<div class="termy">

```console
$ python ./scripts/docs.py live

<span style="color: green;">[INFO]</span> Serving on http://127.0.0.1:8008
<span style="color: green;">[INFO]</span> Start watching changes
<span style="color: green;">[INFO]</span> Start detecting changes
```

</div>

It will serve the documentation on `http://127.0.0.1:8008`.

    private final Serializer<LogLevel> logLevelSerializer;
    private final Serializer<List<StyledTextOutputEvent.Span>> spanSerializer;

    public StyledTextOutputEventSerializer(Serializer<LogLevel> logLevelSerializer, Serializer<List<StyledTextOutputEvent.Span>> spanSerializer) {
        this.logLevelSerializer = logLevelSerializer;
        this.spanSerializer = spanSerializer;
    }

    @Override

<div class="termy">

```console
$ python ./scripts/docs.py live

<span style="color: green;">[INFO]</span> Serving on http://127.0.0.1:8008
<span style="color: green;">[INFO]</span> Start watching changes
<span style="color: green;">[INFO]</span> Start detecting changes
```

</div>

Das stellt die Dokumentation unter `http://127.0.0.1:8008` bereit.

// Copyright 2024 The Go Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.

//go:build !msan

package msan

import (
	"unsafe"
)

const Enabled = false

func Read(addr unsafe.Pointer, sz uintptr) {
}

func Write(addr unsafe.Pointer, sz uintptr) {
}

func Malloc(addr unsafe.Pointer, sz uintptr) {
}

#include "tensorflow/c/experimental/gradients/not_differentiable.h"

namespace tensorflow {
namespace gradients {
Status NotDifferentiableGradientFunction::Compute(
    AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> grad_outputs,
    absl::Span<AbstractTensorHandle*> grad_inputs) {
  for (int i = 0; i < grad_inputs.size(); i++) {
    grad_inputs[i] = nullptr;
  }
  return absl::OkStatus();
}

class NotDifferentiableGradientFunction : public GradientFunction {
  Status Compute(AbstractContext* ctx,
                 absl::Span<AbstractTensorHandle* const> grad_outputs,
                 absl::Span<AbstractTensorHandle*> grad_inputs) override;
};
// Shorthand for registry->Register(op, new NotDifferentiableGradientFunction)

==============================================================================*/

#include "tensorflow/c/experimental/saved_model/core/revived_types/flat_tensor_function.h"

#include <memory>
#include <string>

#include "absl/types/span.h"
#include "tensorflow/c/eager/abstract_tensor_handle.h"
#include "tensorflow/c/eager/immediate_execution_operation.h"
#include "tensorflow/c/eager/immediate_execution_tensor_handle.h"

																	<span class="badge bg-primary"><la:message
                                                                            key="labels.enabled"/></span>
                                                    </c:if> <c:if test="${data.available=='false'}">
																	<span class="badge bg-gray"><la:message

                                                        aria-label="Close">
                                                    <span aria-hidden="true">×</span>
                                                </button>
                                            </div>
                                            <div class="modal-body">

  if (attr_.full_type() == "list(string)") {
    return "absl::Span<string const>";
  }

  // Normal path: translate base type to C++ ...
  string c_base_type = attr_.base_type();
  if (attr_.base_type() == "type") {
    c_base_type = "DataType";
  } else if (attr_.base_type() == "shape") {
    c_base_type = "const PartialTensorShape";
  }

  // ... and wrap in a Span<> if it's a list.
  if (attr_.is_list()) {