wizare

Thanks very much for your kind reply. Assume that my raw training corpus contains the following lines: ``i am a student i like to eat apple`` So I can obtain...

Thanks to your ``tokenizer.py``, I prepared my input file successfully. However, when I started training, the following problem appeared: OSError: /usr/local/lib/python3.6/site-packages/flyvec/src/model_descriptor.so: cannot open shared object file: No such file or...

I neglected to recognize this command. Then I run ``flyvec_compile``, and it throws several errors like that: ``cu_special_reduction.cu(249): error: initialization with "{...}" is not allowed for object of type "dim3"``...

[root@wizare/]# nvcc --version nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2018 NVIDIA Corporation Built on Sat_Aug_25_21:08:01_CDT_2018 Cuda compilation tools, release 10.0, V10.0.130

Okay, I'll have a try ~ And what's your g++ version?

In nmt/utils/Model.py, 230-238 rows: `ref_contexts, ref_mask = [], [] for template_input, template_length in zip(template_inputs, template_lengths): emb_ref = self.dec_embedding(template_input) ref_context, _ = self.encoder_ref(emb_ref, template_length) ref_mask_ = sequence_mask(template_length) ref_contexts.append(ref_context) ref_mask.append(ref_mask_) ref_contexts =...

I also meet the same issue. Can you tell me more about how to obtain the augmented sentences? Thanks.