Lóránt Pintér <******@****.***>
Lóránt Pintér <******@****.***> <******@****.***>
Lóránt Pintér <******@****.***> <******@****.***>
Marcin Erdmann <******@****.***> <******@****.***>
Marco Vermeulen <marco@gradle.com> <******@****.***>
Mark Vieira <******@****.***> <******@****.***>
Michael Barnathan <******@****.***> <******@****.***>
Paul King <******@****.***> <******@****.***>

Dentro de la función, puedes acceder a todos los atributos del objeto modelo directamente:

{* ../../docs_src/body/tutorial002_py310.py *}

/// info | Información

En Pydantic v1 el método se llamaba `.dict()`, se marcó como obsoleto (pero sigue soportado) en Pydantic v2, y se renombró a `.model_dump()`.

Los ejemplos aquí usan `.dict()` por compatibilidad con Pydantic v1, pero deberías usar `.model_dump()` si puedes usar Pydantic v2.

///

For instructions or titles in imperative, keep them in imperative, for example "Edit it" to "Edítalo".

---

For the next terms, use the following translations:

* framework: framework (do not translate to "marco")
* performance: rendimiento
* program (verb): programar
* code (verb): programar
* type hints: anotaciones de tipos
* type annotations: anotaciones de tipos
* autocomplete: autocompletado

	{
		"define without value",
		"#define A",
		"",
	},
	{
		"macro without arguments",
		"#define A() 1234\n" + "A()\n",
		"1234.\n",
	},
	{
		"macro with just parens as body",
		"#define A () \n" + "A\n",
		"(.).\n",
	},
	{
		"macro with parens but no arguments",
		"#define A (x) \n" + "A\n",
		"(.x.).\n",
	},
	{
		"macro with arguments",
		"#define A(x, y, z) x+z+y\n" + "A(1, 2, 3)\n",

	return Token{ScanToken: token, text: text}
}

func (l Token) String() string {
	return l.text
}

// A Macro represents the definition of a #defined macro.
type Macro struct {
	name   string   // The #define name.
	args   []string // Formal arguments.
	tokens []Token  // Body of macro.
}

// Tokenize turns a string into a list of Tokens; used to parse the -D flag and in tests.

#ifndef TENSORFLOW_C_C_API_MACROS_INTERNAL_H_
#define TENSORFLOW_C_C_API_MACROS_INTERNAL_H_

#ifdef __cplusplus
#include "tensorflow/core/platform/status.h"

// Macro to verify that the field `struct_size` of STRUCT_OBJ is initialized.
// `struct_size` is used for struct member compatibility check between core TF
// and plug-ins with the same C API minor version. More info here:

        mapEntry("three", "March"),
        mapEntry("four", "April"),
        mapEntry("five", "May"));
  }

  @Override
  public SampleElements<String> sampleKeys() {
    return new SampleElements<>("one", "two", "three", "four", "five");
  }

  @Override
  public SampleElements<String> sampleValues() {
    return new SampleElements<>("January", "February", "March", "April", "May");
  }

  @Override

        mapEntry("three", "March"),
        mapEntry("four", "April"),
        mapEntry("five", "May"));
  }

  @Override
  public SampleElements<String> sampleKeys() {
    return new SampleElements<>("one", "two", "three", "four", "five");
  }

  @Override
  public SampleElements<String> sampleValues() {
    return new SampleElements<>("January", "February", "March", "April", "May");
  }

  @Override

}

func (s *Slice) Line() int {
	return s.line
}

func (s *Slice) Col() int {
	// TODO: Col is only called when defining a macro and all it cares about is increasing
	// position to discover whether there is a blank before the parenthesis.
	// We only get here if defining a macro inside a macro.
	// This imperfect implementation means we cannot tell the difference between
	//	#define A #define B(x) x
	// and

        mapEntry("three", "March"),
        mapEntry("four", "April"),
        mapEntry("five", "May"));
  }

  @Override
  public SampleElements<String> sampleKeys() {
    return new SampleElements<>("one", "two", "three", "four", "five");
  }

  @Override
  public SampleElements<String> sampleValues() {
    return new SampleElements<>("January", "February", "March", "April", "May");
  }

  @Override