第七期算子开发题目，对于手册中的ops_demo，可以给一个交叉编译的CMakeLists吗？想在x86上写代码和编译，arm上推理，节省云算力，谢谢

Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simpleWARNING: Retrying (Retry(total=4, connect=None, read=None, redirect=None, status=None)) after connection broken by 'ProxyError('Cannot connect to proxy.', OSError('Tunnel connection failed: 503 Service Unavailable'))': /simple/gradio/WARNING: Retrying (Retry(total=3, connect=None, read=None, redirect=None, status=None)) after connection broken by 'ProxyError('Cannot connect to proxy.', OSError('Tunnel connection failed: 503 Service Unavailable'))': /simple/gradio/WARNING: Retrying (Retry(total=2, connect=None, read=None, redirect=None, status=None)) after connection broken by 'ProxyError('Cannot connect to proxy.', OSError('Tunnel connection failed: 503 Service Unavailable'))': /simple/gradio/WARNING: Retrying (Retry(total=1, connect=None, read=None, redirect=None, status=None)) after connection broken by 'ProxyError('Cannot connect to proxy.', OSError('Tunnel connection failed: 503 Service Unavailable'))': /simple/gradio/WARNING: Retrying (Retry(total=0, connect=None, read=None, redirect=None, status=None)) after connection broken by 'ProxyError('Cannot connect to proxy.', OSError('Tunnel connection failed: 503 Service Unavailable'))': /simple/gradio/ERROR: Could not find a version that satisfies the requirement gradio==4.16.0ERROR: No matching distribution found for gradio==4.16.0

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CodeArts中的项目是怎么实现一键部署成服务的？原理是什么？是每个程序启动一个独立的服务；还是在只启动一个总的服务，然后每个用户部署的就是其中一个接口

作品提交三小时后得分还是0 状态judging，也没有日志 。 模型在线部署时能正常运作，预测时打开本地的图像也能预测到结果。ai应用的id：1a9be8d3-10e0-4e54-9464-7f240c6355c9在线部署服务id：1cd61314-1ad2-4c6e-89d6-d89dbe5d465emodel-f001初赛阶段2024-05-28 15:41:440judging无

可以用pycharm的里自己写的算法和训练好的模型直接部署到modelarts里吗  还是要一定要从创建算法阶段开始？

/home/ma-user/anaconda3/envs/python-3.10.10/lib/python3.10/site-packages/gradio_client/documentation.py:103: UserWarning: Could not get documentation group for <class 'gradio.mix.Parallel'>: No known documentation group for module 'gradio.mix' warnings.warn(f"Could not get documentation group for {cls}: {exc}")/home/ma-user/anaconda3/envs/python-3.10.10/lib/python3.10/site-packages/gradio_client/documentation.py:103: UserWarning: Could not get documentation group for <class 'gradio.mix.Series'>: No known documentation group for module 'gradio.mix' warnings.warn(f"Could not get documentation group for {cls}: {exc}")Running on local URL: http://127.0.0.1:7860IMPORTANT: You are using gradio version 3.39.0, however version 4.29.0 is available, please upgrade.--------Running on public URL: https://4bf68ac779bd610ca7.gradio.liveThis share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)---------------------------------------------------------------------------TimeoutError Traceback (most recent call last)File ~/anaconda3/envs/python-3.10.10/lib/python3.10/site-packages/urllib3/connectionpool.py:537, in HTTPConnectionPool._make_request(self, conn, method, url, body, headers, retries, timeout, chunked, response_conn, preload_content, decode_content, enforce_content_length) 536 try:--> 537 response = conn.getresponse() 538 except (BaseSSLError, OSError) as e:File ~/anaconda3/envs/python-3.10.10/lib/python3.10/site-packages/urllib3/connection.py:466, in HTTPConnection.getresponse(self) 465 # Get the response from http.client.HTTPConnection--> 466 httplib_response = super().getresponse() 468 try:File ~/anaconda3/envs/python-3.10.10/lib/python3.10/http/client.py:1374, in HTTPConnection.getresponse(self) 1373 try:-> 1374 response.begin() 1375 except ConnectionError:File ~/anaconda3/envs/python-3.10.10/lib/python3.10/http/client.py:318, in HTTPResponse.begin(self) 317 while True:--> 318 version, status, reason = self._read_status() 319 if status != CONTINUE:File ~/anaconda3/envs/python-3.10.10/lib/python3.10/http/client.py:279, in HTTPResponse._read_status(self) 278 def _read_status(self):--> 279 line = str(self.fp.readline(_MAXLINE + 1), "iso-8859-1") 280 if len(line) > _MAXLINE:File ~/anaconda3/envs/python-3.10.10/lib/python3.10/socket.py:705, in SocketIO.readinto(self, b) 704 try:--> 705 return self._sock.recv_into(b) 706 except timeout:File ~/anaconda3/envs/python-3.10.10/lib/python3.10/ssl.py:1274, in SSLSocket.recv_into(self, buffer, nbytes, flags) 1271 raise ValueError( 1272 "non-zero flags not allowed in calls to recv_into() on %s" % 1273 self.__class__)-> 1274 return self.read(nbytes, buffer) 1275 else:File ~/anaconda3/envs/python-3.10.10/lib/python3.10/ssl.py:1130, in SSLSocket.read(self, len, buffer) 1129 if buffer is not None:-> 1130 return self._sslobj.read(len, buffer) 1131 else:TimeoutError: The read operation timed outThe above exception was the direct cause of the following exception:ReadTimeoutError Traceback (most recent call last)File ~/anaconda3/envs/python-3.10.10/lib/python3.10/site-packages/requests/adapters.py:589, in HTTPAdapter.send(self, request, stream, timeout, verify, cert, proxies) 588 try:--> 589 resp = conn.urlopen( 590 method=request.method, 591 url=url, 592 body=request.body, 593 headers=request.headers, 594 redirect=False, 595 assert_same_host=False, 596 preload_content=False, 597 decode_content=False, 598 retries=self.max_retries, 599 timeout=timeout, 600 chunked=chunked, 601 ) 603 except (ProtocolError, OSError) as err:File ~/anaconda3/envs/python-3.10.10/lib/python3.10/site-packages/urllib3/connectionpool.py:847, in HTTPConnectionPool.urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw) 845 new_e = ProtocolError("Connection aborted.", new_e)--> 847 retries = retries.increment( 848 method, url, error=new_e, _pool=self, _stacktrace=sys.exc_info()[2] 849 ) 850 retries.sleep()File ~/anaconda3/envs/python-3.10.10/lib/python3.10/site-packages/urllib3/util/retry.py:470, in Retry.increment(self, method, url, response, error, _pool, _stacktrace) 469 if read is False or method is None or not self._is_method_retryable(method):--> 470 raise reraise(type(error), error, _stacktrace) 471 elif read is not None:File ~/anaconda3/envs/python-3.10.10/lib/python3.10/site-packages/urllib3/util/util.py:39, in reraise(tp, value, tb) 38 raise value.with_traceback(tb)---> 39 raise value 40 finally:File ~/anaconda3/envs/python-3.10.10/lib/python3.10/site-packages/urllib3/connectionpool.py:793, in HTTPConnectionPool.urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw) 792 # Make the request on the HTTPConnection object--> 793 response = self._make_request( 794 conn, 795 method, 796 url, 797 timeout=timeout_obj, 798 body=body, 799 headers=headers, 800 chunked=chunked, 801 retries=retries, 802 response_conn=response_conn, 803 preload_content=preload_content, 804 decode_content=decode_content, 805 **response_kw, 806 ) 808 # Everything went great!File ~/anaconda3/envs/python-3.10.10/lib/python3.10/site-packages/urllib3/connectionpool.py:539, in HTTPConnectionPool._make_request(self, conn, method, url, body, headers, retries, timeout, chunked, response_conn, preload_content, decode_content, enforce_content_length) 538 except (BaseSSLError, OSError) as e:--> 539 self._raise_timeout(err=e, url=url, timeout_value=read_timeout) 540 raiseFile ~/anaconda3/envs/python-3.10.10/lib/python3.10/site-packages/urllib3/connectionpool.py:370, in HTTPConnectionPool._raise_timeout(self, err, url, timeout_value) 369 if isinstance(err, SocketTimeout):--> 370 raise ReadTimeoutError( 371 self, url, f"Read timed out. (read timeout={timeout_value})" 372 ) from err 374 # See the above comment about EAGAIN in Python 3.ReadTimeoutError: HTTPSConnectionPool(host='4bf68ac779bd610ca7.gradio.live', port=443): Read timed out. (read timeout=3)During handling of the above exception, another exception occurred:ReadTimeout Traceback (most recent call last)Cell In[4], line 29 25 submitBtn.click(reset_user_input, [], [user_input]) 27 emptyBtn.click(reset_state, outputs=[chatbot, history, past_key_values], show_progress=True)---> 29 demo.queue().launch(share=True, inbrowser=True)File ~/anaconda3/envs/python-3.10.10/lib/python3.10/site-packages/gradio/blocks.py:1974, in Blocks.launch(self, inline, inbrowser, share, debug, enable_queue, max_threads, auth, auth_message, prevent_thread_lock, show_error, server_name, server_port, show_tips, height, width, encrypt, favicon_path, ssl_keyfile, ssl_certfile, ssl_keyfile_password, ssl_verify, quiet, show_api, file_directories, allowed_paths, blocked_paths, root_path, _frontend, app_kwargs) 1971 from IPython.display import HTML, Javascript, display # type: ignore 1973 if self.share and self.share_url:-> 1974 while not networking.url_ok(self.share_url): 1975 time.sleep(0.25) 1976 display( 1977 HTML( 1978 f'<div><iframe src="{self.share_url}" width="{self.width}" height="{self.height}" allow="autoplay; camera; microphone; clipboard-read; clipboard-write;" frameborder="0" allowfullscreen></iframe></div>' 1979 ) 1980 )File ~/anaconda3/envs/python-3.10.10/lib/python3.10/site-packages/gradio/networking.py:202, in url_ok(url) 200 with warnings.catch_warnings(): 201 warnings.filterwarnings("ignore")--> 202 r = requests.head(url, timeout=3, verify=False) 203 if r.status_code in (200, 401, 302): # 401 or 302 if auth is set 204 return TrueFile ~/anaconda3/envs/python-3.10.10/lib/python3.10/site-packages/requests/api.py:100, in head(url, **kwargs) 89 r"""Sends a HEAD request. 90 91 :param url: URL for the new :class:`Request` object. (...) 96 :rtype: requests.Response 97 """ 99 kwargs.setdefault("allow_redirects", False)--> 100 return request("head", url, **kwargs)File ~/anaconda3/envs/python-3.10.10/lib/python3.10/site-packages/requests/api.py:59, in request(method, url, **kwargs) 55 # By using the 'with' statement we are sure the session is closed, thus we 56 # avoid leaving sockets open which can trigger a ResourceWarning in some 57 # cases, and look like a memory leak in others. 58 with sessions.Session() as session:---> 59 return session.request(method=method, url=url, **kwargs)File ~/anaconda3/envs/python-3.10.10/lib/python3.10/site-packages/requests/sessions.py:589, in Session.request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json) 584 send_kwargs = { 585 "timeout": timeout, 586 "allow_redirects": allow_redirects, 587 } 588 send_kwargs.update(settings)--> 589 resp = self.send(prep, **send_kwargs) 591 return respFile ~/anaconda3/envs/python-3.10.10/lib/python3.10/site-packages/requests/sessions.py:703, in Session.send(self, request, **kwargs) 700 start = preferred_clock() 702 # Send the request--> 703 r = adapter.send(request, **kwargs) 705 # Total elapsed time of the request (approximately) 706 elapsed = preferred_clock() - startFile ~/anaconda3/envs/python-3.10.10/lib/python3.10/site-packages/requests/adapters.py:635, in HTTPAdapter.send(self, request, stream, timeout, verify, cert, proxies) 633 raise SSLError(e, request=request) 634 elif isinstance(e, ReadTimeoutError):--> 635 raise ReadTimeout(e, request=request) 636 elif isinstance(e, _InvalidHeader): 637 raise InvalidHeader(e, request=request)ReadTimeout: HTTPSConnectionPool(host='4bf68ac779bd610ca7.gradio.live', port=443): Read timed out. (read timeout=3)

用yolov5训练完自己的数据集后，ai应用创建好，最后在开始部署上线时报错File "/home/mind/model/customize_service.py", line 2, inimport cv2File "/home/modelarts/.local/lib/python3.7/site-packages/cv2/__init__.py", line 5, infrom .cv2 import *ImportError: libGL.so.1: cannot open shared object file: No such file or directory[2024-05-27 13:25:47 +0000] [44] [ERROR] Exception in worker processTraceback (most recent call last):File "/home/mind/model_service/model_service.py", line 167, in load_servicespec.loader.exec_module(module)File "", line 728, in exec_moduleFile "", line 219, in _call_with_frames_removedFile "/home/mind/model/customize_service.py", line 2, inimport cv2File "/home/modelarts/.local/lib/python3.7/site-packages/cv2/__init__.py", line 5, infrom .cv2 import *ImportError: libGL.so.1: cannot open shared object file: No such file or directory好像是导入opencv的问题

深度卷积神经网络在发明之初就是用来解决图像分类问题的，现阶段深度学习与图像分类的结合愈加紧密，并且出现了很多经典的算法模型。ResNet基本上成了很多业务场景下开发者快速尝试的标杆算法。后期出现的DenseNet、Xception、ResNext等算法都以ResNet为对比对象。另外，典型的面向移动端的小型网络有MobileNet、ShumeNet、GhostNet等，当开发者对于模型的推理时延要求较高时，需要直接采用小型神经网络进行训练；或者先训练一个大网络，再利用大网络产生的标签对小网络进行训练。随着神经网络结构搜索技术的不断演进，机器搜索出的网络结构NASNet、AmoebaNet、EfficientNet比人工设计的网络结构更好（要么精度更高，要么推理时延更低），其中EfficientNet是目前较为流行的一种卷积神经网络结构。当数据集中含有大量无标签数据时，开发者可以选择基于对比学习或AET等无监督学习方法得到一个预训练模型。最近一两年视觉无监督学习的发展非常迅速，已经非常接近全监督学习水平。当得到预训练模型后，就可以用少量有标签的数据在预训练模型上进行微调，这会大大减少算法对标注数据量的需求。另外，还可以选择相对成熟一些的半监督算法，如Mixmatch、Remixmatch及LabelPropagation等，这些算法在标注量较少时可以获得不错的精度。

为什么按照官方给的解决方法还是出现上述问题呢？以上是日志报错信息 按照论坛的方式二修改也报错 按照第一种方式修改也是有错我在本地用的Python版本是3.11.0，问了ChatGPT说3.8以上的会自带，所以本地跑没问题，但我的是轻薄本，根本跑不了 求大佬支招

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使用镜像保存功能构建镜像按照如下流程保存当前的Notebook环境：如果一个Notebook同时中存在多个环境，保持镜像时如何切换默认要保存的环境？

如图所示，初始化完成后就显示这个，然后无法上传文件，无法选择kernel，甚至无法删除文件夹，这可咋办呀…………

Dreambooth：一键生成你想要的人物画像Dreambooth是谷歌发布的一种通过向模型注入自定义的主题来fine-tune diffusion model的技术，可以生成不同场景下的图片。本文将演示在AI Gallery中使用自定义数据集微调Stable Diffusion，一键生成你想要的人画图像！1. 准备工作首先下载3~10人像照片，最好是不同角度的人物图像，这里我从网上搜集了5张庄达菲的图片作为输入：2. 运行案例本案例需使用 Pytorch-2.0.1 GPU-V100 及以上规格，点击Run in ModelArts在Notebook中一键体验：3. 模型训练首先下载代码模型并配置运行环境，然后下载原始数据集wh11e.zip压缩包，替换为自己的图片并上传压缩包：模型训练配置和参数保持不变，之后启动训练，一般耗时10min：# --pretrained_model_name_or_path: 模型路径，这里使用我下载的离线权重SD1.5# --pretrained_vae_name_or_path: vae路径，这里使用我下载的离线权重# --output_dir: 输出路径# --resolution: 分辨率# --save_sample_prompt: 保存样本的提示语# --concepts_list: 配置json路径!python3 ./tools/train_dreambooth.py \ --pretrained_model_name_or_path=$model_sd \ --pretrained_vae_name_or_path="vae-ft-mse" \ --output_dir=$output_dir \ --revision="fp16" \ --with_prior_preservation --prior_loss_weight=1.0 \ --seed=777 \ --resolution=512 \ --train_batch_size=1 \ --train_text_encoder \ --mixed_precision="fp16" \ --use_8bit_adam \ --gradient_accumulation_steps=1 \ --learning_rate=$learning_rate \ --lr_scheduler="constant" \ --lr_warmup_steps=80 \ --num_class_images=$num_class_images \ --sample_batch_size=4 \ --max_train_steps=$max_num_steps \ --save_interval=10000 \ --save_sample_prompt="a photo of wh11e person" \ --concepts_list="./training_data/concepts_list.json"查看模型输出的样本：from natsort import natsortedfrom glob import glob# 查看模型输出的样本saved_weights_dir = natsorted(glob(output_dir + os.sep + '*'))[-1]saved_weights_dir'dreambooth_wh11e/500'4. 模型推理运行Gradio应用，修改输入提示词生成不同场景的人物画像：import torch import numpy as npimport gradio as grfrom diffusers import StableDiffusionPipeline# 加载模型pipe = StableDiffusionPipeline.from_pretrained(saved_weights_dir, torch_dtype=torch.float16)# 配置GPUpipe = pipe.to('cuda')pipe.enable_attention_slicing() # 开启注意力切片，节约显存pipe.enable_xformers_memory_efficient_attention() # 开启Xformers的内存优化注意力，节约显存# 更换schedulerfrom diffusers import DDIMSchedulerpipe.scheduler = DDIMScheduler.from_config(pipe.scheduler.config)negative_prompt = "bad anatomy, ugly, deformed, desfigured, distorted face, poorly drawn hands, poorly drawn face, poorly drawn feet, blurry, low quality, low definition, lowres, out of frame, out of image, cropped, cut off, signature, watermark"num_samples = 1guidance_scale = 7.5num_inference_steps = 30height = 512width = 512def generate_image(prompt, steps): image = pipe(prompt, output_type='numpy', negative_prompt=negative_prompt, height=height, width=width, num_images_per_prompt=num_samples, num_inference_steps=steps, guidance_scale=guidance_scale ).images image = np.uint8(image[0] * 255) return imagewith gr.Blocks() as demo: gr.HTML("""<h1 align="center">Dreambooth</h1>""") with gr.Tab("Generate Image"): with gr.Row(): with gr.Column(): text_input = gr.Textbox(value="a photo of wh11e person", label="prompts", lines=4) steps = gr.Slider(30, 50, step=1, label="steps") gr.Examples( examples=[ ["face portrait of wh11e in the snow, realistic, hd, vivid, sunset"], ["photo of wh11e person, closeup, mountain fuji in the background, natural lighting"], ["photo of wh11e person in the desert, closeup, pyramids in the background, natural lighting, frontal face"] ], inputs=[text_input] ) image_output = gr.Image(height=400, width=400) image_button = gr.Button("submit") image_button.click(generate_image, [text_input, steps], [image_output]) demo.launch(share=True)Loading pipeline components...: 100%|██████████| 6/6 [00:01<00:00, 4.09it/s]You have disabled the safety checker for <class 'diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline'> by passing `safety_checker=None`. Ensure that you abide to the conditions of the Stable Diffusion license and do not expose unfiltered results in services or applications open to the public. Both the diffusers team and Hugging Face strongly recommend to keep the safety filter enabled in all public facing circumstances, disabling it only for use-cases that involve analyzing network behavior or auditing its results. For more information, please have a look at https://github.com/huggingface/diffusers/pull/254 .Running on local URL: http://127.0.0.1:7860IMPORTANT: You are using gradio version 4.0.2, however version 4.29.0 is available, please upgrade.--------Running on public URL: https://0706d8a2cf7260863f.gradio.liveThis share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)