class_docstr: Maintains a map from torch operations to their MIL values
  while building the graph. Can be used to process subgraphs recursively
  by pushing new context when stepping into a subgraph and popping that
  context when stepping out.
docstr: Lookup a name in the context. Note that since nested blocks must be
  able to access anything that was defined before them, we have to
  search all contexts for a name, starting with the most local scope.
docstr_tok: ["Lookup","a","name","in","the","context",".","Note","that","since","nested","blocks","must","be","able","to","access","anything","that","was","defined","before","them",",","we","have","to","search","all","contexts","for","a","name",",","starting","with","the","most","local","scope","."]
code: def __getitem__(self, torch_name: str) -> Var:
      """
      Lookup a name in the context. Note that since nested blocks must be
      able to access anything that was defined before them, we have to
      search all contexts for a name, starting with the most local scope.
      """
      for idx in reversed(range(len(self._current_graph))):
          current_graph = self._current_graph[idx]
          if torch_name in current_graph:
              return self._current_graph[idx][torch_name]
      raise ValueError(
          f"Torch var {torch_name} not found in context {self.name}"
      )
  
imports: from collections import OrderedDict
  from typing import List, Optional, Union
  import numpy
  import torch
  from torch.jit._script import RecursiveScriptModule
  from coremltools import _logger
  from coremltools._deps import _HAS_TORCH_EXPORT_API
  from coremltools.converters.mil._deployment_compatibility import AvailableTarget
  from coremltools.converters.mil.input_types import ImageType, InputType, TensorType
  from coremltools.converters.mil.mil import Builder
  from coremltools.converters.mil.mil import Function, Placeholder, Program, types
  from coremltools.converters.mil.mil.types import is_float
  from coremltools.converters.mil.mil.var import Var
  from .._utils import get_output_names
  from .internal_graph import InternalTorchIRGraph, InternalTorchIRNode
  from .ops import TorchFrontend, convert_nodes
  from .quantization_ops import _dequantized_weight
  from .torch_op_registry import _TORCH_OPS_REGISTRY
  from .torchir_passes import flatten_graph_input_values, flatten_graph_output_values, generate_tensor_assignment_ops, remove_getattr_nodes, transform_inplace_ops
  from .torchscript_utils import torch_to_mil_types
label_desc: Use image node_id 8 for calling the TranscriptionContext obj's underlying member method code with example usage: obj.__getitem__(torch_name) and returns: self