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Not sure if you are using a sample code or writing on your own. If you can share the details, that would be helpful.
If you are using Image Classification - MXNet, the SageMaker Image Classification algorithm supports both RecordIO (application/x-recordio) and image (image/png, image/jpeg, and application/x-image) content types for training in file mode, and supports the RecordIO (application/x-recordio) content type for training in pipe mode. However, you can also train in pipe mode using the image files (image/png, image/jpeg, and application/x-image), without creating RecordIO files, by using the augmented manifest format.
Reference : https://docs.aws.amazon.com/sagemaker/latest/dg/image-classification.html
Dear @aws-user-Nitin, tnx for your comment. No I use Image Classification - MXNet, the SageMaker Image Classification algorithm itself. I havent impelement any coding yet. I also tested with Pipe and (application/x-recordio and application/x-image ) and it still do not work. You can contact me for more demonstation via skype/teams greencomputinguae at g mail dot c@m
with leave type for channel emtpy as optional:
ClientError: Unable to initialize the algorithm. ContentType for channel 'train_lst' is empty. Please set content type for channel 'train_lst'. (caused by KeyError) Caused by: 'train_lst', exit code: 2
with setting type for channel application/x-image: ClientError: ContentType must be specified for train channel., exit code: 2
By setting to application/x-recordio ClientError: Invalid RecordIO format. Please make sure that the RecordIO files are not corrupted. , exit code: 2
By setting to application/x-image:
ClientError: Invalid RecordIO format. Please make sure that the RecordIO files are not corrupted. , exit code: 2
It is strange, if it mentions the field is optional, then why user force to set it?

Can you provide more information on how you are creating the estimator and passing the data. Looks like the data path the script is reading is wrong.
@arun tnx for your comment. I am not sure what you mean by estimator but I pass the data via S3 location with S3 data type S3prefix and s3 data distribution type:FullyReplicate. Actually, two channel are created for training/validation and two more channels for lables for training and validation.