//   "The text in style, script, title, and textarea elements
		//   must not have an escaping text span start that is not
		//   followed by an escaping text span end."
		// Furthermore, spoofing an escaping text span end could lead
		// to different interpretation of a </script> sequence otherwise
		// masked by the escaping text span, and spoofing a start could

		})
		if err != nil {
			span.AddEvent("Write to database call failed", attribute.Int("len", len(body)), attribute.String("err", err.Error()))
			scope.err(err, w, req)
			return
		}
		span.AddEvent("Write to database call succeeded", attribute.Int("len", len(body)))

		status := http.StatusOK
		if wasCreated {
			status = http.StatusCreated
		}

		span.AddEvent("About to write a response")

                <button type="button" aria-label="Navigation Menu" class="site-header__navigation-button hamburger">
                    <span class="hamburger__bar"></span>
                    <span class="hamburger__bar"></span>
                    <span class="hamburger__bar"></span>
                </button>
            </div>
            <div class="site-header__navigation-collapsible site-header__navigation-collapsible--collapse">

		}

		// Check if val points to a heap span.
		span := spanOfHeap(val)
		if span == nil {
			continue
		}

		// Check if val points to an allocated object.
		idx := span.objIndex(val)
		if span.isFree(idx) {
			continue
		}

		// val points to an allocated object. Mark it.
		obj := span.base() + idx*span.elemsize
		greyobject(obj, b, i, span, gcw, idx)
	}
}

    TF_DeleteTensor(numerical_tensor);
    delete[] danalytical;
    delete[] dnumerical;
    outputs[i]->Unref();
  }
}

void CheckTensorValue(AbstractTensorHandle* t, absl::Span<const float> manuals,
                      absl::Span<const int64_t> dims, double abs_error) {
  TF_Tensor* analytical_tensor;
  auto s = GetValue(t, &analytical_tensor);
  ASSERT_EQ(errors::OK, s.code()) << s.message();

                 AbstractTensorHandle* const tensor_names,
                 AbstractTensorHandle* const shape_and_slices,
                 absl::Span<AbstractTensorHandle*> tensors,
                 absl::Span<DataType> dtypes, const char* name = nullptr,
                 const char* raw_device_name = nullptr);

// Saves tensors in V2 checkpoint format.

  int num_retvals = 1;
  return op_ptr->Execute(absl::MakeSpan(product, 1), &num_retvals);
}

// Op: IdentityN()
// Summary:
//
// Description:
Status IdentityN(AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> input, absl::Span<AbstractTensorHandle*> output, const char* name, const char* raw_device_name) {
  AbstractOperationPtr op_ptr(ctx->CreateOperation());
  TF_RETURN_IF_ERROR(op_ptr->Reset("IdentityN", raw_device_name));

    LogLevel getLogLevel();

    @Override
    List<? extends Span> getSpans();

    @UsedByScanPlugin("Non-internal replacement available since Gradle 7.4")
    @Deprecated
    @SuppressWarnings("DeprecatedIsStillUsed")
    interface Span extends org.gradle.internal.operations.logging.StyledTextBuildOperationProgressDetails.Span {
    }

Status ReluModel(AbstractContext* ctx,
                 absl::Span<AbstractTensorHandle* const> inputs,
                 absl::Span<AbstractTensorHandle*> outputs) {
  return ops::Relu(ctx, inputs[0], &outputs[0], "Relu");
}

Status SparseSoftmaxCrossEntropyWithLogitsModel(
    AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> inputs,
    absl::Span<AbstractTensorHandle*> outputs) {
  AbstractTensorHandle* loss;

	// always accessed atomically.
	//
	// The head and the tail are only 32 bits wide, which means we
	// can only support up to 2^32 pushes before a reset. If every
	// span in the heap were stored in this set, and each span were
	// the minimum size (1 runtime page, 8 KiB), then roughly the
	// smallest heap which would be unrepresentable is 32 TiB in size.
	index atomicHeadTailIndex
}

const (