ImmediateExecutionOperation* p) const {
    if (p != nullptr) {
      p->Release();
    }
  }
};
}  // namespace internal

using ImmediateOpPtr =
    std::unique_ptr<ImmediateExecutionOperation,
                    internal::ImmediateExecutionOperationDeleter>;

   
   -----------------------------------------------------------------------------------------------
   
   **2. Installing **TensorFlow** (TF) CPU prebuilt binaries**
   
   
   *TensorFlow release binaries version 1.6 and higher are prebuilt with AVX instruction sets.*
   
   
   Therefore on any CPU that does not have these instruction sets, either CPU or GPU version of TF will fail to load.