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밑바닥부터 시작하는 데이터 과학 데이터 분석을 위한 파이썬 프로그래밍과 수학·통계 기초
book

밑바닥부터 시작하는 데이터 과학 데이터 분석을 위한 파이썬 프로그래밍과 수학·통계 기초

by Joel Grus, Hangyeol Kim, Seongju Ha, Eunjung Park
May 2022
Beginner to intermediate
448 pages
13h 7m
Korean
Insight
Content preview from 밑바닥부터 시작하는 데이터 과학 데이터 분석을 위한 파이썬 프로그래밍과 수학·통계 기초
Data Science
326
󻱴󽴔󽴔󻱟󻪿󻪃󽴔󼅧󺹻
if self.last
_
input
_
id is not None:
zero
_
row = [0 for
_
in range(self.embedding
_
dim)]
self.grad[self.last
_
input
_
id] = zero
_
row
self.last
_
input
_
id = self.input
_
id
self.grad[self.input
_
id] = gradient
기존
params
grads
메서드를 오버라이딩해야 한다.
def params(self) -> Iterable[Tensor]:
return [self.embeddings]
def grads(self) -> Iterable[Tensor]:
return [self.grad]
앞서 말했듯, 단어 벡터를 생성하기 위한 전용 서브클래스를 만들 것이다. 이 경
우, 임베딩 벡터의 개수는 사전의 크기에 따라 달라지므로, 아예
vocab
을 입력으
로 받자.
class TextEmbedding(Embedding):
def
__
init
__
(self, vocab: Vocabulary, embedding
_
dim: int) -> None:
# superclass
생성자
호출
super().
__
init
__
(vocab.size, embedding
_
dim)
#
사전은
유지
self.vocab ...
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Publisher Resources

ISBN: 9788966262571