msavinash1139
India
modify tensorflow network to use binary instead of onehot encoding
- 状态: Closed
- 奖金: $20
- 参赛作品已收到: 2
- 获胜者: msavinash1139
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竞赛简介
I need a simple change made to this sample code (attached). It was downloaded from https://github.com/atramos/titonn
Specifically I want to use a 7-bit binary encoding instead of the current one-hot encoding for each encoded character. I don't know how to do this in TF so you need to figure this out for me. For example the letter 'A' should be encoded as seven fields with value 1,0,0,0,0,0,1 (0b1000001 = 65 = equals 'A' in ASCII). In the current code only 6 values are allowed (a, b, c, d, e, f) but after this change, the entire 7-bit ASCII character set will be allowed.
This means also a different error function has to be used instead of softmax_cross_entropy_with_logits, but I don't know in advance what the correct function is. I will know the correct one when I see it in a working solution. Please discuss your reasoning in the comments so that I can be confident you have the right solution.
Contest will become #guaranteed after I see at least one serious submission.
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此竞赛的顶尖作品
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dellkj1996 Algeria
公共说明面板
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dellkj1996
- 3 年 之前
Can you check entries and suggestions please
- 3 年 之前
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anubhavkumarc
- 3 年 之前
If it's just about representing every character, why don't you just use sparse one hot encoding? You can represent the entire charset with that while using the predefined loss function.
I will try working on the binary encoding loss and submit it later though- 3 年 之前
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竞赛主办者 - 3 年 之前
I am not familiar with sparse one-hot encoding. Does it reduce memory utilization?
- 3 年 之前
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anubhavkumarc
- 3 年 之前
It does because it uses sparse structures rather than a full blown array. One hot encoding has arrays which are mostly empty with only one position with the data, and sparse vectors can take advantage of that for it to be represented with just the position of that vector and the size of the array
- 3 年 之前
