chore: import upstream snapshot with attribution

2026-07-13 12:59:13 +08:00
commit f2d31077b9
1276 changed files with 194291 additions and 0 deletions
@@ -0,0 +1,152 @@
+import json
+import re
+import pprint
+import requests
+
+def update_contributors():
+    """
+    Update contributors' task numbers and sort them based on contribution.
+
+    This function:
+    - Reads the support_model.md, support_model_amd.md, and support_model_Ascend.md to extract tasks
+    - Counts contribution points (2 for LoRA tasks, 1 for regular tasks)
+    - Adds special contributor points
+    - Sorts contributors by their contribution points
+    - Saves the updated data to JSON file
+    - Prints contributor information
+
+    Returns:
+        dict: Updated contributors information
+    """
+    # Read files
+    with open('./support_model.md', 'r') as f:
+        readme = f.read()
+
+    with open('./support_model_amd.md', 'r') as f:
+        readme_amd = f.read()
+
+    with open('./support_model_Ascend.md', 'r') as f:
+        readme_ascend = f.read()
+
+    with open('./contributors.json', 'r') as f:
+        contributors = json.load(f)
+
+    # Reset task counts
+    keys = contributors.keys()
+    for key in keys:
+        contributors[key]['task_num'] = 0
+
+    # Extract tasks from main support_model.md
+    tasks = readme.split('\n')
+    tasks = [task for task in tasks if '@' in task][:-1]
+
+    # Extract tasks from AMD support_model_amd.md
+    tasks_amd = readme_amd.split('\n')
+    tasks_amd = [task for task in tasks_amd if '@' in task]
+
+    # Extract tasks from Ascend support_model_Ascend.md
+    tasks_ascend = readme_ascend.split('\n')
+    tasks_ascend = [task for task in tasks_ascend if '@' in task]
+
+    # Combine all tasks
+    all_tasks = tasks + tasks_amd + tasks_ascend
+
+    # Count points: LoRA tasks +2, regular tasks +1
+    for task in all_tasks:
+        if '@' not in task:
+            continue
+        name = task.split('@')[1]
+        if name not in keys:
+            continue
+        # Check if the task contains "Lora" or "微调" (case-insensitive)
+        if "Lora" in task or "微调" in task:
+            contributors[name]['task_num'] += 2
+        else:
+            contributors[name]['task_num'] += 1
+
+    # Add special contributor points
+    special_contributors = {
+        '不要葱姜蒜': 300,
+        'Logan Zou': 300,
+        '刘十一': 150,
+    }
+    for name, points in special_contributors.items():
+        if name in contributors:
+            contributors[name]['task_num'] += points
+
+    # Sort by contribution points
+    contributors = dict(sorted(contributors.items(), key=lambda x: x[1]['task_num'], reverse=True))
+
+    # Save results
+    with open('./contributors.json', 'w') as f:
+        json.dump(contributors, f, indent=4, ensure_ascii=False)
+
+    # Print results
+    for key, value in contributors.items():
+        print(f'- {value["info"]}')
+
+    return contributors
+
+
+def calculate_docker_hours():
+    """
+    Calculate and display Docker runtime hours from CodeWithGPU API.
+    Fetches data from Datawhale account, calculates total runtime hours,
+    and displays sorted information about each container.
+    """
+    url = "https://www.codewithgpu.com/api/v1/image/home/Datawhale?page_index=1&page_size=100&username=Datawhale"
+
+    headers = {
+        "accept": "application/json, text/plain, */*",
+        "accept-language": "zh-CN,zh;q=0.9",
+        "User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/135.0.0.0 Safari/537.36",
+    }
+
+    total_hours = 0
+    docker_list = []
+
+    response = requests.get(url, headers=headers)
+    if response.status_code == 200:
+        data = response.json()
+        if data['code'] == "Success":
+            item_list = data['data']['list']
+            for item in item_list:
+                uuid = item['uuid']
+                runtime_hour = item['runtime_hour']
+
+                if runtime_hour is not None:
+                    total_hours += runtime_hour
+                    docker_list.append({
+                        "uuid": uuid.split("/")[-1],
+                        "runtime_hour": runtime_hour
+                    })
+        else:
+            print(f"Error: {data['message']}")
+
+    print(f"\n{'='*60}")
+    print(f"{' DOCKER RUNTIME SUMMARY ':^60}")
+    print(f"{'='*60}")
+    print(f"{'Total Containers:':<20} {len(docker_list):>10}")
+    print(f"{'Total Runtime:':<20} {total_hours:>10.1f} hours")
+
+    if docker_list:
+        print(f"{'='*60}")
+        print(f"{' DOCKER CONTAINERS (Sorted by Runtime) ':^60}")
+        print(f"{'='*60}")
+        print(f"{'Rank':<6} {'UUID':<35} {'Runtime (hours)':>15}")
+        print(f"{'-'*6}-{'-'*35}-{'-'*15}")
+        
+        docker_list = sorted(docker_list, key=lambda x: x['runtime_hour'], reverse=True)
+        for i, item in enumerate(docker_list, 1):
+            print(f"{i:<6} {item['uuid']:<35} {item['runtime_hour']:>15.1f}")
+        print(f"{'='*60}")
+    else:
+        print("No Docker containers found.")
+    
+    return docker_list, total_hours
+
+
+# Usage example
+if __name__ == "__main__":
+    update_contributors()
+    calculate_docker_hours()