use imagenet spawn (tinygrad#4096)

examples/mlperf/model_train.py

@@ -2,6 +2,7 @@
 import os
 import time
 from tqdm import tqdm
+import multiprocessing
 
 from tinygrad import Device, GlobalCounters, Tensor, TinyJit, dtypes
 from tinygrad.helpers import getenv, BEAM, WINO
@@ -251,6 +252,7 @@ def train_maskrcnn():
   pass
 
 if __name__ == "__main__":
+  multiprocessing.set_start_method('spawn')
   with Tensor.train():
     for m in getenv("MODEL", "resnet,retinanet,unet3d,rnnt,bert,maskrcnn").split(","):
       nm = f"train_{m}"

tinygrad/device.py

@@ -1,7 +1,7 @@
 from __future__ import annotations
 from collections import defaultdict
 from typing import TYPE_CHECKING, Any, List, Optional, Dict, Tuple, ClassVar, NamedTuple
-import importlib, inspect, functools, pathlib, time, ctypes
+import importlib, inspect, functools, pathlib, time, ctypes, os
 from tinygrad.helpers import ansilen, prod, getenv, colored, all_int, to_function_name, from_mv, flat_mv, diskcache_get, diskcache_put
 from tinygrad.helpers import DEBUG, CACHECOLLECTING, BEAM, NOOPT, GlobalCounters
 from tinygrad.shape.symbolic import Variable, sym_infer, sint
@@ -23,6 +23,7 @@ def canonicalize(self, device:Optional[str]) -> str: return self._canonicalize(d
   def __getitem__(self, ix:str) -> Compiled: return self.__get_canonicalized_item(self.canonicalize(ix))
   @functools.lru_cache(maxsize=None)  # this class is a singleton, pylint: disable=method-cache-max-size-none
   def __get_canonicalized_item(self, ix:str) -> Compiled:
+    if DEBUG >= 1: print(f"opening device {ix} from pid:{os.getpid()}")
     x = ix.split(":")[0].upper()
     return [cls for cname, cls in inspect.getmembers(importlib.import_module(f'tinygrad.runtime.ops_{x.lower()}')) if (cname.lower() == x.lower() + "device") and x in self._devices][0](ix)  # noqa: E501
   @functools.cached_property