nvidia-cublas-cu12>=12.5.3.2,<13.0
nvidia-cuda-cupti-cu12>=12.5.82,<13.0
nvidia-cuda-nvcc-cu12>=12.5.82,<13.0
nvidia-cuda-nvrtc-cu12>=12.5.82,<13.0
nvidia-cuda-runtime-cu12>=12.5.82,<13.0
# The upper bound is set for the CUDNN API compatibility.
# See
# https://docs.nvidia.com/deeplearning/cudnn/backend/latest/developer/forward-compatibility.html#cudnn-api-compatibility
nvidia-cudnn-cu12>=9.3.0.75,<10.0
nvidia-cufft-cu12>=11.2.3.61,<12.0

    write_repo_env_to_bazelrc('cuda', env_var, local_path)


def set_other_cuda_vars(environ_cp):
  """Set other CUDA related variables."""
  # If CUDA is enabled, always use GPU during build and test.
  if environ_cp.get('TF_CUDA_CLANG') == '1':
    write_to_bazelrc('build --config=cuda_clang')
  else:
    write_to_bazelrc('build --config=cuda')

    done < $BATS_TEST_TMPDIR/missing_deps
    exit 1
  fi
}

# The Python package is not allowed to depend on any CUDA packages.
@test "Pip package doesn't depend on CUDA" {
  bazel cquery \
    --experimental_cc_shared_library \
    --@local_config_cuda//:enable_cuda \
    --@local_config_cuda//cuda:include_cuda_libs=false \

export DEBIAN_FRONTEND=noninteractive

# Fetch the NVIDIA key.
apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/3bf863cc.pub;

# Set up sources for NVIDIA CUDNN.
cat >/etc/apt/sources.list.d/nvidia.list <<SOURCES
# NVIDIA
deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/ /

# Tutorial - Pedoman Pengguna - Pengenalan

Tutorial ini menunjukan cara menggunakan ***FastAPI*** dengan semua fitur-fiturnya, tahap demi tahap.

Setiap bagian dibangun secara bertahap dari bagian sebelumnya, tetapi terstruktur untuk memisahkan banyak topik, sehingga kamu bisa secara langsung menuju ke topik spesifik untuk menyelesaikan kebutuhan API tertentu.

Ini juga dibangun untuk digunakan sebagai referensi yang akan datang.

,CAA9C,oBAAkBzN,OAAlB,IAIZ0N,EAAY5I,EAAOgC,KAAPhC,CAAa,SAAbA,EAAwBoB,GAAxBpB,CAA4B,kBAAQ6I,GAAKC,IAALD,EAApC,CAAA7I,EAIZ+I,EAAUH,EAAU1N,OAAV0N,CACdxF,IAAgB,kBAAgC,CAAC,CAAzByF,KAAKG,MAALH,CAAY,MAAZA,CAAxB,CAAAzF,CADcwF,EAIZA,MAA0D,CAAC,CAArCA,QAAmB1N,OAAnB0N,CAA2B,GAA3BA,CAlB1B,UAmBU7E,KACN,+EApBJ,IA0BMkF,GAAa,cACfC,EAAkB,CAAC,CAAbH,KASN,GATMA,CACN,CACEH,EACG/E,KADH+E,CACS,CADTA,IAEGL,MAFHK,CAEU,CAACA,KAAmB5G,KAAnB4G,IAAqC,CAArCA,CAAD,CAFVA,CADF,CAIE,CAACA,KAAmB5G,KAAnB4G,IAAqC,CAArCA,CAAD,EAA0C...

# Config setting that is satisfied when TensorFlow is being built with CUDA
# support through e.g. `--config=cuda` (or `--config=cuda_clang` in OSS).
alias(
    name = "is_cuda_enabled",
    actual = if_oss(
        "@local_config_cuda//:is_cuda_enabled",
        "@local_config_cuda//cuda:using_config_cuda",
    ),
)

# Config setting that is satisfied when CUDA device code should be compiled

C3BpQ,IAAK,SAAUP,GAId,IAAI8O,EAAS9O,EAAKb,WAIlB,OAHK2P,GAAUA,EAAO3P,YACrB2P,EAAO3P,WAAWyR,cAEZ,MAERgN,IAAK,SAAU5d,GAId,IAAI8O,EAAS9O,EAAKb,WACb2P,IACJA,EAAO8B,cAEF9B,EAAO3P,YACX2P,EAAO3P,WAAWyR,kBAOvBpR,GAAOsB,KAAM,CACZ,WACA,WACA,YACA,cACA,cACA,UACA,UACA,SACA,cACA,mBACE,WACFtB,GAAOk7B,QAASn+B,KAAK2D,eAAkB3D,OA4BxCiD,GAAOG,GAAGmC,OAAQ,CACjBg5B,SAAU,SAAUx2B,GACnB,IAAIy2B,EAAY5kB,EAAK6kB,EAAUxuB,EAAW9N,EAAGu8B,EAE7C,OAAKr9B,EAAY0G,GACT/H,KAAKuE,KAAM,SAAUY,GAC3BlC,GAAQjD,MAAOu+B,SAAUx2B,EAAMtH,KAAMT...

      description: If compiling from source
  - type: input
    id: Compiler
    attributes:
      label: GCC/compiler version
      description: If compiling from source
  - type: input
    id: Cuda
    attributes:
      label: CUDA/cuDNN version
  - type: input
    id: Gpu
    attributes:
      label: GPU model and memory
      description: If compiling from source
  - type: textarea
    id: what-happened

These "env" files match up with an environment matrix that roughly covers:

-   Different Python versions
-   Linux, MacOS, and Windows machines (these pool definitions are internal)
-   x86 and arm64
-   CPU-only, or with NVIDIA CUDA support (Linux only), or with TPUs

## How to Test Your Changes to TensorFlow

You may check how your changes will affect TensorFlow by:

1. Creating a PR and observing the presubmit test results