AWS：客户端：呼叫createTransFormjob操作时发生错误（验证Exception）：找不到模型
我在这里是新手，对一些基本的事情感到沮丧。 我正在尝试实现DeepAR模型，但也许由于萨吉式制造商的更新，它找不到像示例上的正确路径。 有人可以告诉我为什么会发生以及如何修复它？
错误：客户端：呼叫createTransFormJob操作时发生错误（验证Exception）：找不到模型“ ARN：AWS：AWS：SAGEMAKER：EU-CENTRAL-1：900386373554：Model/Model/forecasting-Deecasting-Deecar-2022-2022-2022-06-14-14-12-14-14-12 -51-560“。
这是我要实现的批处理
转换 ： 导入boto3 - 创建SageMaker Boto3客户端 boto3_sm = boto3.client（'sagemaker'）
导入时间 从时间导入GMTime，strftime
batch_job_name ='batch-transform-' + strftime（“％y-％m-％d-％d-％h-％m-％s”，gmtime（）） input_location ='s3：//sagemaker-eu-central-1-900386373554/deepar-rossmann/input/prediction_input.json' output_location ='s3：// {}/{}/{}/output/{}'.format（bucket，prefix，batch_job_name）
request =
{ “批处理”：“ Singlerecord”， “ maxpayloadinmb”：100， “环境”： { “ deepar_inference_config”：“ {” {“ num_samples”：200，“ output_types”：[“ sane” sane']}” }，， “ transformjobname”：batch_job_name， “ modelname”：'预测深度-2022-06-21-14-14-12-51-560'， “ transformOutput”：{ “ s3Outputpath”：output_location， “接受”：“应用程序/jsonlines”， “ coptemblewith”：“ line” }，， [...]
我正在关注此项目： https://githerline noreflofe 笔记本3 of 3步骤49-
＆GT; ModelName从AWS控制台完成的培训工作中复制
了
I am new here and am strugling with some basic things.
I am trying to implement a DeepAR model, but maybe due to an update from sagemaker it doesn't find the correct path as it did on the example..
Can someone tell me why is it happening and how o fix it?
Error: ClientError: An error occurred (ValidationException) when calling the CreateTransformJob operation: Could not find model "arn:aws:sagemaker:eu-central-1:900386373554:model/forecasting-deepar-2022-06-21-14-12-51-560".
This is the Batch Transformation I am trying to implement:
-Batch Transform
import boto3
-Create the SageMaker Boto3 client
boto3_sm = boto3.client('sagemaker')
import time
from time import gmtime, strftime
batch_job_name = 'Batch-Transform-' + strftime("%Y-%m-%d-%H-%M-%S", gmtime())
input_location = 's3://sagemaker-eu-central-1-900386373554/deepar-rossmann/input/prediction_input.json'
output_location = 's3://{}/{}/output/{}'.format(bucket, prefix, batch_job_name)
request =
{
"BatchStrategy": "SingleRecord",
"MaxPayloadInMB": 100,
"Environment": {
"DEEPAR_INFERENCE_CONFIG" : "{ "num_samples": 200, "output_types": ["mean"] }"
},
"TransformJobName": batch_job_name,
"ModelName": 'forecasting-deepar-2022-06-21-14-12-51-560',
"TransformOutput": {
"S3OutputPath": output_location,
"Accept": "application/jsonlines",
"AssembleWith": "Line"
},
[...]
I am following this project: https://github.com/CatherineSai/project_sales_prediction_DEEPAR
Notebook 3 of 3 step 49
--> ModelName is copied from the finished training job at aws console
Thanks
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为了启动SageMaker批处理转换作业，您需要
sagemaker模型。请确认modelName您正在传递的model页面中的“ ”页面（推荐选项卡＆gt; models）In order to launch a SageMaker Batch Transform Job you require a
SageMaker Model. Kindly confirm that theModelNameyou are passing exists in theModelspage in the Console (Inference tab > Models)