Comments (1)
I think with the definition of the network and loss function, the backpropagation should be auto computed, why should we explicitly definite it in the code?
because we are using numpy instead of torch, it is necessary for us to build the calculation diagram manually
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Related Issues (20)
- Usage of the LSTM
- action recogniton
- A parameter (x_dim) appears to be unused
- Explain self.wi = rand_arr(-0.1, 0.1, mem_cell_ct, concat_len)
- line 85&86:if s_prev == None: s_prev = np.zeros_like(self.state.s) HOT 5
- new dataset HOT 1
- Swift port
- why there is no 0.5* in the equation of the derivative of sate(t) ? HOT 4
- How to predict a new sequence ?
- Execution problem HOT 1
- can't convergence
- I have a question of ds,how to compulete ds?
- I don't understand wi_diff wf_diff etc
- The tanh_derivative should be : 1. + values**2 HOT 4
- self.state.h = self.state.s * self.state.o HOT 1
- lstm.py the 97 line
- loss compute
- You forget the tanh function in the last computation in the part of def bottom_data_is(): HOT 4
- Error in using 2 outputs
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