#SNG: from basn3p08.png
IHDR {
    width: 32; height: 32; bitdepth: 8;
    using color palette;
}
gAMA {1.0000}
PLTE {
    ( 34, 68,  0)     # rgb = (0x22,0x44,0x00)
    (245,255,237)     # rgb = (0xf5,0xff,0xed)
    (119,255,119)     # rgb = (0x77,0xff,0x77)
    (203,255,255)     # rgb = (0xcb,0xff,0xff)
    ( 17, 10,  0)     # rgb = (0x11,0x0a,0x00)
    ( 58,119,  0)     # rgb = (0x3a,0x77,0x00)
    ( 34, 34,255)     # rgb = (0x22,0x22,0xff)

#SNG: from ftp1n3p08.png
IHDR {
    width: 32; height: 32; bitdepth: 8;
    using color palette;
}
gAMA {1.0000}
PLTE {
    (255,255,255)     # rgb = (0xff,0xff,0xff) grey100
    (128, 86, 86)     # rgb = (0x80,0x56,0x56)
    (181,181,184)     # rgb = (0xb5,0xb5,0xb8)
    (168, 66, 66)     # rgb = (0xa8,0x42,0x42)
    (159,159,159)     # rgb = (0x9f,0x9f,0x9f)
    (177, 32, 32)     # rgb = (0xb1,0x20,0x20)

                    withPsiEntry("parent", parent)
                }
            /**
             * EXPRESSIONS
             */
            // Enum entries, type parameters, lamda expressions and script
            // initializers never use any child expressions.
            is KtEnumEntry ->
                false
            is KtTypeParameter ->
                false

* <a href="https://github.com/swagger-api/swagger-ui" class="external-link" target="_blank"><strong>Swagger UI</strong></a>, con exploración interactiva, llama y prueba tu API directamente desde tu navegador.

![Swagger UI interaction](https://fastapi.tiangolo.com/img/index/index-03-swagger-02.png)

      TypeID::get<TF::IFFTOp>(),
      TypeID::get<TF::ImagOp>(),
      TypeID::get<TF::IsFiniteOp>(),
      TypeID::get<TF::IsInfOp>(),
      TypeID::get<TF::IsNanOp>(),
      TypeID::get<TF::LgammaOp>(),
      TypeID::get<TF::Log1pOp>(),
      TypeID::get<TF::LogSoftmaxOp>(),
      TypeID::get<TF::MatrixBandPartOp>(),
      TypeID::get<TF::MaxPool3DGradOp>(),
      TypeID::get<TF::PreventGradientOp>(),

    %t:tensor<1x10x10x3xf32>, %m:tensor<3xf32>, %v:tensor<3xf32>, %beta:tensor<3xf32>, %gamma:tensor<3xf32>) -> (tensor<1x10x10x3xf32>) {
  %0 = "tf.BatchNormWithGlobalNormalization"(%t, %m, %v, %beta, %gamma) {T = "tfdtype$DT_FLOAT", variance_epsilon = 0.001 : f32, scale_after_normalization = false} : (tensor<1x10x10x3xf32>, tensor<3xf32>, tensor<3xf32>, tensor<3xf32>, tensor<3xf32>) -> (tensor<1x10x10x3xf32>)

	"ucirc":    "\u00FB",
	"uuml":     "\u00FC",
	"yacute":   "\u00FD",
	"thorn":    "\u00FE",
	"yuml":     "\u00FF",
	"fnof":     "\u0192",
	"Alpha":    "\u0391",
	"Beta":     "\u0392",
	"Gamma":    "\u0393",
	"Delta":    "\u0394",
	"Epsilon":  "\u0395",
	"Zeta":     "\u0396",
	"Eta":      "\u0397",
	"Theta":    "\u0398",
	"Iota":     "\u0399",
	"Kappa":    "\u039A",
	"Lambda":   "\u039B",

If "scale_after_normalization" is true, this tensor will be multiplied
with the normalized tensor.}]>:$gamma,

    F32Attr:$variance_epsilon,
    BoolAttr:$scale_after_normalization
  );

  let results = (outs

        .body("abcd")
        .build(),
    )
    server.enqueue(
      MockResponse.Builder()
        .addHeader("Transfer-Encoding: none")
        .addHeaderLenient("Gamma", "Γ")
        .addHeaderLenient("Δ", "Delta")
        .code(HttpURLConnection.HTTP_NOT_MODIFIED)
        .build(),
    )
    val response1 = get(server.url("/"))

	"lipstick":                             "\U0001f484",
	"lithuania":                            "\U0001f1f1\U0001f1f9",
	"lizard":                               "\U0001f98e",
	"llama":                                "\U0001f999",
	"lobster":                              "\U0001f99e",
	"lock":                                 "\U0001f512",
	"lock_with_ink_pen":                    "\U0001f50f",