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First, thanks for you work, it's very useful for inference BERT-like modes. Hope your paper get published soon.
And something i'm confused about is the FLOP of dense layer, which is in the section 4.1.
As far as i know, the FLOPs of fully connect layer with bias = 2 * I * O
I=input neuron numbers, O=output neuron numbers.
For the Fully-connect layer 128 ->128, FLOPs = 2 * 128 * 128 = 32,768
And in the Table 1, the answer is 4.2M, which is much higher than i got.
Can you release your method to calculate the answer ?
The text was updated successfully, but these errors were encountered:
First, thanks for you work, it's very useful for inference BERT-like modes. Hope your paper get published soon.
And something i'm confused about is the FLOP of dense layer, which is in the section 4.1.
As far as i know, the FLOPs of fully connect layer with bias = 2 * I * O
I=input neuron numbers, O=output neuron numbers.
For the Fully-connect layer 128 ->128, FLOPs = 2 * 128 * 128 = 32,768
And in the Table 1, the answer is 4.2M, which is much higher than i got.
Can you release your method to calculate the answer ?
In BERT, if the input sentence contains 128 words, the FLOPs should be 2 * 128 * 128 * 128 = 4194304.
First, thanks for you work, it's very useful for inference BERT-like modes. Hope your paper get published soon.
And something i'm confused about is the FLOP of dense layer, which is in the section 4.1.
As far as i know, the FLOPs of fully connect layer with bias = 2 * I * O
For the Fully-connect layer 128 ->128, FLOPs = 2 * 128 * 128 = 32,768
And in the Table 1, the answer is 4.2M, which is much higher than i got.
Can you release your method to calculate the answer ?
The text was updated successfully, but these errors were encountered: