class_docstr: Deserialize stream to torch.Tensor.
  
  Args:
      stream (botocore.response.StreamingBody): Data to be deserialized.
      content_type (str): The MIME type of the data.
  
  Returns:
      torch.Tensor: The data deserialized into a torch Tensor.
class_docstr_tok: ["Deserialize","stream","to","torch.Tensor",".","Args",":","stream","(","botocore.response.StreamingBody",")",":","Data","to","be","deserialized",".","content_type","(","str",")",":","The","MIME","type","of","the","data",".","Returns",":","torch.Tensor",":","The","data","deserialized","into","a","torch","Tensor","."]
docstr: Deserialize streamed data to TorchTensor
  
  See https://pytorch.org/docs/stable/generated/torch.from_numpy.html
  
  Args:
      stream (botocore.response.StreamingBody): Data to be deserialized.
      content_type (str): The MIME type of the data.
  
  Returns:
      list: A list of TorchTensor serializable objects.
docstr_tok: ["Deserialize","streamed","data","to","TorchTensor","See","https",":","\/\/pytorch.org\/docs\/stable\/generated\/torch.from_numpy.html","Args",":","stream","(","botocore.response.StreamingBody",")",":","Data","to","be","deserialized",".","content_type","(","str",")",":","The","MIME","type","of","the","data",".","Returns",":","list",":","A","list","of","TorchTensor","serializable","objects","."]
code: def deserialize(self, stream, content_type="tensor/pt"):
      """Deserialize streamed data to TorchTensor
  
      See https://pytorch.org/docs/stable/generated/torch.from_numpy.html
  
      Args:
          stream (botocore.response.StreamingBody): Data to be deserialized.
          content_type (str): The MIME type of the data.
  
      Returns:
          list: A list of TorchTensor serializable objects.
      """
      try:
          numpy_array = self.numpy_deserializer.deserialize(
              stream=stream, content_type="application/x-npy"
          )
          return self.convert_npy_to_tensor(numpy_array)
      except Exception:
          raise ValueError(
              "Unable to deserialize your data to torch.Tensor.\
                      Please provide custom deserializer in InferenceSpec."
          )
  
imports: from __future__ import absolute_import
  import csv
  import abc
  import codecs
  import io
  import json
  import numpy
  from six import with_metaclass
  from sagemaker.utils import DeferredError
label_desc: Use image node_id 2 for calling the TorchTensorDeserializer obj's underlying member method code with example usage: obj.deserialize(stream, content_type) and returns: self