sonnet
TensorFlow 기반 신경망 라이브러리
파일 탐색기
- ci.yml
- favicon.ico
- BUILD
- link_tf_api.py
- link_tf_api_test.py
- .gitignore
- api.rst
- conf.py
- index.rst
- Makefile
- modules.rst
- references.bib
- requirements.txt
- BUILD
- distributed_cifar10.ipynb
- functional_mlp_mnist.py
- little_gan_on_mnist.ipynb
- mlp_on_mnist.ipynb
- README.md
- simple_mnist.py
- simple_mnist_test.py
- vqvae_example.ipynb
- __init__.py
- BUILD
- resnet.py
- checkpoint
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- checkpoint-1.index
- checkpoint
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- BUILD
- generate.py
- README.md
- __init__.py
- api_test.py
- BUILD
- build_test.py
- checkpoint_test.py
- copy_test.py
- descriptors.py
- descriptors_test.py
- distribute_test.py
- doctest_test.py
- function_test.py
- goldens.py
- goldens_test.py
- keras_test.py
- optimizer_test.py
- pickle_test.py
- saved_model_test.py
- tensorflow1_test.py
- xla_test.py
- __init__.py
- BUILD
- distributed_batch_norm.py
- distributed_batch_norm_test.py
- replicator.py
- replicator_test.py
- replicator_test_utils.py
- __init__.py
- BUILD
- haiku.py
- haiku_test.py
- jax.py
- jax_test.py
- optimizers.py
- optimizers_test.py
- utils.py
- __init__.py
- BUILD
- control.py
- control_test.py
- read.py
- read_test.py
- util.py
- util_test.py
- write.py
- write_test.py
- __init__.py
- BUILD
- cifar10_convnet.py
- cifar10_convnet_test.py
- mlp.py
- mlp_test.py
- resnet.py
- resnet_test.py
- vqvae.py
- vqvae_test.py
- __init__.py
- adam.py
- adam_test.py
- BUILD
- momentum.py
- momentum_test.py
- optimizer_tests.py
- optimizer_utils.py
- rmsprop.py
- rmsprop_test.py
- sgd.py
- sgd_test.py
- __init__.py
- axis_norm.py
- axis_norm_test.py
- base.py
- base_test.py
- batch_apply.py
- batch_apply_test.py
- batch_norm.py
- batch_norm_test.py
- bias.py
- bias_test.py
- BUILD
- build.py
- build_defs.bzl
- build_test.py
- conv.py
- conv_test.py
- conv_transpose.py
- conv_transpose_test.py
- custom_getter.py
- custom_getter_test.py
- deferred.py
- deferred_test.py
- depthwise_conv.py
- depthwise_conv_test.py
- dropout.py
- dropout_test.py
- embed.py
- embed_test.py
- group_norm.py
- group_norm_test.py
- initializers.py
- initializers_test.py
- leaky_clip_by_value.py
- leaky_clip_by_value_test.py
- linear.py
- linear_test.py
- metrics.py
- metrics_test.py
- mixed_precision.py
- mixed_precision_test.py
- moving_averages.py
- moving_averages_test.py
- once.py
- once_test.py
- pad.py
- pad_test.py
- parallel_linear.py
- parallel_linear_test.py
- recurrent.py
- recurrent_test.py
- regularizers.py
- regularizers_test.py
- reshape.py
- reshape_test.py
- scale_gradient.py
- scale_gradient_test.py
- sequential.py
- sequential_test.py
- test_utils.py
- types.py
- utils.py
- utils_test.py
- __init__.py
- BUILD
- distribute.py
- functional.py
- initializers.py
- mixed_precision.py
- optimizers.py
- pad.py
- regularizers.py
- CONTRIBUTING.md
- LICENSE
- MANIFEST.in
- README.md
- readthedocs.yml
- requirements-test.txt
- requirements-tf.txt
- requirements.txt
- setup.py
- test.sh
- WORKSPACE
# 설치 가이드
python사전 준비물
- Python 3.x
- TensorFlow 2.0 >= 2.0
설치 및 실행 절차
pip install tensorflow tensorflow-probability
TensorFlow 및 관련 패키지를 설치합니다.
pip install dm-sonnet
Sonnet 라이브러리를 설치합니다.
핵심 명령어
pip install tensorflow tensorflow-probability dm-sonnet
TensorFlow 및 Sonnet 라이브러리를 설치합니다.
Google Colab을 사용하면 GPU나 TPU 환경에서 손쉽게 Sonnet을 테스트할 수 있습니다.
# CDN으로 사용하기
jsDelivrjsDelivr는 공개 GitHub 리포지토리를 별도 설정 없이 CDN으로 즉시 서빙합니다. 버전과 파일을 고르면 웹페이지에 바로 붙일 수 있는 링크와 예시 코드가 만들어집니다.
링크
예시
릴리즈 타임라인
- 2024-01-02 v2.0.2
- 2024-01-02 v2.0.1
- 2020-03-27 v2.0.0
- 2019-09-06 v2.0-beta: Sonnet 2.0 Beta release 사전 릴리즈
명령어 용어집
이 문서에서 사용된 명령어를 모아봤습니다. 낯선 명령어가 있다면 펼쳐서 확인해보세요.
pickle
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pickle
Composer 기반의 PHP 확장 프로그램 설치 도구.
더 많은 정보: <https://github.com/FriendsOfPHP/pickle#usage>.
pickle install {{extension_name}}
특정 PHP 확장 프로그램 설치:
pickle convert {{path/to/directory}}
기존 PECL 확장 구성 파일을 Pickle 구성 파일로 변환:
pickle validate {{path/to/directory}}
PECL 확장 유효성 검사:
pip install
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pip install
Install Python packages.
pip install {{package1 package2 ...}}
Install one or more packages:
pip install {{package1 package2 ...}} {{[-U|--upgrade]}}
Upgrade all specified packages to the latest version, installing any that are not already present:
pip install {{package}}=={{version}}
Install a specific version of a package:
// repository documentation
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