}
		p.printf("}")

	case reflect.Struct:
		typ := x.Type()

		// if span, ok := x.Interface().(lexical.Span); ok {
		// 	p.printf("%s", &span)
		// 	return
		// }

		p.printf("%s {", typ)
		p.indent++

		first := true
		if n != nil {
			p.printf("\n")
			first = false
			// p.printf("Span: %s\n", n.Span())
			// if c := *n.Comments(); c != nil {
			// 	p.printf("Comments: ")

<div class="badge-wrapper">
    <a class="badge" href="https://dpeuniversity.gradle.com/app/courses/012de84f-fcd3-45d4-9c4c-284382eb3f3f/" target="_blank">
        <span class="badge-type button--blue">LEARN</span>
        <span class="badge-text">Introduction to Gradle for Developers&nbsp;&nbsp;&nbsp;&gt;</span>
    </a>
</div>
++++

Build engineers that are ready to configure custom build logic and write their own plugins should start here.

const (
	_ traceEv = 127 + iota

	// Experimental events for ExperimentAllocFree.

	// Experimental heap span events. IDs map reversibly to base addresses.
	traceEvSpan      // heap span exists [timestamp, id, npages, type/class]
	traceEvSpanAlloc // heap span alloc [timestamp, id, npages, type/class]
	traceEvSpanFree  // heap span free [timestamp, id]

	// Experimental heap object events. IDs map reversibly to addresses.

                </mxCell>

                 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));

    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();

    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;

Status MatMulModel(AbstractContext* ctx,
                   absl::Span<AbstractTensorHandle* const> inputs,
                   absl::Span<AbstractTensorHandle*> outputs) {
  return ops::MatMul(ctx, inputs[0], inputs[1], &outputs[0],
                     /*transpose_a=*/false,
                     /*transpose_b=*/false, "MatMul");
}

Status MulModel(AbstractContext* ctx,
                absl::Span<AbstractTensorHandle* const> inputs,