#### Option A: Reference colab notebooks

1)  Reference [TensorFlow Model Colab](https://colab.research.google.com/gist/ymodak/e96a4270b953201d5362c61c1e8b78aa/tensorflow-datasets.ipynb?authuser=1): Demonstrate how to build your TF model.

   
   Apparently, your CPU model does not support AVX instruction sets. You can still use TensorFlow with the alternatives given below:
   
      * Try Google Colab to use TensorFlow.
         * The easiest way to use TF will be to switch to [google colab](https://colab.sandbox.google.com/notebooks/welcome.ipynb#recent=true). You get pre-installed latest stable TF version. Also you can use ```pip install```  to install any other preferred TF version.

```
# Copy and paste here
```

**Standalone code to reproduce the issue** 
Provide a reproducible test case that is the bare minimum necessary to generate
the problem. If possible, please share a link to Colab/Jupyter/any notebook.

Also, please include a link to a GraphDef or the model if possible.

**Any other info / logs**

Include any logs or source code that would be helpful to diagnose the problem.

    reproduce the issue description: Provide a reproducible test case that is
    the bare minimum necessary to generate the problem. If possible, please
    share a link to Colab/Jupyter/any notebook. placeholder: Tell us what you
    see! value: render: shell validations: required: true

-   type: textarea id: logs attributes: label: Relevant log output description:

    id: code-to-reproduce
    attributes:
      label: Standalone code to reproduce the issue
      description: Provide a reproducible test case that is the bare minimum necessary to generate the problem. Please share a link to Colab, Jupyter, or any notebook.
      placeholder: Tell us what you see!
      value:
      render: shell
    validations:
      required: true
  - type: textarea
    id: logs
    attributes:

En lugar de eso, al ser un sistema "asíncrono", una vez finalizada, la tarea puede esperar un poco en la cola (algunos microsegundos) para que la computadora / programa termine lo que estaba haciendo, y luego vuelva para recoger los resultados y seguir trabajando con ellos.

	Isso ocorre porque está utilizando o mesmo nome que está nas especificações do OpenAPI. Então, se você precisa investigar mais sobre qualquer um desses esquemas de segurança, você pode simplesmente copiar e colar para encontrar mais informações sobre isso.

A variável `oauth2_scheme` é um instância de `OAuth2PasswordBearer`, mas também é um "callable".

Pode ser chamada de:

```Python
oauth2_scheme(some, parameters)

    }
    sink1.writeUtf8("def")
    sink1.close()
    assertFailsWith<ConnectionShutdownException> {
      connection.newStream(headerEntries("c", "cola"), true)
    }
    assertThat(stream1.isOpen).isTrue()
    assertThat(stream2.isOpen).isFalse()
    assertThat(connection.openStreamCount()).isEqualTo(1)

    // Verify the peer received what was expected.

        strings and takes care of text standardization, tokenization, n-gram
        generation, and vocabulary indexing. See this
        [end-to-end text classification example](https://colab.research.google.com/drive/1RvCnR7h0_l4Ekn5vINWToI9TNJdpUZB3).
    *   Keras `.compile` `.fit` `.evaluate` and `.predict` are allowed to be
        outside of the DistributionStrategy scope, as long as the model was

   * Format</a> ({@code crw} files), a widely-used "raw image" format for cameras. It is found in
   * {@code /etc/mime.types}, e.g. in <a href=
   * "http://anonscm.debian.org/gitweb/?p=collab-maint/mime-support.git;a=blob;f=mime.types;hb=HEAD"
   * >Debian 3.48-1</a>.
   *
   * @since 15.0
   */
  public static final MediaType CRW = createConstant(IMAGE_TYPE, "x-canon-crw");