From 208430c8dda875dc0b9c51caa36524bbd12faa8d Mon Sep 17 00:00:00 2001 From: Acexoul081 Date: Sat, 18 Jun 2022 19:12:08 +0700 Subject: [PATCH] Endpoint model name revision Change the correct model name for serving in tensorflow and keras example readme.md --- examples/keras/readme.md | 4 ++-- examples/sklearn/readme.md | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/examples/keras/readme.md b/examples/keras/readme.md index 5a9f84c..f306ee7 100644 --- a/examples/keras/readme.md +++ b/examples/keras/readme.md @@ -17,12 +17,12 @@ Prerequisites, Keras/Tensorflow models require Triton engine support, please use 1. Create serving Service: `clearml-serving create --name "serving example"` (write down the service ID) 2. Create model endpoint: - `clearml-serving --id model add --engine triton --endpoint "test_model_keras" --preprocess "examples/keras/preprocess.py" --name "train keras model" --project "serving examples" --input-size 1 784 --input-name "dense_input" --input-type float32 --output-size -1 10 --output-name "activation_2" --output-type float32 + `clearml-serving --id model add --engine triton --endpoint "test_model_keras" --preprocess "examples/keras/preprocess.py" --name "train keras model - serving_model" --project "serving examples" --input-size 1 784 --input-name "dense_input" --input-type float32 --output-size -1 10 --output-name "activation_2" --output-type float32 ` Or auto update -`clearml-serving --id model auto-update --engine triton --endpoint "test_model_auto" --preprocess "examples/keras/preprocess.py" --name "train keras model" --project "serving examples" --max-versions 2 +`clearml-serving --id model auto-update --engine triton --endpoint "test_model_auto" --preprocess "examples/keras/preprocess.py" --name "train keras model - serving_model" --project "serving examples" --max-versions 2 --input-size 1 784 --input-name "dense_input" --input-type float32 --output-size -1 10 --output-name "activation_2" --output-type float32` diff --git a/examples/sklearn/readme.md b/examples/sklearn/readme.md index 33b802f..13d5058 100644 --- a/examples/sklearn/readme.md +++ b/examples/sklearn/readme.md @@ -14,11 +14,11 @@ The output will be a model created on the project "serving examples", by the nam 1. Create serving Service: `clearml-serving create --name "serving example"` (write down the service ID) 2. Create model endpoint: -`clearml-serving --id model add --engine sklearn --endpoint "test_model_sklearn" --preprocess "examples/sklearn/preprocess.py" --name "train sklearn model" --project "serving examples"` +`clearml-serving --id model add --engine sklearn --endpoint "test_model_sklearn" --preprocess "examples/sklearn/preprocess.py" --name "train sklearn model - sklearn-model" --project "serving examples"` Or auto update -`clearml-serving --id model auto-update --engine sklearn --endpoint "test_model_sklearn_auto" --preprocess "examples/sklearn/preprocess.py" --name "train sklearn model" --project "serving examples" --max-versions 2` +`clearml-serving --id model auto-update --engine sklearn --endpoint "test_model_sklearn_auto" --preprocess "examples/sklearn/preprocess.py" --name "train sklearn model - sklearn-model" --project "serving examples" --max-versions 2` Or add Canary endpoint