Error when using --summarize with matcher.py about ditto HOT 1 OPEN

I have encountered similar issue.

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Some weights of the model checkpoint at distilbert-base-uncased were not used when initializing DistilBertModel: ['vocab_layer_norm.weight', 'vocab_transform.bias', 'vocab_projector.bias', 'vocab_layer_norm.bias', 'vocab_projector.weight', 'vocab_transform.weight']

• This IS expected if you are initializing DistilBertModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
• This IS NOT expected if you are initializing DistilBertModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
  Selected optimization level O2: FP16 training with FP32 batchnorm and FP32 master weights.

Defaults for this optimization level are:
enabled : True
opt_level : O2
cast_model_type : torch.float16
patch_torch_functions : False
keep_batchnorm_fp32 : True
master_weights : True
loss_scale : dynamic
Processing user overrides (additional kwargs that are not None)...
After processing overrides, optimization options are:
enabled : True
opt_level : O2
cast_model_type : torch.float16
patch_torch_functions : False
keep_batchnorm_fp32 : True
master_weights : True
loss_scale : dynamic
Warning: multi_tensor_applier fused unscale kernel is unavailable, possibly because apex was installed without --cuda_ext --cpp_ext. Using Python fallback. Original ImportError was: ModuleNotFoundError("No module named 'amp_C'",)
/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/apex/amp/_initialize.py:25: UserWarning: An input tensor was not cuda.
warnings.warn("An input tensor was not cuda.")
Gradient overflow. Skipping step, loss scaler 0 reducing loss scale to 32768.0
/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/torch/optim/lr_scheduler.py:134: UserWarning: Detected call of lr_scheduler.step() before optimizer.step(). In PyTorch 1.1.0 and later, you should call them in the opposite order: optimizer.step() before lr_scheduler.step(). Failure to do this will result in PyTorch skipping the first value of the learning rate schedule. See more details at https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate
"https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate", UserWarning)
step: 0, loss: 0.7943093180656433
Traceback (most recent call last):
File "train_ditto.py", line 92, in
run_tag, hp)
File "/home/ec2-user/SageMaker/vendor_matching/ditto/ditto_light/ditto.py", line 201, in train
train_step(train_iter, model, optimizer, scheduler, hp)
File "/home/ec2-user/SageMaker/vendor_matching/ditto/ditto_light/ditto.py", line 123, in train_step
for i, batch in enumerate(train_iter):
File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 521, in next
data = self._next_data()
File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 561, in _next_data
data = self._dataset_fetcher.fetch(index) # may raise StopIteration
File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/torch/utils/data/_utils/fetch.py", line 49, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/torch/utils/data/_utils/fetch.py", line 49, in
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/ec2-user/SageMaker/vendor_matching/ditto/ditto_light/dataset.py", line 80, in getitem
left, right = combined.split(' [SEP] ')
ValueError: not enough values to unpack (expected 2, got 1)
Traceback (most recent call last):
File "matcher.py", line 7, in
import jsonlines
ModuleNotFoundError: No module named 'jsonlines'
`

from ditto.