Python GCP AI平台：创建自定义预测模型版本时出错（训练模型Pytorch model+；torchvision.transform）_Python_Google Cloud Platform_Pytorch_Torchvision_Google Ai Platform

Python GCP AI平台：创建自定义预测模型版本时出错（训练模型Pytorch model+；torchvision.transform）

python google-cloud-platform pytorch

Python GCP AI平台：创建自定义预测模型版本时出错（训练模型Pytorch model+；torchvision.transform）,python,google-cloud-platform,pytorch,torchvision,google-ai-platform,Python,Google Cloud Platform,Pytorch,Torchvision,Google Ai Platform,我目前正试图通过遵循将自定义模型部署到AI平台。它是基于来自'Pytorch'和“torchvision.transform”的预先训练模型的组合。目前，我一直得到以下错误，这恰好与自定义预测上的500MB限制有关错误：（gcloud.beta.ai platform.versions.create）创建版本失败。检测到错误的模型：模型需要的内存超过允许的内存。请尝试减小模型大小并重新部署。如果您仍然遇到错误，请与支持部门联系。 Setup.py from setuptools import

我目前正试图通过遵循将自定义模型部署到AI平台。它是基于来自'Pytorch'和“torchvision.transform”的预先训练模型的组合。目前，我一直得到以下错误，这恰好与自定义预测上的500MB限制有关
错误：（gcloud.beta.ai platform.versions.create）创建版本失败。检测到错误的模型：模型需要的内存超过允许的内存。请尝试减小模型大小并重新部署。如果您仍然遇到错误，请与支持部门联系。
Setup.py

from setuptools import setup from pathlib import Path base = Path(__file__).parent REQUIRED_PACKAGES = [line.strip() for line in open(base/"requirements.txt")] print(f"\nPackages: {REQUIRED_PACKAGES}\n\n") # [torch==1.3.0,torchvision==0.4.1, ImageHash==4.2.0 # Pillow==6.2.1,pyvis==0.1.8.2] installs 800mb worth of files setup(description="Extract features of a image", author='Amrit', name='test', version='0.1', install_requires=REQUIRED_PACKAGES, project_urls={ 'Documentation':'https://cloud.google.com/ai-platform/prediction/docs/custom-prediction-routines#tensorflow', 'Deploy':'https://cloud.google.com/ai-platform/prediction/docs/deploying-models#gcloud_1', 'Ai_platform troubleshooting':'https://cloud.google.com/ai-platform/training/docs/troubleshooting', 'Say Thanks!': 'https://medium.com/searce/deploy-your-own-custom-model-on-gcps-ai-platform- 7e42a5721b43', 'google Torch wheels':"http://storage.googleapis.com/cloud-ai-pytorch/readme.txt", 'Torch & torchvision wheels':"https://download.pytorch.org/whl/torch_stable.html " }, python_requires='~=3.7', scripts=['predictor.py', 'preproc.py'])
采取的步骤： 尝试将“torch”和torchvision直接添加到setup.py文件中的“REQUIRED_PACKAGES”列表中，以便在部署时提供Pytork+torchvision作为要安装的依赖项。我猜，在内部Ai平台下载PyTorch的PyPI包是+500 MB，这导致我们的模型部署失败。如果我只使用“torch”部署模型，并且它似乎正在工作（当然，由于找不到库“torchvision”，会抛出错误）
文件大小

pytorch（torch-1.3.1+cpu-cp37-cp37m-linux\u x86\u 64.whl关于111MB）

torchvision（torchvision-0.4.1+cpu-cp37-cp37m-linux\u x86\u 64.whl关于46MB）并存储在GKS上

压缩的预测器模型文件（.tar.gz格式），它是setup.py（5kb）的输出

经过训练的Pytork模型（大小44MB）

总的来说，模型依赖项应该小于250MB，但仍然会出现此错误。他们也尝试使用谷歌镜像软件包提供的torch和torchvision，但同样的内存问题依然存在。人工智能平台对我们来说是一个全新的平台，需要专业人士的一些意见
更多信息： GCP CLI输入：

BUCKET_NAME= “something” MODEL_DIR="gs://$BUCKET_NAME/" VERSION_NAME='v6' MODEL_NAME="something_model" STAGING_BUCKET=$MODEL_DIR"staging_area/" # TORCH_PACKAGE=$MODEL_DIR"package/torch-1.3.1+cpu-cp37-cp37m-linux_x86_64.whl" # TORCHVISION_PACKAGE=$MODEL_DIR"package/torchvision-0.4.1+cpu-cp37-cp37m-linux_x86_64.whl" TORCH_PACKAGE="gs://cloud-ai-pytorch/torch-1.3.1+cpu-cp37-cp37m-linux_x86_64.whl" TORCHVISION_PACKAGE="gs://cloud-ai-pytorch/torchvision-0.4.1+cpu-cp37-cp37m-linux_x86_64.whl" CUSTOM_CODE_PATH=$STAGING_BUCKET"imt_ai_predict-0.1.tar.gz" PREDICTOR_CLASS="predictor.MyPredictor" REGION='europe-west1' MACHINE_TYPE='mls1-c4-m2' gcloud beta ai-platform versions create $VERSION_NAME \ --model=$MODEL_NAME \ --origin=$MODEL_DIR \ --runtime-version=2.3 \ --python-version=3.7 \ --machine-type=$MACHINE_TYPE \ --package-uris=$CUSTOM_CODE_PATH,$TORCH_PACKAGE,$TORCHVISION_PACKAGE \ --prediction-class=$PREDICTOR_CLASS \

**[1] global** [2] asia-east1 [3] asia-northeast1 [4] asia-southeast1 [5] australia-southeast1 [6] europe-west1 [7] europe-west2 [8] europe-west3 [9] europe-west4 [10] northamerica-northeast1 [11] us-central1 [12] us-east1 [13] us-east4 [14] us-west1 [15] cancel Please enter your numeric choice: 1 To make this the default region, run `gcloud config set ai_platform/region global`. Using endpoint [https://ml.googleapis.com/] Creating version (this might take a few minutes)......failed. ERROR: (gcloud.beta.ai-platform.versions.create) Create Version failed. Bad model detected with error: **Model requires more memory than allowed. Please try to decrease the model size and re-deploy. If you continue to experience errors, please contact support.**
我的环境变量：

BUCKET_NAME= “something” MODEL_DIR="gs://$BUCKET_NAME/" VERSION_NAME='v6' MODEL_NAME="something_model" STAGING_BUCKET=$MODEL_DIR"staging_area/" # TORCH_PACKAGE=$MODEL_DIR"package/torch-1.3.1+cpu-cp37-cp37m-linux_x86_64.whl" # TORCHVISION_PACKAGE=$MODEL_DIR"package/torchvision-0.4.1+cpu-cp37-cp37m-linux_x86_64.whl" TORCH_PACKAGE="gs://cloud-ai-pytorch/torch-1.3.1+cpu-cp37-cp37m-linux_x86_64.whl" TORCHVISION_PACKAGE="gs://cloud-ai-pytorch/torchvision-0.4.1+cpu-cp37-cp37m-linux_x86_64.whl" CUSTOM_CODE_PATH=$STAGING_BUCKET"imt_ai_predict-0.1.tar.gz" PREDICTOR_CLASS="predictor.MyPredictor" REGION='europe-west1' MACHINE_TYPE='mls1-c4-m2' gcloud beta ai-platform versions create $VERSION_NAME \ --model=$MODEL_NAME \ --origin=$MODEL_DIR \ --runtime-version=2.3 \ --python-version=3.7 \ --machine-type=$MACHINE_TYPE \ --package-uris=$CUSTOM_CODE_PATH,$TORCH_PACKAGE,$TORCHVISION_PACKAGE \ --prediction-class=$PREDICTOR_CLASS \

**[1] global** [2] asia-east1 [3] asia-northeast1 [4] asia-southeast1 [5] australia-southeast1 [6] europe-west1 [7] europe-west2 [8] europe-west3 [9] europe-west4 [10] northamerica-northeast1 [11] us-central1 [12] us-east1 [13] us-east4 [14] us-west1 [15] cancel Please enter your numeric choice: 1 To make this the default region, run `gcloud config set ai_platform/region global`. Using endpoint [https://ml.googleapis.com/] Creating version (this might take a few minutes)......failed. ERROR: (gcloud.beta.ai-platform.versions.create) Create Version failed. Bad model detected with error: **Model requires more memory than allowed. Please try to decrease the model size and re-deploy. If you continue to experience errors, please contact support.**
GCP CLI输出：

BUCKET_NAME= “something” MODEL_DIR="gs://$BUCKET_NAME/" VERSION_NAME='v6' MODEL_NAME="something_model" STAGING_BUCKET=$MODEL_DIR"staging_area/" # TORCH_PACKAGE=$MODEL_DIR"package/torch-1.3.1+cpu-cp37-cp37m-linux_x86_64.whl" # TORCHVISION_PACKAGE=$MODEL_DIR"package/torchvision-0.4.1+cpu-cp37-cp37m-linux_x86_64.whl" TORCH_PACKAGE="gs://cloud-ai-pytorch/torch-1.3.1+cpu-cp37-cp37m-linux_x86_64.whl" TORCHVISION_PACKAGE="gs://cloud-ai-pytorch/torchvision-0.4.1+cpu-cp37-cp37m-linux_x86_64.whl" CUSTOM_CODE_PATH=$STAGING_BUCKET"imt_ai_predict-0.1.tar.gz" PREDICTOR_CLASS="predictor.MyPredictor" REGION='europe-west1' MACHINE_TYPE='mls1-c4-m2' gcloud beta ai-platform versions create $VERSION_NAME \ --model=$MODEL_NAME \ --origin=$MODEL_DIR \ --runtime-version=2.3 \ --python-version=3.7 \ --machine-type=$MACHINE_TYPE \ --package-uris=$CUSTOM_CODE_PATH,$TORCH_PACKAGE,$TORCHVISION_PACKAGE \ --prediction-class=$PREDICTOR_CLASS \

**[1] global** [2] asia-east1 [3] asia-northeast1 [4] asia-southeast1 [5] australia-southeast1 [6] europe-west1 [7] europe-west2 [8] europe-west3 [9] europe-west4 [10] northamerica-northeast1 [11] us-central1 [12] us-east1 [13] us-east4 [14] us-west1 [15] cancel Please enter your numeric choice: 1 To make this the default region, run `gcloud config set ai_platform/region global`. Using endpoint [https://ml.googleapis.com/] Creating version (this might take a few minutes)......failed. ERROR: (gcloud.beta.ai-platform.versions.create) Create Version failed. Bad model detected with error: **Model requires more memory than allowed. Please try to decrease the model size and re-deploy. If you continue to experience errors, please contact support.**
我的发现： 已经找到了一些人以同样的方式为PyTorch软件包奋斗的文章，并通过在地面军事系统上安装火炬轮使其工作( 7e42a5721b43）。
曾尝试过火炬和火炬视觉的相同方法，但到目前为止运气不佳，等待“cloudml”的回应-feedback@google.comcloudml-feedback@google.com". 关于在AI平台上使用基于torchvision的定制预测器的定制torch的任何帮助都将非常好。
通过几件事的组合解决了这个问题。我坚持使用4gb CPU MlS1机器和自定义预测程序（我建议使用自定义容器而不是自定义预测程序在AI平台预测上部署模型。请查看此示例>。感谢Raj，我将查看自定义容器。您认为没有模型内存限制吗（请尝试使用更大的机器类型mls1-c4-m4重新部署好吗？自定义容器的最大内存限制为2GB，自定义预测例程为500MB。自定义容器部署在n1-*机器类型上。以下是受支持的机器类型>感谢Enrique，将使用“mls1-c4-m4”进行测试）.虽然在官方谷歌文档中没有显示该机器类型，但只有m1和m4类型的Mls1具有自定义预测功能。