"//tensorflow/core/transforms:__subpackages__",
    ],
    deps = [
        ":c_api_macros_hdrs",
        "@local_tsl//tsl/platform:status",
        "@local_xla//xla/tsl/c:tsl_status",
        "@local_xla//xla/tsl/c:tsl_status_internal",
    ] + select({
        "//tensorflow:android": [
            "//tensorflow/core:portable_tensorflow_lib_lite",  # TODO(annarev): exclude runtime srcs
        ],

WIP ML Build Docker container for ML repositories (Tensorflow, JAX and XLA).

This container branches off from
/tensorflow/tools/tf_sig_build_dockerfiles/. However, since
hermetic CUDA and hermetic Python is now available for Tensorflow, a lot of the
requirements installed on the original container can be removed to reduce the
footprint of the container and make it more reusable across different ML

        [],
        otherwise = [
            "@local_xla//xla/stream_executor/cuda:all_runtime",
            "@local_xla//xla/stream_executor/cuda:cuda_driver",
            "@local_xla//xla/stream_executor/cuda:cuda_platform",
            "@local_xla//xla/stream_executor/cuda:cudnn_plugin",
            "@local_xla//xla/stream_executor/cuda:cufft_plugin",
            "@local_xla//xla/stream_executor:cuda_platform",
        ],
    ),

#include "tensorflow/c/eager/tfe_context_internal.h"
#include "tensorflow/c/tf_buffer.h"
#include "tensorflow/c/tf_datatype.h"
#include "tensorflow/c/tf_status.h"
#include "xla/tsl/lib/core/status_test_util.h"
#include "tensorflow/core/common_runtime/eager/context.h"
#include "tensorflow/core/framework/cancellation.h"
#include "tensorflow/core/framework/function.h"

#     --config=dbg --per_file_copt=+tensorflow/core/kernels/identity_op.*@-g
# Since this .bazelrc file is synced between the tensorflow/tensorflow repo and
# the openxla/xla repo, also include debug info for files under xla/.
build:dbg --per_file_copt=+.*,-tensorflow.*,-xla.*@-g0
build:dbg --per_file_copt=+tensorflow/core/kernels.*@-g0
# for now, disable arm_neon. see: https://github.com/tensorflow/tensorflow/issues/33360

  auto* optimizer_options =
      config.mutable_graph_options()->mutable_optimizer_options();
  if (enable) {
    optimizer_options->set_global_jit_level(tensorflow::OptimizerOptions::ON_1);

    // These XLA flags are needed to trigger XLA properly from C (more generally
    // non-Python) clients. If this API is called again with `enable` set to
    // false, it is safe to keep these flag values as is.
    tensorflow::MarkForCompilationPassFlags* flags =

reachable and exploitable through production-grade, benign models.

### Compilation

Compiling models via the recommended entry points described in
[XLA](https://www.tensorflow.org/xla) and
[JAX](https://jax.readthedocs.io/en/latest/jax-101/02-jitting.html)
documentation should be safe, while some of the testing and debugging tools that

</div>

/// note

Câu lệnh `uvicorn main:app` được giải thích như sau:

* `main`: tệp tin `main.py` (một Python "mô đun").
* `app`: một object được tạo ra bên trong `main.py` với dòng `app = FastAPI()`.
* `--reload`: làm server khởi động lại sau mỗi lần thay đổi. Chỉ sử dụng trong môi trường phát triển.

///

Trong output, có một dòng giống như:

```hl_lines="4"
INFO:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)

#include "tensorflow/c/eager/tfe_tensorhandle_internal.h"
#include "tensorflow/c/tf_status.h"
#include "tensorflow/c/tf_status_helper.h"
#include "xla/tsl/c/tsl_status_internal.h"
#include "xla/tsl/distributed_runtime/coordination/coordination_service_agent.h"
#include "xla/tsl/framework/cancellation.h"
#include "tensorflow/core/common_runtime/composite_device.h"
#include "tensorflow/core/common_runtime/device.h"

```Python
    first_name="john", last_name="doe"
```

Nó là một thứ khác.

Chúng ta sử dụng dấu hai chấm (`:`), không phải dấu bằng (`=`).

Và việc thêm gợi ý kiểu dữ liệu không làm thay đổi những gì xảy ra so với khi chưa thêm chúng.

But now, imagine you are again in the middle of creating that function, but with type hints.

Tại cùng một điểm, bạn thử kích hoạt autocomplete với `Ctrl+Space` và bạn thấy: