tf.contrib.tpu.shard(
computation,
inputs=None,
num_shards=1,
input_shard_axes=None,
outputs_from_all_shards=True,
output_shard_axes=None,
infeed_queue=None,
device_assignment=None,
name=None
)
Defined in tensorflow/contrib/tpu/python/tpu/tpu.py
.
Shards computation
for parallel execution.
inputs
must be a list of Tensors or None (equivalent to an empty list), each
of which has a corresponding split axis (from input_shard_axes
). Each input
is split into num_shards
pieces along the corresponding axis, and
computation is applied to each shard in parallel.
Tensors are broadcast to all shards if they are lexically captured by
computation
. e.g.,
x = tf.constant(7) def computation(): return x + 3 ... = shard(computation, ...)
TODO(phawkins): consider adding support for broadcasting Tensors passed as inputs.
If outputs_from_all_shards
is true, the outputs from all shards of
computation
are concatenated back together along their output_shards_axes
.
Otherwise, each output is taken from an arbitrary shard.
Inputs and outputs of the computation must be at least rank-1 Tensors.
Args:
computation
: A Python function that builds a computation to apply to each shard of the input.inputs
: A list of input tensors or None (equivalent to an empty list). Each input tensor has a corresponding shard axes, given byinput_shard_axes
, which must have size divisible bynum_shards
.num_shards
: The number of shards.input_shard_axes
: A list of dimensions along which to shardinputs
, orNone
.None
means "shard all inputs along dimension 0". If notNone
, there must be one dimension per input.outputs_from_all_shards
: Boolean or list of boolean. For each output, ifTrue
, outputs from all shards are concatenated along the correspondingoutput_shard_axes
entry. Otherwise, each output is taken from an arbitrary shard. If the argument is a boolean, the argument's value is used for each output.output_shard_axes
: A list of dimensions along which to concatenate the outputs ofcomputation
, orNone
.None
means "concatenate all outputs along dimension 0". If notNone
, there must be one dimension per output. Ignored ifoutputs_from_all_shards
is False.infeed_queue
: If notNone
, theInfeedQueue
to use to augment the inputs ofcomputation
.device_assignment
: If notNone
, aDeviceAssignment
describing the mapping between logical cores in the computation with physical cores in the TPU topology. Uses a default device assignment ifNone
. TheDeviceAssignment
may be omitted if each shard of the computation uses only one core, and there is either only one shard, or the number of shards is equal to the number of cores in the TPU system.name
: (Deprecated) Does nothing.
Returns:
A list of output tensors.
Raises:
ValueError
: If num_shards <= 0ValueError
: If len(input_shard_axes) != len(inputs)ValueError
: If len(output_shard_axes) != len(outputs fromcomputation
)