fa08cfd489
This contains all performance hints to the API. Currently there's only bytes_per_pack, which splits large batches into multiple packs allows overlapping communication and computation. Currently we can only pack if all Tensors in the batch have known shapes. PiperOrigin-RevId: 297269428 Change-Id: Iaf7d7d3adf7c6cad59aa6079fbcd36b31e92c4b5
35 lines
1.6 KiB
Plaintext
35 lines
1.6 KiB
Plaintext
path: "tensorflow.distribute.ReductionToOneDevice"
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tf_class {
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is_instance: "<class \'tensorflow.python.distribute.cross_device_ops.ReductionToOneDevice\'>"
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is_instance: "<class \'tensorflow.python.distribute.cross_device_ops.CrossDeviceOps\'>"
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is_instance: "<type \'object\'>"
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member_method {
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name: "__init__"
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argspec: "args=[\'self\', \'reduce_to_device\', \'accumulation_fn\'], varargs=None, keywords=None, defaults=[\'None\', \'None\'], "
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}
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member_method {
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name: "batch_reduce"
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argspec: "args=[\'self\', \'reduce_op\', \'value_destination_pairs\', \'experimental_hints\'], varargs=None, keywords=None, defaults=[\'None\'], "
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}
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member_method {
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name: "batch_reduce_implementation"
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argspec: "args=[\'self\', \'reduce_op\', \'value_destination_pairs\', \'experimental_hints\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "broadcast"
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argspec: "args=[\'self\', \'tensor\', \'destinations\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "broadcast_implementation"
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argspec: "args=[\'self\', \'tensor\', \'destinations\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "reduce"
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argspec: "args=[\'self\', \'reduce_op\', \'per_replica_value\', \'destinations\', \'experimental_hints\'], varargs=None, keywords=None, defaults=[\'None\'], "
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}
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member_method {
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name: "reduce_implementation"
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argspec: "args=[\'self\', \'reduce_op\', \'per_replica_value\', \'destinations\', \'experimental_hints\'], varargs=None, keywords=None, defaults=None"
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}
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}
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