Windows host writes sm_train.sh with CRLF in SDK v3, causing SageMaker training job bootstrap failure ($'\r': command not found)

**PySDK Version**
- [ ] PySDK V2 (2.x)
- [x] PySDK V3 (3.x)

**Describe the bug**
When launching a SageMaker training job from Windows using `sagemaker.train.ModelTrainer` (SDK v3), the generated bootstrap script `sm_train.sh` is written with CRLF line endings. Inside the Linux training container, bash fails to parse it and the job exits before user training code starts.

The script appears to be written in `sagemaker/train/model_trainer.py` with:

`with open(os.path.join(tmp_dir.name, TRAIN_SCRIPT), "w") as f:`

which applies platform newline conversion on Windows (`\r\n`).

**To reproduce**
1. Use Windows host with SageMaker Python SDK v3.
2. Run this complete script (replace `ROLE_ARN` and `S3_INPUT`):

```python
from sagemaker.core import image_uris
from sagemaker.core.helper.session_helper import Session
from sagemaker.core.training.configs import SourceCode, Compute, InputData
from sagemaker.train import ModelTrainer

session = Session()
region = session.boto_region_name

training_image = image_uris.retrieve(
framework="pytorch",
region=region,
version="2.4.0",
py_version="py311",
instance_type="ml.g4dn.xlarge",
image_scope="training",
)

trainer = ModelTrainer(
sagemaker_session=session,
role="ROLE_ARN",
training_image=training_image,
source_code=SourceCode(
source_dir=".",
entry_script="sagemaker_entry.py",
requirements="requirements/sagemaker_train.txt",
),
compute=Compute(instance_type="ml.g4dn.xlarge", instance_count=1),
)

trainer.train(
input_data_config=[InputData(channel_name="train", data_source="S3_INPUT")],
wait=True,
logs=True,
)
```

3. Check CloudWatch logs for the training job.

**Expected behavior**
`sm_train.sh` should be written with LF (`\n`) and execute correctly in the Linux container, allowing the training entry point to start.

**Screenshots or logs**
Observed logs:

```text
/opt/ml/input/data/sm_drivers/sm_train.sh: line 1: $'\r': command not found
Starting training script#015
/opt/ml/input/data/sm_drivers/sm_train.sh: line 3: set: -#015: invalid option
set: usage: set [-abefhkmnptuvxBCHP] [-o option-name] [--]
/opt/ml/input/data/sm_drivers/sm_train.sh: line 5: $'\r': command not found
/opt/ml/input/data/sm_drivers/sm_train.sh: line 6: syntax error near unexpected token `$'{\r''
/opt/ml/input/data/sm_drivers/sm_train.sh: line 6: `handle_error() {#015'
```

**System information**
- **SageMaker Python SDK version**: 3.12.0
- **Framework name (eg. PyTorch) or algorithm (eg. KMeans)**: PyTorch
- **Framework version**: 2.4.0 (DLC)
- **Python version**: 3.11
- **CPU or GPU**: GPU (`ml.g4dn.xlarge`)
- **Custom Docker image (Y/N)**: N

**Additional context**
- Reproduced from Windows 10 host.
- Workaround: launching from Linux (WSL/Studio/EC2) avoids CRLF in `sm_train.sh`.
- Suggested fix in SDK: force LF on script write, e.g. `open(..., "w", newline="\n")`.

Kiểm tra code ghi script trong sagemaker/train/model_trainer.py, đặc biệt là lệnh gọi open được hiển thị trong issue, và tái tạo file được tạo trên Windows. Được xem là hoàn tất khi sm_train.sh chứa ký tự kết thúc dòng LF và log của container SageMaker cho thấy entry point của quá trình training khởi động mà không có các lỗi phân tích cú pháp bash đã nêu.

Do mô hình lập chỉ mục viết ra từ nội dung của issue.