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path: "tensorflow.ConditionalAccumulator"
tf_class {
is_instance: "<class \'tensorflow.python.ops.data_flow_ops.ConditionalAccumulator\'>"
is_instance: "<class \'tensorflow.python.ops.data_flow_ops.ConditionalAccumulatorBase\'>"
is_instance: "<type \'object\'>"
member {
name: "accumulator_ref"
mtype: "<type \'property\'>"
}
member {
name: "dtype"
mtype: "<type \'property\'>"
}
member {
name: "name"
mtype: "<type \'property\'>"
}
member_method {
name: "__init__"
argspec: "args=[\'self\', \'dtype\', \'shape\', \'shared_name\', \'name\'], varargs=None, keywords=None, defaults=[\'None\', \'None\', \'conditional_accumulator\'], "
}
member_method {
name: "apply_grad"
argspec: "args=[\'self\', \'grad\', \'local_step\', \'name\'], varargs=None, keywords=None, defaults=[\'0\', \'None\'], "
}
member_method {
name: "num_accumulated"
argspec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
member_method {
name: "set_global_step"
argspec: "args=[\'self\', \'new_global_step\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
member_method {
name: "take_grad"
argspec: "args=[\'self\', \'num_required\', \'name\'], varargs=None, keywords=None, defaults=[\'None\'], "
}
}
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