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This error usually occurs when you exceed the account level service quotas that are specified for your SageMaker resources.
To resolve this error, complete the following steps:
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Open the Service Quotas console. Note: To use the Service Quotas console, you need the corresponding AWS Identity and Access Management (IAM) permission in your user or role.
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From the AWS Region selector on the navigation bar, select the Region where you get the error.
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In the navigation pane, choose AWS services.
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In the Search bar, enter Amazon SageMaker.
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Choose Amazon SageMaker.
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Select the quota that you want to increase. For the preceding example error message, select ml.p2.xlarge for endpoint usage.
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Choose Request quote increase.
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For Change quota value, enter the desired value.
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Choose Request.
This sends your request to AWS Support. Based on your use case and current usage, your request is either approved, denied, or partially approved.
Thanks for your reply . I tried to follow the instruction shared and tried to increase the quote as can be found here: https://github.com/andysingal/aws_issues/blob/main/Screenshot%202023-07-06%20at%203.02.34%20PM.png
However i am still getting error: clarify_processor_unbalanced = clarify.SageMakerClarifyProcessor( role=role, instance_count=1, instance_type='ml.c5.2xlarge', sagemaker_session=sess )
clarify_processor_unbalanced.run_pre_training_bias( ### BEGIN SOLUTION - DO NOT delete this comment for grading purposes data_config=data_config_unbalanced, # Replace None data_bias_config=bias_config_unbalanced, # Replace None ### END SOLUTION - DO NOT delete this comment for grading purposes methods=["CI", "DPL", "KL", "JS", "LP", "TVD", "KS"], wait=False, logs=False )
ERROR:
ResourceLimitExceeded Traceback (most recent call last) <ipython-input-18-2cd2c7618f12> in <cell line: 1>() ----> 1 clarify_processor_unbalanced.run_pre_training_bias( 2 ### BEGIN SOLUTION - DO NOT delete this comment for grading purposes 3 data_config=data_config_unbalanced, # Replace None 4 data_bias_config=bias_config_unbalanced, # Replace None 5 ### END SOLUTION - DO NOT delete this comment for grading purposes
9 frames /usr/local/lib/python3.10/dist-packages/botocore/client.py in make_api_call(self, operation_name, api
Can you try increasing the Processing job usage quota for ml.c5.2xlarge as shown here
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What is the current quota you have and what's the region?