Allow unhashable inputs to parallel_apply

Author: nhynes

torch/nn/parallel/parallel_apply.py

@@ -16,30 +16,31 @@ def parallel_apply(modules, inputs, kwargs_tup=None):
  lock = threading.Lock()
  results = {}
 
- def _worker(module, input, kwargs, results, lock):
+ def _worker(i, module, input, kwargs, results, lock):
  var_input = input
  while not isinstance(var_input, Variable):
  var_input = var_input[0]
  try:
  with torch.cuda.device_of(var_input):
  output = module(*input, **kwargs)
  with lock:
- results[input] = output
+ results[i] = output
  except Exception as e:
  with lock:
- results[input] = e
+ results[i] = e
 
  threads = [threading.Thread(target=_worker,
- args=(module, input, kwargs, results, lock),
+ args=(i, module, input, kwargs, results, lock),
  )
- for module, input, kwargs in zip(modules, inputs, kwargs_tup)]
+ for i, (module, input, kwargs) in
+ enumerate(zip(modules, inputs, kwargs_tup))]
 
  for thread in threads:
  thread.start()
  for thread in threads:
  thread.join()
  outputs = []
- for i in inputs:
+ for i in range(len(inputs)):
  output = results[i]
  if isinstance(output, Exception):
  raise output