fix wrong path in some doc (#25658)

* update

* check

---------

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

docs/source/en/testing.md

@@ -112,7 +112,7 @@ pytest tests/test_optimization.py --collect-only -q
 To run an individual test module:
 
 ```bash
-pytest tests/test_logging.py
+pytest tests/utils/test_logging.py
 ```
 
 ### Run specific tests
@@ -432,14 +432,14 @@ pytest --instafail
 On a GPU-enabled setup, to test in CPU-only mode add `CUDA_VISIBLE_DEVICES=""`:
 
 ```bash
-CUDA_VISIBLE_DEVICES="" pytest tests/test_logging.py
+CUDA_VISIBLE_DEVICES="" pytest tests/utils/test_logging.py
 ```
 
 or if you have multiple gpus, you can specify which one is to be used by `pytest`. For example, to use only the
 second gpu if you have gpus `0` and `1`, you can run:
 
 ```bash
-CUDA_VISIBLE_DEVICES="1" pytest tests/test_logging.py
+CUDA_VISIBLE_DEVICES="1" pytest tests/utils/test_logging.py
 ```
 
 This is handy when you want to run different tasks on different GPUs.
@@ -515,14 +515,14 @@ n_gpu = get_gpu_count()  # works with torch and tf
 
 To run the test suite on a specific torch device add `TRANSFORMERS_TEST_DEVICE="$device"` where `$device` is the target backend. For example, to test on CPU only:
 ```bash
-TRANSFORMERS_TEST_DEVICE="cpu" pytest tests/test_logging.py
+TRANSFORMERS_TEST_DEVICE="cpu" pytest tests/utils/test_logging.py
 ```
 
 This variable is useful for testing custom or less common PyTorch backends such as `mps`. It can also be used to achieve the same effect as `CUDA_VISIBLE_DEVICES` by targeting specific GPUs or testing in CPU-only mode.
 
 Certain devices will require an additional import after importing `torch` for the first time. This can be specified using the environment variable `TRANSFORMERS_TEST_BACKEND`:
 ```bash
-TRANSFORMERS_TEST_BACKEND="torch_npu" pytest tests/test_logging.py
+TRANSFORMERS_TEST_BACKEND="torch_npu" pytest tests/utils/test_logging.py
 ```
 
 
@@ -553,7 +553,7 @@ according captured output will usually be shown along with the failure traceback
 To disable output capturing and to get the `stdout` and `stderr` normally, use `-s` or `--capture=no`:
 
 ```bash
-pytest -s tests/test_logging.py
+pytest -s tests/utils/test_logging.py
 ```
 
 To send test results to JUnit format output:
@@ -567,7 +567,7 @@ py.test tests --junitxml=result.xml
 To have no color (e.g., yellow on white background is not readable):
 
 ```bash
-pytest --color=no tests/test_logging.py
+pytest --color=no tests/utils/test_logging.py
 ```
 
 ### Sending test report to online pastebin service
@@ -575,7 +575,7 @@ pytest --color=no tests/test_logging.py
 Creating a URL for each test failure:
 
 ```bash
-pytest --pastebin=failed tests/test_logging.py
+pytest --pastebin=failed tests/utils/test_logging.py
 ```
 
 This will submit test run information to a remote Paste service and provide a URL for each failure. You may select
@@ -584,7 +584,7 @@ tests as usual or add for example -x if you only want to send one particular fai
 Creating a URL for a whole test session log:
 
 ```bash
-pytest --pastebin=all tests/test_logging.py
+pytest --pastebin=all tests/utils/test_logging.py
 ```
 
 ## Writing tests
@@ -1214,7 +1214,7 @@ tf.random.set_seed(seed)
 To start a debugger at the point of the warning, do this:
 
 ```bash
-pytest tests/test_logging.py -W error::UserWarning --pdb
+pytest tests/utils/test_logging.py -W error::UserWarning --pdb
 ```
 
 ## Working with github actions workflows

docs/source/ko/testing.md

@@ -112,7 +112,7 @@ pytest tests/test_optimization.py --collect-only -q
 개별 테스트 모듈 실행하기:
 
 ```bash
-pytest tests/test_logging.py
+pytest tests/utils/test_logging.py
 ```
 
 ### 특정 테스트 실행[[run-specific-tests]]
@@ -432,14 +432,14 @@ pytest --instafail
 GPU가 활성화된 환경에서, CPU 전용 모드로 테스트하려면 `CUDA_VISIBLE_DEVICES=""`를 추가합니다:
 
 ```bash
-CUDA_VISIBLE_DEVICES="" pytest tests/test_logging.py
+CUDA_VISIBLE_DEVICES="" pytest tests/utils/test_logging.py
 ```
 
 또는 다중 GPU가 있는 경우 `pytest`에서 사용할 GPU를 지정할 수도 있습니다. 
 예를 들어, GPU `0` 및 `1`이 있는 경우 다음을 실행할 수 있습니다:
 
 ```bash
-CUDA_VISIBLE_DEVICES="1" pytest tests/test_logging.py
+CUDA_VISIBLE_DEVICES="1" pytest tests/utils/test_logging.py
 ```
 
 이렇게 하면 다른 GPU에서 다른 작업을 실행하려는 경우 유용합니다.
@@ -538,7 +538,7 @@ CUDA_VISIBLE_DEVICES=0,1 RUN_SLOW=1 pytest -sv tests/test_trainer_distributed.py
 출력 캡처를 비활성화하고 `stdout` 및 `stderr`를 정상적으로 받으려면 `-s` 또는 `--capture=no`를 사용하세요:
 
 ```bash
-pytest -s tests/test_logging.py
+pytest -s tests/utils/test_logging.py
 ```
 
 테스트 결과를 JUnit 형식의 출력으로 보내려면 다음을 사용하세요:
@@ -552,7 +552,7 @@ py.test tests --junitxml=result.xml
 색상이 없게 하려면 다음과 같이 설정하세요(예를 들어 흰색 배경에 노란색 글씨는 가독성이 좋지 않습니다):
 
 ```bash
-pytest --color=no tests/test_logging.py
+pytest --color=no tests/utils/test_logging.py
 ```
 
 ### online pastebin service에 테스트 보고서 전송[[sending test report to online pastebin service]]
@@ -560,7 +560,7 @@ pytest --color=no tests/test_logging.py
 각 테스트 실패에 대한 URL을 만듭니다:
 
 ```bash
-pytest --pastebin=failed tests/test_logging.py
+pytest --pastebin=failed tests/utils/test_logging.py
 ```
 
 이렇게 하면 각 실패에 대한 URL을 제공하는 remote Paste service에 테스트 실행 정보를 제출합니다. 
@@ -569,7 +569,7 @@ pytest --pastebin=failed tests/test_logging.py
 전체 테스트 세션 로그에 대한 URL을 생성합니다:
 
 ```bash
-pytest --pastebin=all tests/test_logging.py
+pytest --pastebin=all tests/utils/test_logging.py
 ```
 
 ## 테스트 작성[[writing-tests]]
@@ -1199,7 +1199,7 @@ tf.random.set_seed(seed)
 경고가 있는 곳에서 디버거를 시작하려면 다음을 수행하세요.
 
 ```bash
-pytest tests/test_logging.py -W error::UserWarning --pdb
+pytest tests/utils/test_logging.py -W error::UserWarning --pdb
 ```
 
 ## Github Actions 워크플로우 작업 처리[[working-with-github-actions-workflows]]

utils/not_doctested.txt

@@ -315,7 +315,6 @@ docs/source/en/tasks/visual_question_answering.md
 docs/source/en/tasks/zero_shot_image_classification.md
 docs/source/en/tasks/zero_shot_object_detection.md
 docs/source/en/tasks_explained.md
-docs/source/en/testing.md
 docs/source/en/tf_xla.md
 docs/source/en/tflite.md
 docs/source/en/tokenizer_summary.md