TF_DeleteStatus(s);
}

void Deallocator(void* data, size_t, void* arg) {
  tensorflow::cpu_allocator()->DeallocateRaw(data);
  *reinterpret_cast<bool*>(arg) = true;
}

TEST(CAPI, Tensor) {
  const int num_bytes = 6 * sizeof(float);
  float* values =
      reinterpret_cast<float*>(tensorflow::cpu_allocator()->AllocateRaw(
          TF_TensorDefaultAlignment(), num_bytes));
  int64_t dims[] = {2, 3};

      - name: Build and test pip wheel
        shell: bash
        run: |
          is_nightly=0 && tf_project_name='tensorflow_cpu_aws' && ${{ github.event_name == 'schedule' }} && is_nightly=1 && tf_project_name='tf_nightly_cpu_aws'
          echo "PyPI project name:" $tf_project_name

)

config_setting(
    name = "linux_aarch64",
    values = {"cpu": "aarch64"},
    visibility = ["//visibility:public"],
)

config_setting(
    name = "linux_armhf",
    values = {"cpu": "armhf"},
    visibility = ["//visibility:public"],
)

config_setting(
    name = "linux_x86_64",
    values = {"cpu": "k8"},
    visibility = ["//visibility:public"],
)

config_setting(

```bash
tensorflow/tools/ci_build/ci_build.sh CPU tensorflow/tools/ci_build/ci_sanity.sh
```

This will catch most license, Python coding style and BUILD file issues that
may exist in your changes.

#### Running unit tests

There are two ways to run TensorFlow unit tests.

1.  Using tools and libraries installed directly on your system.

    Refer to the

          ./tensorflow/tools/ci_build/ci_build.sh cpu.arm64 bash tensorflow/tools/ci_build/rel/ubuntu/cpu_arm64_test.sh...

            ":tf_attrtype",
            "//tensorflow/core:core_cpu",
            "//tensorflow/core:framework",
            "//tensorflow/core:lib",
            "//tensorflow/core/platform:platform",
        ],
        "//conditions:default": [
            ":tf_attrtype",
            "//tensorflow/core:core_cpu",
            "//tensorflow/core:framework",
            "//tensorflow/core:lib",

build:android_arm64 --config=android
build:android_arm64 --cpu=arm64-v8a
build:android_arm64 --fat_apk_cpu=arm64-v8a
build:android_x86 --config=android
build:android_x86 --cpu=x86
build:android_x86 --fat_apk_cpu=x86
build:android_x86_64 --config=android
build:android_x86_64 --cpu=x86_64
build:android_x86_64 --fat_apk_cpu=x86_64

# Build everything statically for Android since all static libs are later

    flags->tf_xla_cpu_global_jit = true;
    flags->tf_xla_min_cluster_size = 1;
  } else {
    optimizer_options->set_global_jit_level(tensorflow::OptimizerOptions::OFF);
  }

  auto* gpu_options = config.mutable_gpu_options();
  gpu_options->set_allow_growth(gpu_memory_allow_growth);

  (*config.mutable_device_count())["CPU"] = num_cpu_devices;

        *   `tf.raw_ops.Bucketize` op on CPU.
        *   `tf.where` op for data types
            `tf.int32`/`tf.uint32`/`tf.int8`/`tf.uint8`/`tf.int64`.
        *   `tf.random.normal` op for output data type `tf.float32` on CPU.
        *   `tf.random.uniform` op for output data type `tf.float32` on CPU.
        *   `tf.random.categorical` op for output data type `tf.int64` on CPU.

*   `tensorflow.experimental.tensorrt`:

            "//tensorflow/c:tf_buffer_internal",
            "//tensorflow/c:tf_status_internal",
            "//tensorflow/c:tf_tensor_internal",
            "//tensorflow/core:core_cpu",
            "//tensorflow/core:core_cpu_internal",
            "//tensorflow/core:framework",
            "//tensorflow/core:framework_internal",
            "//tensorflow/core:lib",
            "//tensorflow/core:lib_internal",