code: def select_compilers_from_hardware_torch(device: Device):
      from nebullvm.optional_modules.utils import torch_is_available
  
      compilers = []
      if torch_is_available():
          compilers.append(ModelCompiler.TORCHSCRIPT)
          if tvm_is_available():
              compilers.append(ModelCompiler.APACHE_TVM)
          if bladedisc_is_available():
              compilers.append(ModelCompiler.BLADEDISC)
          if torch_neuron_is_available():
              compilers.append(ModelCompiler.TORCH_NEURON)
  
          if device.type is DeviceType.CPU:
              if deepsparse_is_available():
                  compilers.append(ModelCompiler.DEEPSPARSE)
              if intel_neural_compressor_is_available():
                  compilers.append(
                      ModelCompiler.INTEL_NEURAL_COMPRESSOR
                  )
          elif device.type is DeviceType.GPU:
              if torch_tensorrt_is_available:
                  compilers.append(ModelCompiler.TENSOR_RT)
      return compilers
  
file_path: nebuly/optimization/nebullvm/nebullvm/operations/optimizations/compilers/utils.py
imports: from pathlib import Path
  import nebullvm
  from nebullvm.core.models import Device, ModelCompiler, DeviceType
label_desc: Use image node_id 14 for calling a global function with example usage: select_compilers_from_hardware_torch(device) and returns: compilers