rithwik-db commented on code in PR #39267:
URL: https://github.com/apache/spark/pull/39267#discussion_r1068750849
##########
python/pyspark/ml/torch/distributor.py:
##########
@@ -428,6 +432,84 @@ def _run_local_training(
return output
+ def _get_spark_task_program(
+ self, framework_wrapper_fn: Optional[Callable], train_fn:
Union[Callable, str], *args: Any
+ ) -> Callable:
+ num_processes = self.num_processes
+ num_tasks = self.num_tasks
+ use_gpu = self.use_gpu
+ input_params = self.input_params
+
+ # Spark task program
+ def wrapped_train_fn(_): # type: ignore[no-untyped-def]
+ import os
+ from pyspark import BarrierTaskContext
+
+ CUDA_VISIBLE_DEVICES = "CUDA_VISIBLE_DEVICES"
+
+ # The idea of setting the random port to 0 doesn't seem to work?
Review Comment:
Something like the following seems to error:
```
import socket
sock = socket.socket()
sock.bind((master_address, 0))
port = sock.getsockname()[1]
```
So I just find a port using randomness.
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