class_docstr: Manually specify the compression strategy depending on tensor key
code: def __init__(
      self,
      tensor_compressions: Union[
          Sequence[CompressionBase], Mapping[Key, CompressionBase]
      ],
  ):
      self.tensor_compressions = tensor_compressions
  
imports: from abc import ABC, abstractmethod
  from typing import Mapping, Sequence, Union
  import torch
  from hivemind.compression.base import CompressionBase, CompressionInfo, Key, NoCompression, TensorRole
  from hivemind.compression.serialization import deserialize_torch_tensor
  from hivemind.proto import runtime_pb2
label_desc: Use image node_id 1 to create a new PerTensorCompression object from inherited base classes: AdaptiveCompressionBase with example: obj = PerTensorCompression(tensor_compressions)