class_docstr: Class that handles conversion of pytorch models to the MIL format.
  
  Models passed to the @TorchConverter go from:
  Loaded-Torch Model -> Internal Graph -> PyMIL
docstr: Converts an InputType into a Placeholder.
  
  _input: TensorType
docstr_tok: ["Converts","an","InputType","into","a","Placeholder",".","_input",":","TensorType"]
code: def _create_placeholder(
      _input: TensorType,
  ) -> Placeholder:
      """
      Converts an InputType into a Placeholder.
  
      _input: TensorType
      """
      shape = _input.shape.symbolic_shape
      dtype = _input.dtype
      # int64 and fp64 are not supported, so they are mapped to int32 / fp32 accordingly
      if dtype == types.int64:
          dtype = types.int32
      elif dtype == types.fp64:
          dtype = types.fp32
      return mb.placeholder(shape, dtype=dtype)
  
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 5 for calling the TorchConverter obj's underlying member method code with example usage: obj._create_placeholder(_input) and returns: mb