--experimental_cc_shared_library \
    --@local_config_cuda//:enable_cuda \
    --define framework_shared_object=false \
    "somepath(//tensorflow/tools/pip_package:build_pip_package, " \
    "@local_config_cuda//cuda:cudart + "\
    "@local_config_cuda//cuda:cudart + "\
    "@local_config_cuda//cuda:cuda_driver + "\
    "@local_config_cuda//cuda:cudnn + "\
    "@local_config_cuda//cuda:curand + "\
    "@local_config_cuda//cuda:cusolver + "\

    --@local_config_cuda//:enable_cuda \
    --define framework_shared_object=false \
    "somepath(//tensorflow/tools/pip_package:wheel, " \
    "@local_config_cuda//cuda:cudart + "\
    "@local_config_cuda//cuda:cudart + "\
    "@local_config_cuda//cuda:cuda_driver + "\
    "@local_config_cuda//cuda:cudnn + "\
    "@local_config_cuda//cuda:curand + "\
    "@local_config_cuda//cuda:cusolver + "\

load(
    "//tensorflow:tensorflow.bzl",
    "check_deps",
    "if_google",
    "if_not_mobile",
    "tf_cc_test",
    "tf_copts",
    "tf_cuda_library",
    "tf_custom_op_library",
    "tf_kernel_library",
)
load("//tensorflow:tensorflow.default.bzl", "filegroup", "tf_cuda_cc_test")
load(
    "//tensorflow/core/tpu:build_defs.bzl",
    "if_libtpu_tf_status",
)

package(

load(
    "//tensorflow:tensorflow.bzl",
    "tf_cc_test",
    "tf_copts",
    "tf_cuda_cc_test",
    "tf_cuda_library",
)
load("//tensorflow:tensorflow.default.bzl", "cc_header_only_library", "filegroup")
load(
    "//tensorflow/core/platform:build_config_root.bzl",
    "tf_cuda_tests_tags",
)
load("//tensorflow/core/platform:rules_cc.bzl", "cc_library")

package(

    export flags="--config=opt -k"
    ```

    If the tests are to be run on the GPU, add CUDA paths to LD_LIBRARY_PATH and
    add the `cuda` option flag

    ```bash
    export LD_LIBRARY_PATH="${LD_LIBRARY_PATH}:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH"
    export flags="--config=opt --config=cuda -k"
    ```

    For example, to run all tests under tensorflow/python, do:

    ```bash

3. Copie o arquivo com os requisitos para o diretório `/code`.

    Copie **somente** o arquivo com os requisitos primeiro, não o resto do código.

    Como esse arquivo **não muda com frequência**, o Docker irá detectá-lo e usar o **cache** para esse passo, habilitando o cache para o próximo passo também.

4. Instale as dependências de pacote vindas do arquivo de requisitos.

[Docker container](https://www.tensorflow.org/install/docker), and
[build from source](https://www.tensorflow.org/install/source).

To install the current release, which includes support for
[CUDA-enabled GPU cards](https://www.tensorflow.org/install/gpu) *(Ubuntu and
Windows)*:

```
$ pip install tensorflow
```

Other devices (DirectX and MacOS-metal) are supported using

pkg debug/elf, const EM_CRX = 114
pkg debug/elf, const EM_CRX Machine
pkg debug/elf, const EM_CSR_KALIMBA = 219
pkg debug/elf, const EM_CSR_KALIMBA Machine
pkg debug/elf, const EM_CUDA = 190
pkg debug/elf, const EM_CUDA Machine
pkg debug/elf, const EM_CYPRESS_M8C = 161
pkg debug/elf, const EM_CYPRESS_M8C Machine
pkg debug/elf, const EM_D10V = 85
pkg debug/elf, const EM_D10V Machine
pkg debug/elf, const EM_D30V = 86

    sdkmanager 'build-tools;27.0.3';

# Install Scoop and packages
RUN iex \"& {$(irm get.scoop.sh)} -RunAsAdmin\"; \
    scoop install perl; \
    scoop install bazel; \
    scoop install cuda; \
    scoop install azure-functions-core-tools; \
    scoop install azure-cli;

# Setting environment variables
RUN [Environment]::SetEnvironmentVariable('CYGWIN', 'winsymlinks:native', 'Machine'); \

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