tensorflow::unwrap(ctx)->CreateLocalHandle(t->tensor));
}

TFE_TensorHandle* TFE_CreatePackedTensorHandle(TFE_Context* ctx,
                                               TFE_TensorHandle** handles,
                                               int* num_handles,
                                               TF_Status* status) {
  std::vector<tensorflow::TensorHandle*> tensor_handles;

    }

    @Test
    public void test_render_null() {
        assertEquals("", markdownRenderer.render(null));
    }

    @Test
    public void test_render_empty() {
        assertEquals("", markdownRenderer.render(""));
    }

    @Test
    public void test_render_plainText() {
        String result = markdownRenderer.render("Hello World");
        assertTrue(result.contains("Hello World"));

    void testAs_Enumeration_Success() throws PACDecodingException {
        // Test successful casting from enumeration
        Vector<ASN1Integer> vector = new Vector<>();
        ASN1Integer expected = new ASN1Integer(123);
        vector.add(expected);
        ASN1Integer result = ASN1Util.as(ASN1Integer.class, vector.elements());
        assertSame(expected, result);
    }

    @Test
    void testAs_Enumeration_Failure() {

  // Returns the status of the tensor handle. If it is a tfrt::TensorHandle,
  // the tensor handle can be an error and return non-OK status.
  virtual absl::Status TensorHandleStatus() const;

  // Returns tensor shape. If tensor has unknown rank, shape remains untouched.
  virtual absl::Status Shape(tensorflow::PartialTensorShape* shape) const = 0;

  // Returns tensor (full) type.

    @SuppressWarnings("unused")
    @Test
    public void testIterable() throws Exception {
        final Vector<String> vector = new Vector<String>();
        vector.add("a");
        vector.add("b");
        int count = 0;
        for (final String s : iterable(vector.elements())) {
            ++count;
        }
        assertThat(count, is(2));
    }

    /**
     * Test method for

            - raw_headers
            - render
            - init_headers
            - headers
            - set_cookie
            - delete_cookie

::: fastapi.responses.ORJSONResponse
    options:
        members:
            - charset
            - status_code
            - media_type
            - body
            - background
            - raw_headers
            - render
            - init_headers

  if (!status->status.ok()) return;

  // Initialize a input_tensor vector with `nullptr` values.
  std::vector<const Tensor*> input_tensors_vector(num_inputs, nullptr);
  // A vector to keep track of newly created `tf::Tensor` objects.
  std::vector<Tensor> all_input_tensors;
  // Update the vector with information from `input_tensors` if provided.
  if (input_tensors != nullptr) {

{% endfor %}
{% endif %}

{% if sponsors.silver %}

### Silver Sponsors

{% for sponsor in sponsors.silver -%}
<a href="{{ sponsor.url }}" title="{{ sponsor.title }}"><img src="{{ sponsor.img }}" style="border-radius:15px"></a>
{% endfor %}
{% endif %}

{% if sponsors.bronze %}

### Bronze Sponsors

{% endfor -%}

### Gold- und Silber-Sponsoren { #gold-and-silver-sponsors }

{% for sponsor in sponsors.gold -%}
<a href="{{ sponsor.url }}" title="{{ sponsor.title }}"><img src="{{ sponsor.img }}" style="border-radius:15px"></a>
{% endfor -%}
{%- for sponsor in sponsors.silver -%}

#ifndef TENSORFLOW_C_EAGER_DLPACK_H_
#define TENSORFLOW_C_EAGER_DLPACK_H_

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

namespace tensorflow {

// PyCapsule name for DLPack Tensor
const char* const kDlTensorCapsuleName = "dltensor";

// Returns the DLDevice* for the given eager tensor handle.
//
// The caller takes ownership of the returned pointer and is responsible for
// deleting it.
TF_CAPI_EXPORT extern void* TFE_GetDLDevice(TFE_TensorHandle* h,