model file loaded dynamically from s3

localizations/zh_CN.json

@@ -840,7 +840,7 @@
     "Save Preview(s) Frequency (Epochs)": "保存预览频率 (Epochs)",
     "A generic prompt used to generate a sample image to verify model fidelity.": "用于生成样本图像以验证模型保真度的通用提示。",
     "Job detail":"训练任务详情",
-    "S3 bucket name for uploading train images":"上传训练图片集的S3桶名",
+    "S3 bucket name for uploading/downloading images":"上传训练图片集或者下载生成图片的S3桶名",
     "Output S3 folder":"S3文件夹目录",
     "Upload Train Images to S3":"上传训练图片到S3",
     "Error, please configure a S3 bucket at settings page first":"失败，请先到设置页面配置S3桶名",

modules/api/api.py

@@ -457,7 +457,7 @@ def invocations(self, req: InvocationsRequest):
             traceback.print_exc()
 
     def ping(self):
-        print('-------ping------')
+        # print('-------ping------')
         return {'status': 'Healthy'}
 
     def launch(self, server_name, port):

modules/shared.py

@@ -423,7 +423,7 @@ def refresh_sagemaker_endpoints(username):
 }))
 
 options_templates.update(options_section(('saving-paths', "Paths for saving"), {
-    "train_files_s3bucket":OptionInfo("","S3 bucket name for uploading train images",component_args=hide_dirs),
+    "train_files_s3bucket":OptionInfo("","S3 bucket name for uploading/downloading images",component_args=hide_dirs),
     "outdir_samples": OptionInfo("", "Output directory for images; if empty, defaults to three directories below", component_args=hide_dirs),
     "outdir_txt2img_samples": OptionInfo("outputs/txt2img-images", 'Output directory for txt2img images', component_args=hide_dirs),
     "outdir_img2img_samples": OptionInfo("outputs/img2img-images", 'Output directory for img2img images', component_args=hide_dirs),

modules/ui.py

@@ -86,6 +86,29 @@
 def gr_show(visible=True):
     return {"visible": visible, "__type__": "update"}
 
+## Begin output images uploaded to s3 by River
+s3_resource = boto3.resource('s3')
+
+def save_images_to_s3(full_fillnames,timestamp):
+    username = shared.username
+    sagemaker_endpoint = shared.opts.sagemaker_endpoint
+    bucket_name = opts.train_files_s3bucket
+    if bucket_name == '':
+        return 'Error, please configure a S3 bucket at settings page first'
+    s3_bucket = s3_resource.Bucket(bucket_name)
+    folder_name = f"output-images/{username}/{sagemaker_endpoint}/{timestamp}"
+    try:
+        for i, fname in enumerate(full_fillnames):
+            filename = fname.split('/')[-1]
+            object_name = f"{folder_name}/{filename}"
+            s3_bucket.upload_file(fname,object_name)
+            print (f'upload file [{i}]:{filename} to s3://{bucket_name}/{object_name}')
+    except ClientError as e:
+        print(e)
+        return e
+    return f"s3://{bucket_name}/{folder_name}"
+## End output images uploaded to s3 by River
+
 
 sample_img2img = "assets/stable-samples/img2img/sketch-mountains-input.jpg"
 sample_img2img = sample_img2img if os.path.exists(sample_img2img) else None
@@ -147,7 +170,7 @@ def __init__(self, d=None):
 
     os.makedirs(opts.outdir_save, exist_ok=True)
 
-    with open(os.path.join(opts.outdir_save, "log.csv"), "a", encoding="utf8", newline='') as file:
+    with open(os.path.join(opts.outdir_save, "log.csv"), "w", encoding="utf8", newline='') as file:
         at_start = file.tell() == 0
         writer = csv.writer(file)
         if at_start:
@@ -163,16 +186,19 @@ def __init__(self, d=None):
                 break
 
             fullfn, txt_fullfn = save_image(image, path, "", seed=p.all_seeds[i], prompt=p.all_prompts[i], extension=extension, info=p.infotexts[image_index], grid=is_grid, p=p, save_to_dirs=save_to_dirs)
-
             filename = os.path.relpath(fullfn, path)
+            print(f'fullfn:{fullfn},\n txt_fullfn:{txt_fullfn} \nfilename:{filename}')
             filenames.append(filename)
             fullfns.append(fullfn)
             if txt_fullfn:
                 filenames.append(os.path.basename(txt_fullfn))
                 fullfns.append(txt_fullfn)
-
         writer.writerow([data["prompt"], data["seed"], data["width"], data["height"], data["sampler_name"], data["cfg_scale"], data["steps"], filenames[0], data["negative_prompt"]])
-
+
+    timestamp = datetime.now(timezone(timedelta(hours=+8))).strftime('%Y-%m-%dT%H:%M:%S')
+    logfile = os.path.join(opts.outdir_save, "log.csv")
+    s3folder = save_images_to_s3(fullfns,timestamp)
+    save_images_to_s3([logfile],timestamp)
     # Make Zip
     if do_make_zip:
         zip_filepath = os.path.join(path, "images.zip")
@@ -184,7 +210,7 @@ def __init__(self, d=None):
                     zip_file.writestr(filenames[i], f.read())
         fullfns.insert(0, zip_filepath)
 
-    return gr.File.update(value=fullfns, visible=True), '', '', plaintext_to_html(f"Saved: {filenames[0]}")
+    return gr.File.update(value=fullfns, visible=True), '', '', plaintext_to_html(f"Saved: {filenames[0]}, \nS3 folder:\n{s3folder}")
 
 
 
@@ -1466,7 +1492,6 @@ def update_orig(image, state):
         with gr.Row().style(equal_height=False):
             with gr.Tabs(elem_id="train_tabs"):
                 ## Begin add s3 images upload interface by River
-                s3_resource = boto3.resource('s3')
                 def upload_to_s3(imgs):
                     username = shared.username 
                     timestamp = datetime.now(timezone(timedelta(hours=+8))).strftime('%Y-%m-%dT%H:%M:%S')

webui.py

@@ -36,6 +36,9 @@
 from modules.shared import cmd_opts, opts
 import modules.hypernetworks.hypernetwork
 import boto3
+import threading
+import time
+
 import traceback
 from botocore.exceptions import ClientError
 import requests
@@ -64,6 +67,21 @@ def initialize():
         modules.scripts.load_scripts()
         return
 
+    ## auto reload new models from s3 add by River
+    sd_models_tmp_dir = "/opt/ml/code/stable-diffusion-webui/models/Stable-diffusion/"
+    cn_models_tmp_dir = "/opt/ml/code/stable-diffusion-webui/models/ControlNet/"
+    session = boto3.Session()
+    region_name = session.region_name
+    sts_client = session.client('sts')
+    account_id = sts_client.get_caller_identity()['Account']
+    sg_defaul_bucket_name = f"sagemaker-{region_name}-{account_id}"
+    s3_folder_sd = "stable-diffusion-webui/models/Stable-diffusion"
+    s3_folder_cn = "stable-diffusion-webui/models/ControlNet"
+
+    sync_s3_folder(sg_defaul_bucket_name,s3_folder_sd,sd_models_tmp_dir,'sd')
+    sync_s3_folder(sg_defaul_bucket_name,s3_folder_cn,cn_models_tmp_dir,'cn')
+    ## end
+
     modelloader.cleanup_models()
     modules.sd_models.setup_model()
     codeformer.setup_model(cmd_opts.codeformer_models_path)
@@ -182,6 +200,114 @@ def user_auth(username, password):
 
     return response.status_code == 200
 
+
+def register_sd_models(sd_models_dir):
+    print ('---register_sd_models()----')
+    if 'endpoint_name' in os.environ:
+        items = []
+        api_endpoint = os.environ['api_endpoint']
+        endpoint_name = os.environ['endpoint_name']
+        print(f'api_endpoint:{api_endpoint}\nendpoint_name:{endpoint_name}')
+        for file in os.listdir(sd_models_dir):
+            if os.path.isfile(os.path.join(sd_models_dir, file)) and (file.endswith('.ckpt') or file.endswith('.safetensors')):
+                hash = modules.sd_models.model_hash(os.path.join(sd_models_dir, file))
+                item = {}
+                item['model_name'] = file
+                item['config'] = '/opt/ml/code/stable-diffusion-webui/repositories/stable-diffusion/configs/stable-diffusion/v1-inference.yaml'
+                item['filename'] = '/opt/ml/code/stable-diffusion-webui/models/Stable-diffusion/{0}'.format(file)
+                item['hash'] = hash
+                item['title'] = '{0} [{1}]'.format(file, hash)
+                item['endpoint_name'] = endpoint_name
+                items.append(item)
+        inputs = {
+            'items': items
+        }
+        params = {
+            'module': 'Stable-diffusion'
+        }
+        if api_endpoint.startswith('http://') or api_endpoint.startswith('https://'):
+            response = requests.post(url=f'{api_endpoint}/sd/models', json=inputs, params=params)
+            print(response)
+
+def register_cn_models(cn_models_dir):
+    print ('---register_cn_models()----')
+    if 'endpoint_name' in os.environ:
+        items = []
+        api_endpoint = os.environ['api_endpoint']
+        endpoint_name = os.environ['endpoint_name']
+        print(f'api_endpoint:{api_endpoint}\nendpoint_name:{endpoint_name}')
+
+        inputs = {
+            'items': items
+        }
+        params = {
+            'module': 'ControlNet'
+        }
+        for file in os.listdir(cn_models_dir):
+            if os.path.isfile(os.path.join(cn_models_dir, file)) and \
+            (file.endswith('.pt') or file.endswith('.pth') or file.endswith('.ckpt') or file.endswith('.safetensors')):
+                hash = modules.sd_models.model_hash(os.path.join(cn_models_dir, file))
+                item = {}
+                item['model_name'] = file
+                item['title'] = '{0} [{1}]'.format(os.path.splitext(file)[0], hash)
+                item['endpoint_name'] = endpoint_name
+                items.append(item)
+
+        if api_endpoint.startswith('http://') or api_endpoint.startswith('https://'):
+            response = requests.post(url=f'{api_endpoint}/sd/models', json=inputs, params=params)
+            print(response)
+
+
+def sync_s3_folder(bucket_name, s3_folder, local_folder,mode):
+    print(f"sync S3 bucket '{bucket_name}', folder '{s3_folder}' for new files...")
+    # Create tmp folders 
+    os.makedirs(os.path.dirname(local_folder), exist_ok=True)
+    print(f'create dir: {os.path.dirname(local_folder)}')
+    # Create an S3 client
+    s3 = boto3.client('s3')
+    def sync():
+        # List all objects in the S3 folder
+        response = s3.list_objects_v2(Bucket=bucket_name, Prefix=s3_folder)
+        # Check if there are any new or deleted files
+        s3_files = set()
+        for obj in response.get('Contents', []):
+            s3_files.add(obj['Key'].replace(s3_folder, '').lstrip('/'))
+
+        local_files = set(os.listdir(local_folder))
+
+        new_files = s3_files - local_files
+        del_files = local_files - s3_files
+
+        # Copy new files to local folder
+        for file in new_files:
+            s3.download_file(bucket_name, s3_folder + '/' + file, os.path.join(local_folder, file))
+            print(f'download_file:from {bucket_name}/{s3_folder}/{file} to {os.path.join(local_folder, file)}')
+
+        # Delete vanished files from local folder
+        for file in del_files:
+            os.remove(os.path.join(local_folder, file))
+            print(f'remove file {os.path.join(local_folder, file)}')
+        # If there are changes
+        if len(new_files) | len(del_files):
+            if mode == 'sd':
+                register_sd_models(local_folder)
+            elif mode == 'cn':
+                register_cn_models(local_folder)
+            else:
+                print(f'unsupported mode:{mode}')
+    # Create a thread function to keep syncing with the S3 folder
+    def sync_thread():
+        while True:
+            sync()
+            time.sleep(60)
+    # Initialize at launch
+    sync()
+    # Start the thread
+    thread = threading.Thread(target=sync_thread)
+    thread.start()
+    return thread
+
+
 def webui():
     launch_api = cmd_opts.api
     initialize()
@@ -218,7 +344,7 @@ def webui():
 
         if launch_api:
             create_api(app)
-
+        
             cmd_sd_models_path = cmd_opts.ckpt_dir
             sd_models_dir = os.path.join(shared.models_path, "Stable-diffusion")
             if cmd_sd_models_path is not None:
@@ -274,7 +400,6 @@ def webui():
                 if api_endpoint.startswith('http://') or api_endpoint.startswith('https://'):
                     response = requests.post(url=f'{api_endpoint}/sd/models', json=inputs, params=params)
                     print(response)
-
         modules.script_callbacks.app_started_callback(shared.demo, app)
 
         wait_on_server(shared.demo)