## ----eval=FALSE--------------------------------------------------------------- # library(azuremlsdk) ## ----load_workpace, eval=FALSE------------------------------------------------ # ws <- load_workspace_from_config() ## ----get_workpace, eval=FALSE------------------------------------------------- # ws <- get_workspace("", "", "") ## ----create_experiment, eval=FALSE-------------------------------------------- # exp <- experiment(workspace = ws, name = "tf-mnist") ## ----create_cluster, eval=FALSE----------------------------------------------- # cluster_name <- "gpucluster" # # compute_target <- get_compute(ws, cluster_name = cluster_name) # if (is.null(compute_target)) # { # vm_size <- "STANDARD_NC6" # compute_target <- create_aml_compute(workspace = ws, # cluster_name = cluster_name, # vm_size = vm_size, # max_nodes = 4) # # wait_for_provisioning_completion(compute_target, show_output = TRUE) # } ## ----create_estimator, eval=FALSE--------------------------------------------- # env <- r_environment("tensorflow-env", custom_docker_image = "amlsamples/r-tensorflow:latest") # # est <- estimator(source_directory = "train-with-tensorflow", # entry_script = "tf_mnist.R", # compute_target = compute_target, # environment = env) ## ----submit_job, eval=FALSE--------------------------------------------------- # run <- submit_experiment(exp, est) ## ----eval=FALSE--------------------------------------------------------------- # plot_run_details(run) ## ----eval=FALSE--------------------------------------------------------------- # wait_for_run_completion(run, show_output = TRUE) ## ----get_metrics, eval=FALSE-------------------------------------------------- # metrics <- get_run_metrics(run) # metrics ## ----delete_compute, eval=FALSE----------------------------------------------- # delete_compute(compute_target)