# /// script
# requires-python = ">=3.12"
# dependencies = [
#     "torch",
#     "torchvision",
#     "transformers",
#     "diffusers",
#     "sentence-transformers",
#     "accelerate",
#     "peft",
#     "slack-sdk",
# ]
# ///

try:
    import torch
    from sentence_transformers import SentenceTransformer
    
    device = "cuda" if torch.cuda.is_available() else "cpu"
    
    model_id = "google/embeddinggemma-300M"
    model = SentenceTransformer(model_id).to(device=device)
    
    print(f"Device: {model.device}")
    print(model)
    print("Total number of parameters in the model:", sum([p.numel() for _, p in model.named_parameters()]))
    with open('google_embeddinggemma-300m_2.txt', 'w', encoding='utf-8') as f:
        f.write('Everything was good in google_embeddinggemma-300m_2.txt')
except Exception as e:
    import os
    from slack_sdk import WebClient
    client = WebClient(token=os.environ['SLACK_TOKEN'])
    client.chat_postMessage(
        channel='#hub-model-metadata-snippets-sprint',
        text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/google_embeddinggemma-300m_2.txt|google_embeddinggemma-300m_2.txt>',
    )

    with open('google_embeddinggemma-300m_2.txt', 'a', encoding='utf-8') as f:
        import traceback
        f.write('''```CODE: 
import torch
from sentence_transformers import SentenceTransformer

device = "cuda" if torch.cuda.is_available() else "cpu"

model_id = "google/embeddinggemma-300M"
model = SentenceTransformer(model_id).to(device=device)

print(f"Device: {model.device}")
print(model)
print("Total number of parameters in the model:", sum([p.numel() for _, p in model.named_parameters()]))
```

ERROR: 
''')
        traceback.print_exc(file=f)
    
finally:
    from huggingface_hub import upload_file
    upload_file(
        path_or_fileobj='google_embeddinggemma-300m_2.txt',
        repo_id='model-metadata/code_execution_files',
        path_in_repo='google_embeddinggemma-300m_2.txt',
        repo_type='dataset',
    )