amazon-sagemaker

问题 I have a pre-trained Tensorflow model, I'm trying to using SagaMaker client.create_endpoint() to create an endpoint so that I can call the API to get predictions, the doc is here After creating the model by using client.create_model() I have a model stored on SageMaker, and the base image I'm using is 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:1.15.2-gpu , this is my code: model_name = `xxx`, role = `xxx`, model_base_image = `763104351884.dkr.ecr.us-east-1.amazonaws.com

问题 this is my problem: I have to run a Sagemaker processing job using custom code written in PySpark. I've used the Sagemaker SDK by running these commands: spark_processor = sagemaker.spark.processing.PySparkProcessor( base_job_name="spark-preprocessor", framework_version="2.4", role=role_arn, instance_count=2, instance_type="ml.m5.xlarge", max_runtime_in_seconds=1800, ) spark_processor.run( submit_app="processing.py", arguments=['s3_input_bucket', bucket_name, 's3_input_file_path', file_path ]

问题 I have created a stepfunction, the definition for this statemachine below ( step-function.json ) is used in terraform (using the syntax in this page:https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTransformJob.html) The first time if I execute this statemachine, it will create a SageMaker batch transform job named example-jobname , but I need to exeucute this statemachine everyday, then it will give me error "error": "SageMaker.ResourceInUseException", "cause": "Job name

问题 I spin up a Sagemaker notebook using the conda_python3 kernel, and follow the example Notebook for Random Cut Forest. As of this writing, the Sagemaker SDK that comes with conda_python3 is version 1.72.0, but I want to use new features, so I update my notebook to use the latest %%bash pip install -U sagemaker And I see it updates. print(sagemaker.__version__) # 2.4.1 A change from version 1.x to 2.x was the serializer/deserializer classes Previously (in version 1.72.0) I'd update my predictor

问题 i have started a sagemaker job: from sagemaker.tensorflow import TensorFlow mytraining= TensorFlow(entry_point='model.py', role=role, train_instance_count=1, train_instance_type='ml.p2.xlarge', framework_version='2.0.0', py_version='py3', distributions={'parameter_server'{'enabled':False}}) training_data_uri ='s3://path/to/my/data' mytraining.fit(training_data_uri,run_tensorboard_locally=True) using run_tesorboard_locally=True gave me Tensorboard is not supported with script mode. You can run

问题 I am trying to use XGBoost on Sagemaker notebook. I am using conda_python3 kernel, and the following packages are installed: py-xgboost-mutex libxgboost py-xgboost py-xgboost-gpu But once I am trying to import xgboost it fails on import: ModuleNotFoundError Traceback (most recent call last) <ipython-input-5-5943d1bfe3f1> in <module>() ----> 1 import xgboost as xgb ModuleNotFoundError: No module named 'xgboost' 回答1: In Sagemaker notebooks use the below steps a) If in Notebook i) !type python3

问题 I am trying to use XGBoost on Sagemaker notebook. I am using conda_python3 kernel, and the following packages are installed: py-xgboost-mutex libxgboost py-xgboost py-xgboost-gpu But once I am trying to import xgboost it fails on import: ModuleNotFoundError Traceback (most recent call last) <ipython-input-5-5943d1bfe3f1> in <module>() ----> 1 import xgboost as xgb ModuleNotFoundError: No module named 'xgboost' 回答1: In Sagemaker notebooks use the below steps a) If in Notebook i) !type python3

问题 I am trying to use XGBoost on Sagemaker notebook. I am using conda_python3 kernel, and the following packages are installed: py-xgboost-mutex libxgboost py-xgboost py-xgboost-gpu But once I am trying to import xgboost it fails on import: ModuleNotFoundError Traceback (most recent call last) <ipython-input-5-5943d1bfe3f1> in <module>() ----> 1 import xgboost as xgb ModuleNotFoundError: No module named 'xgboost' 回答1: In Sagemaker notebooks use the below steps a) If in Notebook i) !type python3

问题 I am trying to use XGBoost on Sagemaker notebook. I am using conda_python3 kernel, and the following packages are installed: py-xgboost-mutex libxgboost py-xgboost py-xgboost-gpu But once I am trying to import xgboost it fails on import: ModuleNotFoundError Traceback (most recent call last) <ipython-input-5-5943d1bfe3f1> in <module>() ----> 1 import xgboost as xgb ModuleNotFoundError: No module named 'xgboost' 回答1: In Sagemaker notebooks use the below steps a) If in Notebook i) !type python3

问题 After creating SKLearn() instance and using HyperparamaterTuner with a few hyperparameter ranges, I get the best estimator. When I try to deploy() the estimator, it gives an error in the log. Exactly same error happens when I create transformer and call transform on it(). Doesn't deploy and doesn't transform. What could be the problem and at least how could I possibly narrow down the problem? I have no idea how to even begin to figure this out. Googling didn't help. Nothing comes up. Creating