在Azure ML中为注册的R模型部署web服务

我有一个绝对的噩梦要用。因此，我尝试通过UI（）实现所有功能。我在R4.0.5中训练了一个本地模型

library(datasets)
library(caret)

data(iris)

setwd("C:/Data")

index <- createDataPartition(iris$Species, p=0.80, list=FALSE)
testset <- iris[-index,]
trainset <- iris[index,]

model = train(Species ~ ., 
                  data=trainset, 
                  method="rpart", 
                  trControl = trainControl(method = "cv"))

saveRDS(model, "model.rds")

但是，请立即了解：

我如何调试正在发生的事情？conda依赖项文件是否错误？就目前情况而言，Azure ML对于我这个拥有本地培训模型的R用户来说绝对是无用的）——：

附言：

我还尝试在本地部署它，如下所示：

library(azuremlsdk)

interactive_auth <- interactive_login_authentication(tenant_id="296bf094-bdb4-488f-8ebd-92b2dd1464c2")

ws <- get_workspace(
        name = "xxx", 
        subscription_id = "xxx", 
        resource_group ="xxx", 
        auth = interactive_auth
)

model <- get_model(ws, name = "iris")

r_env <- r_environment(name = "r_env")

# Create inference config
inference_config <- inference_config(
  entry_script = "score1.R",
  source_directory = ".",
  environment = r_env)

local_deployment_config <- local_webservice_deployment_config()

service <- deploy_model(ws, 
                        'rservice-local', 
                        list(model), 
                        inference_config, 
                        local_deployment_config)
# Wait for deployment
wait_for_deployment(service, show_output = TRUE)

# Show the port of local service
message(service$port)

所以我故意创建了一个相对文件夹：

/var/azureml应用程序/iris/

上面的脚本所在的位置，并将score1.r（见上文）放在那里。还是一样的错误。我迷路了

name: scoring_environment
channels:
  - defaults
dependencies:
  - r-base=4.0.5
  #- r-essentials=4.0.5
  # whatever other dependencies you have
  - jsonlite=1.7.2 

library(azuremlsdk)

interactive_auth <- interactive_login_authentication(tenant_id="296bf094-bdb4-488f-8ebd-92b2dd1464c2")

ws <- get_workspace(
        name = "xxx", 
        subscription_id = "xxx", 
        resource_group ="xxx", 
        auth = interactive_auth
)

model <- get_model(ws, name = "iris")

r_env <- r_environment(name = "r_env")

# Create inference config
inference_config <- inference_config(
  entry_script = "score1.R",
  source_directory = ".",
  environment = r_env)

local_deployment_config <- local_webservice_deployment_config()

service <- deploy_model(ws, 
                        'rservice-local', 
                        list(model), 
                        inference_config, 
                        local_deployment_config)
# Wait for deployment
wait_for_deployment(service, show_output = TRUE)

# Show the port of local service
message(service$port)

/azureml-envs/azureml_da3e97fcb51801118b8e80207f3e01ad/lib/python3.6/site-packages/rpy2/rinterface/__init__.py:146: RRuntimeWarning:  cannot open file '/var/azureml-app/iris/score1.R': No such file or directory