errors.invalid_design_jsp_file_name = Berkas JSP tidak valid.
errors.design_jsp_file_does_not_exist = Berkas JSP tidak ada.
errors.design_file_name_is_not_found = Nama berkas tidak ditentukan.
errors.failed_to_write_design_image_file = Gagal mengunggah berkas gambar.
errors.failed_to_update_jsp_file = Gagal memperbarui berkas JSP.
errors.design_file_name_is_invalid = Nama berkas tidak valid.

labels.startTime=Waktu Mulai
labels.target=Target
labels.token=Token
labels.synonymFile=Berkas Sinonim
labels.stopwordsFile=Berkas Stopwords
labels.stemmerOverrideFile=Berkas Stemmer Override
labels.mappingFile=Berkas Mapping
labels.protwordsFile=Berkas Protwords
labels.kuromojiFile=Berkas Kuromoji
labels.elevateWordFile=Berkas Elevate Word
labels.badWordFile=Berkas Bad Word
labels.urlExpr=Kondisi
labels.boostExpr=Ekspresi Boost

*   Keras 3.0 will be the default Keras version. You may need to update your
    script to use Keras 3.0.

*   Please refer to the new Keras documentation for Keras 3.0
    (https://keras.io/keras_3).

*   To continue using Keras 2.0, do the following.

*   1.  Install tf-keras via pip install tf-keras~=2.16

    1.  To switch tf.keras to use Keras 2 (tf-keras), set the environment

  "$python" -c 'import tensorflow as tf; t1=tf.constant([1,2,3,4]); t2=tf.constant([5,6,7,8]); print(tf.add(t1,t2).shape)'
  "$python" -c 'import sys; import tensorflow as tf; sys.exit(0 if "keras" in tf.keras.__name__ else 1)'
fi
# Import tf nightly wheel built with numpy2 from PyPI in numpy1 env for testing.
# This aims to maintain TF compatibility with NumPy 1.x until 2025 b/361369076.

    # via
    #   -r ci/official/requirements_updater/requirements.in
    #   jax
    #   keras-nightly
namex==0.0.9 \
    --hash=sha256:7bd4e4a2cc3876592111609fdf4cbe6ff19883adbe6b3b40d842fd340f77025e \
    --hash=sha256:8adfea9da5cea5be8f4e632349b4669e30172c7859e1fd97459fdf3b17469253
    # via keras-nightly
numpy==1.26.4 \
    --hash=sha256:03a8c78d01d9781b28a6989f6fa1bb2c4f2d51201cf99d3dd875df6fbd96b23b \

    # via
    #   -r ci/official/requirements_updater/requirements.in
    #   jax
    #   keras-nightly
namex==0.0.9 \
    --hash=sha256:7bd4e4a2cc3876592111609fdf4cbe6ff19883adbe6b3b40d842fd340f77025e \
    --hash=sha256:8adfea9da5cea5be8f4e632349b4669e30172c7859e1fd97459fdf3b17469253
    # via keras-nightly
numpy==1.26.4 \
    --hash=sha256:03a8c78d01d9781b28a6989f6fa1bb2c4f2d51201cf99d3dd875df6fbd96b23b \

    # via
    #   -r ci/official/requirements_updater/requirements.in
    #   jax
    #   keras-nightly
namex==0.0.9 \
    --hash=sha256:7bd4e4a2cc3876592111609fdf4cbe6ff19883adbe6b3b40d842fd340f77025e \
    --hash=sha256:8adfea9da5cea5be8f4e632349b4669e30172c7859e1fd97459fdf3b17469253
    # via keras-nightly
numpy==2.1.3 ; python_version <= "3.13" \

    # via
    #   -r ci/official/requirements_updater/requirements.in
    #   jax
    #   keras-nightly
namex==0.0.9 \
    --hash=sha256:7bd4e4a2cc3876592111609fdf4cbe6ff19883adbe6b3b40d842fd340f77025e \
    --hash=sha256:8adfea9da5cea5be8f4e632349b4669e30172c7859e1fd97459fdf3b17469253
    # via keras-nightly
numpy==2.4.2 ; python_version == "3.14" \

Para este ejemplo simple, vamos a ser completamente inseguros y devolver el mismo `username` como el token.

/// tip | Consejo

En el próximo capítulo, verás una implementación segura real, con hashing de passwords y tokens <abbr title="JSON Web Tokens">JWT</abbr>.

Pero por ahora, enfoquémonos en los detalles específicos que necesitamos.

///

wrapt == 1.16.0
tblib == 2.0.0
ml_dtypes >= 0.5.4, < 0.6.0
auditwheel >= 6.1.0
# Install tensorboard, and keras
# Note that here we want the latest version that matches TF major.minor version
# Note that we must use nightly here as these are used in nightly jobs
# For release jobs, we will pin these on the release branch
keras-nightly ~= 3.12.0.dev
tb-nightly ~= 2.20.0.a