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2017-Spring Machine Learning prj, Yonsei Wonju
요구사항: 텐서보드 summary 요구사항에 따라 템플릿 구성
Modify epoch and batch size in train&test process
Neuron(perceptron function)
choose ReLU, Sigmoid
1st feed_dict
{<tf.Tensor 'X:0' shape=(?, 3072) dtype=float32>: array([[ 59, 43, 50, ..., 140, 84, 72],
[154, 126, 105, ..., 139, 142, 144],
[255, 253, 253, ..., 83, 83, 84],
...,
[145, 131, 115, ..., 89, 88, 91],
[146, 185, 248, ..., 146, 166, 238],
[203, 201, 208, ..., 114, 120, 126]], dtype=uint8), <tf.Tensor 'Y:0' shape=(?, 10) dtype=float32>: ...(생략) }
2nd feed_dict
<tf.Tensor 'X_1:0' shape=(?, 3072) dtype=float32>: array([[ 59, 43, 50, ..., 140, 84, 72],
[154, 126, 105, ..., 139, 142, 144],
[255, 253, 253, ..., 83, 83, 84],
...,
[145, 131, 115, ..., 89, 88, 91],
[146, 185, 248, ..., 146, 166, 238],
[203, 201, 208, ..., 114, 120, 126]], dtype=uint8), <tf.Tensor 'Y_1:0' shape=(?, 10) dtype=float32>: ...(생략) }
여기서 Tensor에 자동으로 붙는 이름(Name) 부여가 중복되는 경우 자동으로 _%d 형태로 붙으며, 이러한 상황으로 인하여 문제가 발생하였음.
이름 부여 방식을 바꿔주어야 해결될 것으로 예상됨.
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