TFDS CLI es una herramienta de línea de comandos que proporciona varios comandos para trabajar fácilmente con conjuntos de datos de TensorFlow.
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Deshabilitar registros TF en la importación
%%capture
%env TF_CPP_MIN_LOG_LEVEL=1 # Disable logs on TF import
Instalación
La herramienta CLI se instala con tensorflow-datasets (o tfds-nightly ).
pip install -q tfds-nightlytfds --version
Para la lista de todos los comandos CLI:
tfds --help
usage: tfds [-h] [--helpfull] [--version] {build,new} ...
Tensorflow Datasets CLI tool
optional arguments:
-h, --help show this help message and exit
--helpfull show full help message and exit
--version show program's version number and exit
command:
{build,new}
build Commands for downloading and preparing datasets.
new Creates a new dataset directory from the template.
tfds new : Implementación de un nuevo conjunto de datos
Este comando lo ayudará a comenzar a escribir su nuevo conjunto de datos de Python creando un <dataset_name>/ que contiene los archivos de implementación predeterminados.
Uso:
tfds new my_dataset
2022-02-07 04:04:10.397902: E tensorflow/stream_executor/cuda/cuda_driver.cc:271] failed call to cuInit: CUDA_ERROR_NO_DEVICE: no CUDA-capable device is detected Dataset generated at /tmpfs/src/temp/docs/my_dataset You can start searching `TODO(my_dataset)` to complete the implementation. Please check https://www.tensorflow.org/datasets/add_dataset for additional details.
Creará:
ls -1 my_dataset/
__init__.py checksums.tsv dummy_data/ my_dataset.py my_dataset_test.py
Consulte nuestra guía de conjunto de datos de escritura para obtener más información.
Opciones Disponibles:
tfds new --help
usage: tfds new [-h] [--helpfull] [--dir DIR] dataset_name
positional arguments:
dataset_name Name of the dataset to be created (in snake_case)
optional arguments:
-h, --help show this help message and exit
--helpfull show full help message and exit
--dir DIR Path where the dataset directory will be created. Defaults to
current directory.
tfds build : descarga y prepara un conjunto de datos
Utilice tfds build <my_dataset> para generar un nuevo conjunto de datos. <my_dataset> puede ser:
Una ruta a
dataset/carpeta o archivodataset.py(vacío para el directorio actual):-
tfds build datasets/my_dataset/ -
cd datasets/my_dataset/ && tfds build -
cd datasets/my_dataset/ && tfds build my_dataset -
cd datasets/my_dataset/ && tfds build my_dataset.py
-
Un conjunto de datos registrado:
-
tfds build mnist -
tfds build my_dataset --imports my_project.datasets
-
Opciones Disponibles:
tfds build --help
usage: tfds build [-h] [--helpfull]
[--datasets DATASETS_KEYWORD [DATASETS_KEYWORD ...]]
[--overwrite]
[--max_examples_per_split [MAX_EXAMPLES_PER_SPLIT]]
[--data_dir DATA_DIR] [--download_dir DOWNLOAD_DIR]
[--extract_dir EXTRACT_DIR] [--manual_dir MANUAL_DIR]
[--add_name_to_manual_dir] [--config CONFIG]
[--config_idx CONFIG_IDX] [--imports IMPORTS]
[--register_checksums] [--force_checksums_validation]
[--beam_pipeline_options BEAM_PIPELINE_OPTIONS]
[--file_format FILE_FORMAT]
[--exclude_datasets EXCLUDE_DATASETS]
[--experimental_latest_version]
[datasets [datasets ...]]
positional arguments:
datasets Name(s) of the dataset(s) to build. Default to current
dir. See https://www.tensorflow.org/datasets/cli for
accepted values.
optional arguments:
-h, --help show this help message and exit
--helpfull show full help message and exit
--datasets DATASETS_KEYWORD [DATASETS_KEYWORD ...]
Datasets can also be provided as keyword argument.
Debug & tests:
--pdb Enter post-mortem debugging mode if an exception is raised.
--overwrite Delete pre-existing dataset if it exists.
--max_examples_per_split [MAX_EXAMPLES_PER_SPLIT]
When set, only generate the first X examples (default
to 1), rather than the full dataset.If set to 0, only
execute the `_split_generators` (which download the
original data), but skip `_generator_examples`
Paths:
--data_dir DATA_DIR Where to place datasets. Default to
`~/tensorflow_datasets/` or `TFDS_DATA_DIR`
environement variable.
--download_dir DOWNLOAD_DIR
Where to place downloads. Default to
`<data_dir>/downloads/`.
--extract_dir EXTRACT_DIR
Where to extract files. Default to
`<download_dir>/extracted/`.
--manual_dir MANUAL_DIR
Where to manually download data (required for some
datasets). Default to `<download_dir>/manual/`.
--add_name_to_manual_dir
If true, append the dataset name to the `manual_dir`
(e.g. `<download_dir>/manual/<dataset_name>/`. Useful
to avoid collisions if many datasets are generated.
Generation:
--config CONFIG, -c CONFIG
Config name to build. Build all configs if not set.
--config_idx CONFIG_IDX
Config id to build
(`builder_cls.BUILDER_CONFIGS[config_idx]`). Mutually
exclusive with `--config`.
--imports IMPORTS, -i IMPORTS
Comma separated list of module to import to register
datasets.
--register_checksums If True, store size and checksum of downloaded files.
--force_checksums_validation
If True, raise an error if the checksums are not
found.
--beam_pipeline_options BEAM_PIPELINE_OPTIONS
A (comma-separated) list of flags to pass to
`PipelineOptions` when preparing with Apache Beam.
(see:
https://www.tensorflow.org/datasets/beam_datasets).
Example: `--beam_pipeline_options=job_name=my-
job,project=my-project`
--file_format FILE_FORMAT
File format to which generate the tf-examples.
Available values: ['tfrecord', 'riegeli'] (see
`tfds.core.FileFormat`).
Automation:
Used by automated scripts.
--exclude_datasets EXCLUDE_DATASETS
If set, generate all datasets except the one defined
here. Comma separated list of datasets to exclude.
--experimental_latest_version
Build the latest Version(experiments=...) available
rather than default version.