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update API doc for single-node distributed training (#198)
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python/sparkdl/horovod/runner_base.py

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@@ -47,7 +47,7 @@ def __init__(self, np):
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which maps to a GPU on a GPU cluster or a CPU core on a CPU cluster.
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Accepted values are:
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- If -1, this will spawn a subprocess on the driver node to run the Horovod job locally.
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- If <0, this will spawn -np subprocesses on the driver node to run Horovod locally.
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Training stdout and stderr messages go to the notebook cell output, and are also
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available in driver logs in case the cell output is truncated. This is useful for
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debugging and we recommend testing your code under this mode first. However, be
@@ -63,8 +63,6 @@ def __init__(self, np):
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- If 0, this will use all task slots on the cluster to launch the job.
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"""
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self.num_processor = np
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if self.num_processor < -1:
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raise ValueError("Invalid number of processes: np = %s" % str(self.num_processor))
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def run(self, main, **kwargs):
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"""

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