Comments (2)
I couldn't find the function of 'depthwise_conv1d'. Considering that conv1d is actually implemented via reshaping the input and then send it to conv2d, may be what you mentioned is exactly the current implementation of conv1d?
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In your version of CIN, the number of weight in k-th layer is field_nums[-1] * field_nums[0] *layer_size * dim。
The Con1d is the two-dimensional weight. But in the CIN analysis(section 3.2) , the CIN is independant of embedding dim which is just ( h_k * h_{k-1) * m in k-th layer)
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Related Issues (19)
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