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
91 lines
3.2 KiB
Plaintext
91 lines
3.2 KiB
Plaintext
path: "tensorflow.distribute.StrategyExtended"
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tf_class {
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is_instance: "<class \'tensorflow.python.distribute.distribute_lib.StrategyExtendedV1\'>"
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is_instance: "<class \'tensorflow.python.distribute.distribute_lib.StrategyExtendedV2\'>"
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is_instance: "<type \'object\'>"
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member {
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name: "experimental_between_graph"
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mtype: "<type \'property\'>"
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}
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member {
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name: "experimental_require_static_shapes"
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mtype: "<type \'property\'>"
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}
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member {
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name: "experimental_should_init"
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mtype: "<type \'property\'>"
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}
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member {
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name: "parameter_devices"
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mtype: "<type \'property\'>"
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}
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member {
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name: "should_checkpoint"
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mtype: "<type \'property\'>"
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}
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member {
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name: "should_save_summary"
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mtype: "<type \'property\'>"
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}
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member {
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name: "worker_devices"
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mtype: "<type \'property\'>"
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}
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member_method {
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name: "__init__"
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argspec: "args=[\'self\', \'container_strategy\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "batch_reduce_to"
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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_to"
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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: "call_for_each_replica"
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argspec: "args=[\'self\', \'fn\', \'args\', \'kwargs\'], varargs=None, keywords=None, defaults=[\'()\', \'None\'], "
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}
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member_method {
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name: "colocate_vars_with"
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argspec: "args=[\'self\', \'colocate_with_variable\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "experimental_make_numpy_dataset"
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argspec: "args=[\'self\', \'numpy_input\', \'session\'], varargs=None, keywords=None, defaults=[\'None\'], "
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}
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member_method {
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name: "experimental_run_steps_on_iterator"
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argspec: "args=[\'self\', \'fn\', \'iterator\', \'iterations\', \'initial_loop_values\'], varargs=None, keywords=None, defaults=[\'1\', \'None\'], "
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}
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member_method {
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name: "non_slot_devices"
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argspec: "args=[\'self\', \'var_list\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "read_var"
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argspec: "args=[\'self\', \'v\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "reduce_to"
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argspec: "args=[\'self\', \'reduce_op\', \'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: "update"
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argspec: "args=[\'self\', \'var\', \'fn\', \'args\', \'kwargs\', \'group\'], varargs=None, keywords=None, defaults=[\'()\', \'None\', \'True\'], "
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}
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member_method {
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name: "update_non_slot"
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argspec: "args=[\'self\', \'colocate_with\', \'fn\', \'args\', \'kwargs\', \'group\'], varargs=None, keywords=None, defaults=[\'()\', \'None\', \'True\'], "
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}
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member_method {
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name: "value_container"
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argspec: "args=[\'self\', \'value\'], varargs=None, keywords=None, defaults=None"
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}
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member_method {
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name: "variable_created_in_scope"
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argspec: "args=[\'self\', \'v\'], varargs=None, keywords=None, defaults=None"
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}
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}
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