# BEGIN TF TEST SUITE OPTIONS
# These are convenience config options that effectively declare TF's CI test suites. Look
# at the scripts of ci/official/ to see how TF's CI uses them.

# PYTHON TESTS run a suite of Python tests intended for verifying that the Python wheel
# will work properly. These are usually run Nightly or upon Release.
# CPU WHEEL

load(
    "//tensorflow/python/tools/api/generator:api_gen.bzl",
    "get_compat_files",
    "get_nested_compat_files",
)
load(
    "//tensorflow/python/tools/api/generator:api_init_files.bzl",
    "TENSORFLOW_API_INIT_FILES",
)
load(
    "//tensorflow/python/tools/api/generator:api_init_files_v1.bzl",
    "TENSORFLOW_API_INIT_FILES_V1",
)

```

### Step 3: Test on RabbitMQ

The python program below waits on the queue exchange `bucketevents` and prints event notifications on the console. We use [Pika Python Client](https://www.rabbitmq.com/tutorials/tutorial-three-python.html) library to do this.

```py
#!/usr/bin/env python
import pika

connection = pika.BlockingConnection(pika.ConnectionParameters(

К примеру, есть официальный <a href="https://hub.docker.com/_/python" class="external-link" target="_blank">образ Python</a>.

Также там представлены и другие полезные образы, такие как базы данных:

* <a href="https://hub.docker.com/_/postgres" class="external-link" target="_blank">PostgreSQL</a>

// TF_FinishWhile() or TF_AbortWhile().
//
// Missing functionality (TODO):
// - Gradients
// - Reference-type inputs
// - Directly referencing external tensors from the cond/body graphs (this is
//   possible in the Python API)
TF_CAPI_EXPORT extern TF_WhileParams TF_NewWhile(TF_Graph* g, TF_Output* inputs,
                                                 int ninputs,
                                                 TF_Status* status);

#
# This file is autogenerated by pip-compile with Python 3.10
# by the following command:
#
#    bazel run //ci/official/requirements_updater:requirements.update
#
absl-py==2.2.2 \
    --hash=sha256:bf25b2c2eed013ca456918c453d687eab4e8309fba81ee2f4c1a6aa2494175eb \
    --hash=sha256:e5797bc6abe45f64fd95dc06394ca3f2bedf3b5d895e9da691c9ee3397d70092
    # via
    #   keras-nightly
    #   tb-nightly
astor==0.7.1 \

#
# This file is autogenerated by pip-compile with Python 3.12
# by the following command:
#
#    bazel run //ci/official/requirements_updater:requirements.update
#
absl-py==2.2.2 \
    --hash=sha256:bf25b2c2eed013ca456918c453d687eab4e8309fba81ee2f4c1a6aa2494175eb \
    --hash=sha256:e5797bc6abe45f64fd95dc06394ca3f2bedf3b5d895e9da691c9ee3397d70092
    # via
    #   keras-nightly
    #   tb-nightly
astor==0.7.1 \

#
# This file is autogenerated by pip-compile with Python 3.12
# by the following command:
#
#    bazel run //ci/official/requirements_updater:requirements.update
#
absl-py==2.2.2 \
    --hash=sha256:bf25b2c2eed013ca456918c453d687eab4e8309fba81ee2f4c1a6aa2494175eb \
    --hash=sha256:e5797bc6abe45f64fd95dc06394ca3f2bedf3b5d895e9da691c9ee3397d70092
    # via
    #   keras-nightly
    #   tb-nightly
astor==0.7.1 \

#
# This file is autogenerated by pip-compile with Python 3.11
# by the following command:
#
#    bazel run //ci/official/requirements_updater:requirements.update
#
absl-py==2.2.2 \
    --hash=sha256:bf25b2c2eed013ca456918c453d687eab4e8309fba81ee2f4c1a6aa2494175eb \
    --hash=sha256:e5797bc6abe45f64fd95dc06394ca3f2bedf3b5d895e9da691c9ee3397d70092
    # via
    #   keras-nightly
    #   tb-nightly
astor==0.7.1 \

#
# This file is autogenerated by pip-compile with Python 3.10
# by the following command:
#
#    bazel run //ci/official/requirements_updater:requirements.update
#
absl-py==2.2.2 \
    --hash=sha256:bf25b2c2eed013ca456918c453d687eab4e8309fba81ee2f4c1a6aa2494175eb \
    --hash=sha256:e5797bc6abe45f64fd95dc06394ca3f2bedf3b5d895e9da691c9ee3397d70092
    # via
    #   keras-nightly
    #   tb-nightly
astor==0.7.1 \