Adding problem #5
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…itialization for self.D in RNN_Cell.py
…code for adding problem
KyleGoyette
requested changes
Mar 17, 2020
| # print("self.UppT: ", self.UppT) | ||
| # print("self.M: ", self.M) | ||
| # print("self.alphas[0]: ", self.alphas[0].size()) | ||
| # print("self.thetas: ", self.thetas) |
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please remove prints that are commented
| @@ -84,6 +86,45 @@ def adding_problem_generator(N, seq_len=6, high=1, number_of_ones=2): | |||
| X = np.append(X_num, X_mask, axis=2) | |||
| return torch.FloatTensor(X), torch.FloatTensor(Y) | |||
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| def generate_copying_sequence(T, labels, c_length): | |||
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What is this used for in the adding problem?
| self.log_P.grad = (frechet_deriv - frechet_deriv.t()).triu(diagonal=1) | ||
| optimizer.step() | ||
| self.P.data = self._B(False) | ||
| self.P.grad.data.zero_() | ||
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| # def get_theta_list(self): | ||
| # return self.theta_list | ||
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Remove commented functions and test prints
| # print("y: ", y.size(), y[0], x[0]) | ||
| # print("onehot", args.onehot) | ||
| # print("x: ", x.size(), "y: ", y.size()) | ||
| # print("x batch size: ", x.shape[1]) |
| print(name, param.data) | ||
| # for name, param in net.named_parameters(): | ||
| # if param.requires_grad: | ||
| # print(name, param.data) |
| @@ -159,7 +161,7 @@ def forward(self, input,hidden): | |||
| # Load data | |||
| ############################################################################### | |||
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| corpus = Corpus('./data/pennchar/') | |||
| corpus = Corpus('//home/madhusudhan/ptb-data/') | |||
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Please remove references to your own file system
| @@ -305,9 +307,9 @@ def train(optimizer, orthog_optimizer): | |||
| try: | |||
| exp_time = "{0:%Y-%m-%d}_{0:%H-%M-%S}".format(datetime.now()) | |||
| SAVEDIR = os.path.join('./saves', | |||
| 'sMNIST', | |||
| 'language-task', | |||
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I think this is fixed in the newest master version. Merge master again.
| scipy==1.3.1 | ||
| torch==1.1.0 | ||
| numpy==1.16.4 | ||
| tensorboardX==1.9 |
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Implemented the adding problem and compared the results of nnRNN, RNN, LSTM and expRNN.