Serializers¶
Implements base methods for serializing data for an inference endpoint.
- class sagemaker.base_serializers.BaseSerializer¶
Bases:
ABCAbstract base class for creation of new serializers.
Provides a skeleton for customization requiring the overriding of the method serialize and the class attribute CONTENT_TYPE.
- abstract serialize(data)¶
Serialize data into the media type specified by CONTENT_TYPE.
- abstract property CONTENT_TYPE¶
The MIME type of the data sent to the inference endpoint.
- class sagemaker.base_serializers.SimpleBaseSerializer(content_type='application/json')¶
Bases:
BaseSerializerAbstract base class for creation of new serializers.
This class extends the API of :class:~`sagemaker.serializers.BaseSerializer` with more user-friendly options for setting the Content-Type header, in situations where it can be provided at init and freely updated.
Initialize a
SimpleBaseSerializerinstance.- Parameters
content_type (str) – The MIME type to signal to the inference endpoint when sending
(default (request data) – “application/json”).
- property CONTENT_TYPE¶
The data MIME type set in the Content-Type header on prediction endpoint requests.
- class sagemaker.base_serializers.CSVSerializer(content_type='text/csv')¶
Bases:
SimpleBaseSerializerSerialize data of various formats to a CSV-formatted string.
Initialize a
CSVSerializerinstance.- Parameters
content_type (str) – The MIME type to signal to the inference endpoint when sending request data (default: “text/csv”).
- class sagemaker.base_serializers.NumpySerializer(dtype=None, content_type='application/x-npy')¶
Bases:
SimpleBaseSerializerSerialize data to a buffer using the .npy format.
Initialize a
NumpySerializerinstance.- Parameters
- class sagemaker.base_serializers.JSONSerializer(content_type='application/json')¶
Bases:
SimpleBaseSerializerSerialize data to a JSON formatted string.
Initialize a
SimpleBaseSerializerinstance.- Parameters
content_type (str) – The MIME type to signal to the inference endpoint when sending
(default (request data) – “application/json”).
- class sagemaker.base_serializers.IdentitySerializer(content_type='application/octet-stream')¶
Bases:
SimpleBaseSerializerSerialize data by returning data without modification.
This serializer may be useful if, for example, you’re sending raw bytes such as from an image file’s .read() method.
Initialize an
IdentitySerializerinstance.- Parameters
content_type (str) – The MIME type to signal to the inference endpoint when sending request data (default: “application/octet-stream”).
- class sagemaker.base_serializers.JSONLinesSerializer(content_type='application/jsonlines')¶
Bases:
SimpleBaseSerializerSerialize data to a JSON Lines formatted string.
Initialize a
JSONLinesSerializerinstance.- Parameters
content_type (str) – The MIME type to signal to the inference endpoint when sending request data (default: “application/jsonlines”).
- serialize(data)¶
Serialize data of various formats to a JSON Lines formatted string.
- class sagemaker.base_serializers.SparseMatrixSerializer(content_type='application/x-npz')¶
Bases:
SimpleBaseSerializerSerialize a sparse matrix to a buffer using the .npz format.
Initialize a
SparseMatrixSerializerinstance.- Parameters
content_type (str) – The MIME type to signal to the inference endpoint when sending request data (default: “application/x-npz”).
- serialize(data)¶
Serialize a sparse matrix to a buffer using the .npz format.
Sparse matrices can be in the
csc,csr,bsr,diaorcooformats.- Parameters
data (scipy.sparse.spmatrix) – The sparse matrix to serialize.
- Returns
A buffer containing the serialized sparse matrix.
- Return type
- class sagemaker.base_serializers.LibSVMSerializer(content_type='text/libsvm')¶
Bases:
SimpleBaseSerializerSerialize data of various formats to a LibSVM-formatted string.
The data must already be in LIBSVM file format: <label> <index1>:<value1> <index2>:<value2> …
It is suitable for sparse datasets since it does not store zero-valued features.
Initialize a
LibSVMSerializerinstance.- Parameters
content_type (str) – The MIME type to signal to the inference endpoint when sending request data (default: “text/libsvm”).
- serialize(data)¶
Serialize data of various formats to a LibSVM-formatted string.
- Parameters
data (object) – Data to be serialized. Can be a string or a file-like object.
- Returns
The data serialized as a LibSVM-formatted string.
- Return type
- Raises
ValueError – If unable to handle input format
- class sagemaker.base_serializers.DataSerializer(content_type='file-path/raw-bytes')¶
Bases:
SimpleBaseSerializerSerialize data in any file by extracting raw bytes from the file.
Initialize a
DataSerializerinstance.- Parameters
content_type (str) – The MIME type to signal to the inference endpoint when sending request data (default: “file-path/raw-bytes”).
- class sagemaker.base_serializers.StringSerializer(content_type='text/plain')¶
Bases:
SimpleBaseSerializerEncode the string to utf-8 bytes.
Initialize a
StringSerializerinstance.- Parameters
content_type (str) – The MIME type to signal to the inference endpoint when sending request data (default: “text/plain”).
- class sagemaker.base_serializers.TorchTensorSerializer(content_type='tensor/pt')¶
Bases:
SimpleBaseSerializerSerialize torch.Tensor to a buffer by converting tensor to numpy and call NumpySerializer.
- Parameters
data (object) – Data to be serialized. The data must be of torch.Tensor type.
- Returns
The data serialized as raw-bytes from the input.
- Return type
raw-bytes
Initialize a
SimpleBaseSerializerinstance.- Parameters
content_type (str) – The MIME type to signal to the inference endpoint when sending
(default (request data) – “application/json”).
Implements methods for serializing data for an inference endpoint.
- sagemaker.serializers.retrieve_options(region=None, model_id=None, model_version=None, hub_arn=None, tolerate_vulnerable_model=False, tolerate_deprecated_model=False, sagemaker_session=<sagemaker.session.Session object>, config_name=None)¶
Retrieves the supported serializers for the model matching the given arguments.
- Parameters
region (str) – The AWS Region for which to retrieve the supported serializers. Defaults to
None.model_id (str) – The model ID of the model for which to retrieve the supported serializers. (Default: None).
model_version (str) – The version of the model for which to retrieve the supported serializers. (Default: None).
hub_arn (str) – The arn of the SageMaker Hub for which to retrieve model details from. (Default: None).
tolerate_vulnerable_model (bool) – True if vulnerable versions of model specifications should be tolerated (exception not raised). If False, raises an exception if the script used by this version of the model has dependencies with known security vulnerabilities. (Default: False).
tolerate_deprecated_model (bool) – True if deprecated models should be tolerated (exception not raised). False if these models should raise an exception. (Default: False).
sagemaker_session (sagemaker.session.Session) – A SageMaker Session object, used for SageMaker interactions. If not specified, one is created using the default AWS configuration chain. (Default: sagemaker.jumpstart.constants.DEFAULT_JUMPSTART_SAGEMAKER_SESSION).
config_name (Optional[str]) – Name of the JumpStart Model config to apply. (Default: None).
- Returns
The supported serializers to use for the model.
- Return type
List[SimpleBaseSerializer]
- Raises
ValueError – If the combination of arguments specified is not supported.
- sagemaker.serializers.retrieve_default(region=None, model_id=None, model_version=None, hub_arn=None, tolerate_vulnerable_model=False, tolerate_deprecated_model=False, model_type=JumpStartModelType.OPEN_WEIGHTS, sagemaker_session=<sagemaker.session.Session object>, config_name=None)¶
Retrieves the default serializer for the model matching the given arguments.
- Parameters
region (str) – The AWS Region for which to retrieve the default serializer. Defaults to
None.model_id (str) – The model ID of the model for which to retrieve the default serializer. (Default: None).
model_version (str) – The version of the model for which to retrieve the default serializer. (Default: None).
hub_arn (str) – The arn of the SageMaker Hub for which to retrieve model details from. (Default: None).
tolerate_vulnerable_model (bool) – True if vulnerable versions of model specifications should be tolerated (exception not raised). If False, raises an exception if the script used by this version of the model has dependencies with known security vulnerabilities. (Default: False).
tolerate_deprecated_model (bool) – True if deprecated models should be tolerated (exception not raised). False if these models should raise an exception. (Default: False).
sagemaker_session (sagemaker.session.Session) – A SageMaker Session object, used for SageMaker interactions. If not specified, one is created using the default AWS configuration chain. (Default: sagemaker.jumpstart.constants.DEFAULT_JUMPSTART_SAGEMAKER_SESSION).
config_name (Optional[str]) – Name of the JumpStart Model config to apply. (Default: None).
model_type (JumpStartModelType) –
- Returns
The default serializer to use for the model.
- Return type
- Raises
ValueError – If the combination of arguments specified is not supported.