def allreduce(value,
name=None,
average=True,
prescale_factor=1.0,
postscale_factor=1.0,
op=None,
compression=Compression.none):
"""
Perform an allreduce on a tensor-compatible value.
Arguments:
value: A tensor-compatible value to reduce.
The shape of the input must be identical across all ranks.
name: Optional name for the constants created by this operation.
average:
.. warning:: .. deprecated:: 0.19.0
Use `op` instead. Will be removed in v0.21.0.
prescale_factor: Multiplicative factor to scale tensor before allreduce.
postscale_factor: Multiplicative factor to scale tensor after allreduce.
op: The reduction operation to combine tensors across different ranks.
Defaults to Average if None is given.
compression: Compression algorithm used to reduce the amount of data
sent and received by each worker node. Defaults to not
using compression.
"""
return _impl.allreduce(backend=K,
value=value,
name=name,
average=average,
prescale_factor=prescale_factor,
postscale_factor=postscale_factor,
op=op,
compression=compression)
def allreduce(value, name=None, average=True):
"""
Perform an allreduce on a tensor-compatible value.
Arguments:
value: A tensor-compatible value to reduce.
The shape of the input must be identical across all ranks.
name: Optional name for the constants created by this operation.
average: If True, computes the average over all ranks.
Otherwise, computes the sum over all ranks.
"""
return _impl.allreduce(K, value, name, average)
def allreduce(value, name=None, average=True, prescale_factor=1.0, postscale_factor=1.0):
"""
Perform an allreduce on a tensor-compatible value.
Arguments:
value: A tensor-compatible value to reduce.
The shape of the input must be identical across all ranks.
name: Optional name for the constants created by this operation.
average: If True, computes the average over all ranks.
Otherwise, computes the sum over all ranks.
prescale_factor: Multiplicative factor to scale tensor before allreduce.
postscale_factor: Multiplicative factor to scale tensor after allreduce.
"""
return _impl.allreduce(K, value, name, average, prescale_factor, postscale_factor)
