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The implementation of the IJCAI 2018 paper: Code Completion with Neural Attention and Pointer Networks
Hi,
I am trying to reproduce the results reported in the paper, but I encounter some problems. Let me use vanillaLSTM.py
to illustrate. I test VanillaLSTM on JS_non_terminal.pickle
and JS_terminal_1k_whole.pickle
, and the following is the configuration according to the paper:
class TestConfig(object):
"""Tiny config, for testing."""
init_scale = 0.05
learning_rate = 0.001
max_grad_norm = 5
num_layers = 1
num_steps = 50
attn_size = 50
hidden_sizeN = 300
hidden_sizeT = 1200
sizeH = 1500
max_epoch = 8
max_max_epoch = 8
keep_prob = 1.0
lr_decay = 0.6
batch_size = 128
vocab_size = 95, 50001
However, the train accuracy and valid accuracy I obtain is around 0.48-0.49. If I test on the test set (uncomment lines 360-364), the test accuracy is 0.46. The paper reports a test accuracy of 0.699. Could you provide some instructions on how to reproduce the results?
Moreover, I find you have modified the batch_size
and num_steps
for test set in lines 343-344. What is the reason for that?
Thanks!
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