NumPy로 구현한 딥러닝 라이브러리입니다. (자동 미분 지원)

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Deep Learningdl_numpy
Overview

Deep Learning Library only using NumPy

본 레포지토리는 NumPy 만으로 구현한 딥러닝 라이브러리입니다. 자동 미분이 구현되어 있습니다.

자동 미분

자동 미분은 미분을 자동으로 계산해주는 기능입니다. 아래 코드는 자동 미분을 활용해 역전파를 수행합니다 :

>>> from dl_numpy import Tensor, math
>>> a, b = Tensor([2, 1]), Tensor([-0.1, 0.3])
>>> out = math.sum(a * b)  # calculation
>>> grad = out.backward()  # backward
>>> grad[id(a)]  # gradient for a
[0.1 0.3]

계산 그래프

계산 그래프를 시각화할 수 있습니다. Tensor 연산 후 graph.render()를 호출하세요 :

>>> out = a * b + math.matmul(a, b) ** 2 / a
>>> out.graph.render('calc_graph', format='svg')  # save graph as a svg file

레이어

활성화 함수, loss 함수, layer가 모듈 형태로 정의되어 있습니다.

자동 미분이 구현되어 있으므로 각 모듈의 도함수를 정의할 필요는 없습니다. 코드 참고

>>> from dl_numpy.layer.activation import sigmoid
>>> from dl_numpy.layer.loss import mse
>>> from dl_numpy.layer import Linear
>>> m = Linear(8, 32, activation=sigmoid)  # linear layer (Wx+b)
>>> out = m(x)  # forward
>>> loss = mse(y, out)  # MSE loss
>>> grad = loss.backward()  # backward
>>> m.apply_grad(grad, lr=0.01)  # update parameters

예제

※ 본 프로젝트는 이론 공부를 목적으로 진행되었습니다.

Owner
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안녕하세요 디미고에 재학 중인 18살의 고등학생입니다! 머신 러닝에 관심이 아주 많습니다🤗 (Hello, I'm a 16-year-old student in Dimigo. I'm very interested in Machine Learning.)
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