# Python rules should not have more than one source file.
action_spec {
  action: CHECK_FILE_COUNT
  file_count_params {
    rule_selector {
      rule_kind_regex: "^.*py(type)?(_strict)?_(binary|library|test).*$"
      generator_function_regex: "^(?!boq_header)$"
    }
    max_source_count: 1
  }

    "//tensorflow/tools/lib_package:clicenses_generate"
}

@test "Java library generated license includes all dependencies' licenses" {
  do_external_licenses_check \
    "//tensorflow/java:libtensorflow_jni.so" \
    "//tensorflow/tools/lib_package:jnilicenses_generate"
}

# This test ensures that all the targets built into the Python package include
# their dependencies. It's a rewritten version of the "smoke test", an older

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",
)
load("//tensorflow/python/tools/api/generator2:generate_api.bzl", "generate_apis")

    "//tensorflow/tools/lib_package:clicenses_generate"
}

@test "Java library generated license includes all dependencies' licenses" {
  do_external_licenses_check \
    "//tensorflow/java:libtensorflow_jni.so" \
    "//tensorflow/tools/lib_package:jnilicenses_generate"
}

# This test ensures that all the targets built into the Python package include
# their dependencies. It's a rewritten version of the "smoke test", an older

    *   `Model.fit_generator`, `Model.evaluate_generator`,
        `Model.predict_generator`, `Model.train_on_batch`,
        `Model.test_on_batch`, and `Model.predict_on_batch` methods now respect
        the `run_eagerly` property, and will correctly run using `tf.function`
        by default. Note that `Model.fit_generator`, `Model.evaluate_generator`,

Ensure you have Bazel installed and accessible from your command line.

These tests use hermetic Python. They also require a built TensorFlow wheel file
and a requirements_lock file. The requirements_lock file is generated by the
[requirements_updater](https://github.com/tensorflow/tensorflow/tree/master/ci/official/requirements_updater)
tool using the path to this wheel file.

### Hermetic Python

    # Fixes "fatal: detected dubious ownership in repository" for Docker.
    git config --system --add safe.directory '*'
    git config --system protocol.file.allow always

    # Note that you could generate a list of all the affected targets with e.g.:
    # bazel query $(paste -sd "+" $BATS_FILE_TMPDIR/changed_files) --keep_going
    # Only shows Added, Changed, Modified, Renamed, and Type-changed files

    required: true

-   type: textarea id: code-to-reproduce attributes: label: Standalone code to
    reproduce the issue description: Provide a reproducible test case that is
    the bare minimum necessary to generate the problem. If possible, please
    share a link to Colab/Jupyter/any notebook. placeholder: Tell us what you
    see! value: render: shell validations: required: true

- Google Play Services version
  (`Settings` > `Apps` > `Google Play Services` > `App details`):

**Standalone code to reproduce the issue**
Provide a reproducible test case that is the bare minimum necessary to generate
the problem. If possible, please share a link to or attach code demonstrating
the problem.

**Any other info / logs**
Include any logs or source code that would be helpful to diagnose the problem.

- Provide links to your TensorFlow model and (optionally) TensorFlow Lite Model.
```

### 3. Failure after conversion
If the conversion is successful, but the generated model is wrong, then state what is wrong:

- Model produces wrong results and/or has lesser accuracy.
- Model produces correct results, but it is slower than expected.

### 4. (optional) RNN conversion support