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# automatically generated by the FlatBuffers compiler, do not modify
# namespace: libtextclassifier3
import flatbuffers
from flatbuffers.compat import import_numpy
np = import_numpy()
class VocabModel(object):
__slots__ = ['_tab']
@classmethod
def GetRootAsVocabModel(cls, buf, offset):
n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
x = VocabModel()
x.Init(buf, n + offset)
return x
@classmethod
def VocabModelBufferHasIdentifier(cls, buf, offset, size_prefixed=False):
return flatbuffers.util.BufferHasIdentifier(buf, offset, b"\x54\x43\x32\x20", size_prefixed=size_prefixed)
# VocabModel
def Init(self, buf, pos):
self._tab = flatbuffers.table.Table(buf, pos)
# VocabModel
def VocabTrie(self, j):
o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
if o != 0:
a = self._tab.Vector(o)
return self._tab.Get(flatbuffers.number_types.Uint8Flags, a + flatbuffers.number_types.UOffsetTFlags.py_type(j * 1))
return 0
# VocabModel
def VocabTrieAsNumpy(self):
o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
if o != 0:
return self._tab.GetVectorAsNumpy(flatbuffers.number_types.Uint8Flags, o)
return 0
# VocabModel
def VocabTrieLength(self):
o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
if o != 0:
return self._tab.VectorLen(o)
return 0
# VocabModel
def VocabTrieIsNone(self):
o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4))
return o == 0
# VocabModel
def BeginnerLevel(self):
o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6))
if o != 0:
x = self._tab.Indirect(o + self._tab.Pos)
from libtextclassifier3.BitVectorData import BitVectorData
obj = BitVectorData()
obj.Init(self._tab.Bytes, x)
return obj
return None
# VocabModel
def DoNotTriggerInUpperCase(self):
o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
if o != 0:
x = self._tab.Indirect(o + self._tab.Pos)
from libtextclassifier3.BitVectorData import BitVectorData
obj = BitVectorData()
obj.Init(self._tab.Bytes, x)
return obj
return None
# VocabModel
def TriggeringLocales(self):
o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(10))
if o != 0:
return self._tab.String(o + self._tab.Pos)
return None
# VocabModel
def TargetClassificationScore(self):
o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(12))
if o != 0:
return self._tab.Get(flatbuffers.number_types.Float32Flags, o + self._tab.Pos)
return 1.0
# VocabModel
def PriorityScore(self):
o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(14))
if o != 0:
return self._tab.Get(flatbuffers.number_types.Float32Flags, o + self._tab.Pos)
return 0.0
def VocabModelStart(builder): builder.StartObject(6)
def VocabModelAddVocabTrie(builder, vocabTrie): builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(vocabTrie), 0)
def VocabModelStartVocabTrieVector(builder, numElems): return builder.StartVector(1, numElems, 1)
def VocabModelAddBeginnerLevel(builder, beginnerLevel): builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(beginnerLevel), 0)
def VocabModelAddDoNotTriggerInUpperCase(builder, doNotTriggerInUpperCase): builder.PrependUOffsetTRelativeSlot(2, flatbuffers.number_types.UOffsetTFlags.py_type(doNotTriggerInUpperCase), 0)
def VocabModelAddTriggeringLocales(builder, triggeringLocales): builder.PrependUOffsetTRelativeSlot(3, flatbuffers.number_types.UOffsetTFlags.py_type(triggeringLocales), 0)
def VocabModelAddTargetClassificationScore(builder, targetClassificationScore): builder.PrependFloat32Slot(4, targetClassificationScore, 1.0)
def VocabModelAddPriorityScore(builder, priorityScore): builder.PrependFloat32Slot(5, priorityScore, 0.0)
def VocabModelEnd(builder): return builder.EndObject()
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