amitmy / chimera Goto Github PK

While trying to run the server on Windows 10, an exception raises on the evaluation part, in the file eval\bleu\eval.py, line 69. I suppose this is because of the Linux command in cmd. How can I fix this issue so that it runs on my OS?

Hi Amit,

Happy to see this great paper with very nice results!

Could you let me know where to find the generated matching plans? It is mentioned in the paper but I cannot find it. It seems it's not easy to run the model on a single PC, so I am wondering if the plans can also be released. Thanks.

Hi,

We would appreciate if we can have a code to test the model on a different dataset where we can easily get a probable plan given the triples and generate a verbalization out of that.

Thanks in advance.

hi friend:
when I run pipeline, got error:

  File "../utils/pipeline.py", line 148, in execute
    x_params=x_params.union(params), previous_name=pn)
  File "../utils/pipeline.py", line 154, in execute
    params[qi.key] = qi.method(params, x_params)
  File "../process/reg.py", line 8, in <lambda>
    lambda _, x: x["config"].reg(x["pre-process"]["train"], x["pre-process"]["dev"]))
TypeError: 'NoneType' object is not callable

You need to add flask and flask_cors as dependencies in the requirements.txt

On the global direction expert of test-time plan selection, Here is a sentence:

"We capture this tendency using an expert that considers the conditional probability p(nr = n∣ ∣G∣) of observing
n reversed edges in an input with ∣G∣ triplets."

What are the meaning of nr and probability counted here?

And the plan selection is aimed to Text plan. not to sentence plan?

Hi Amit,

Thanks for your great work. I am wondering why your baseline results (Melbourne) in Table 1 are different from the scores mentioned in their paper [1]. Besides, there is a paper doing the same dataset, from University of Edinburgh [2]. Did you consider the comparison with them? Thanks

[1] Trisedya, Bayu Distiawan, et al. "GTR-LSTM: A Triple Encoder for Sentence Generation from RDF Data." ACL2018
[2] Diego Marcheggiani, Laura Perez-Beltrachini. Deep Graph Convolutional Encoders for Structured Data to Text Generation. INLG 2018

When I run the server/server.py script, some errors happen. How can I fix it?

File "/environment/python/versions/miniconda3-4.7.12/lib/python3.7/site-packages/urllib3/connectionpool.py", line 667, in urlopen
self._prepare_proxy(conn)
File "/environment/python/versions/miniconda3-4.7.12/lib/python3.7/site-packages/urllib3/connectionpool.py", line 932, in prepare_proxy
conn.connect()
File "/environment/python/versions/miniconda3-4.7.12/lib/python3.7/site-packages/urllib3/connection.py", line 371, in connect
ssl_context=context,
File "/environment/python/versions/miniconda3-4.7.12/lib/python3.7/site-packages/urllib3/util/ssl.py", line 386, in ssl_wrap_socket
return context.wrap_socket(sock, server_hostname=server_hostname)
File "/environment/python/versions/miniconda3-4.7.12/lib/python3.7/ssl.py", line 423, in wrap_socket
session=session
File "/environment/python/versions/miniconda3-4.7.12/lib/python3.7/ssl.py", line 870, in _create
self.do_handshake()
File "/environment/python/versions/miniconda3-4.7.12/lib/python3.7/ssl.py", line 1139, in do_handshake
self._sslobj.do_handshake()
ConnectionResetError: [Errno 104] Connection reset by peer

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "/environment/python/versions/miniconda3-4.7.12/lib/python3.7/site-packages/requests/adapters.py", line 449, in send
timeout=timeout
File "/environment/python/versions/miniconda3-4.7.12/lib/python3.7/site-packages/urllib3/connectionpool.py", line 727, in urlopen
method, url, error=e, _pool=self, _stacktrace=sys.exc_info()[2]
File "/environment/python/versions/miniconda3-4.7.12/lib/python3.7/site-packages/urllib3/util/retry.py", line 446, in increment
raise MaxRetryError(_pool, url, error or ResponseError(cause))
urllib3.exceptions.MaxRetryError: HTTPSConnectionPool(host='dbpedia.org', port=443): Max retries exceeded with url: /data/ACF_Fiorentina.json (Caused by ProxyError('Cannot connect to proxy.', ConnectionResetError(104, 'Connection reset by peer')))

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "server/server.py", line 95, in
res = MainPipeline.mutate({"config": main_config}).execute(dataset_name, cache_name=dataset_name)
File "/home/featurize/chimera/utils/pipeline.py", line 148, in execute
x_params=x_params.union(params), previous_name=pn)
File "/home/featurize/chimera/utils/pipeline.py", line 148, in execute
x_params=x_params.union(params), previous_name=pn)
File "/home/featurize/chimera/utils/pipeline.py", line 154, in execute
params[qi.key] = qi.method(params, x_params)
File "/home/featurize/chimera/process/pre_process.py", line 12, in
CorpusPreProcessPipeline.enqueue("entities", "Describe entities", lambda f, _: f["spelling"].copy().describe_entities())
File "/home/featurize/chimera/data/WebNLG/reader.py", line 187, in describe_entities
ps = pronouns(ent)
File "/home/featurize/chimera/utils/dbpedia.py", line 63, in pronouns
dbpedia = get_dbpedia_entity(entity)
File "/home/featurize/chimera/utils/dbpedia.py", line 35, in get_dbpedia_entity
r = requests.get(url=DBPEDIA + 'data/' + entity + '.json')
File "/environment/python/versions/miniconda3-4.7.12/lib/python3.7/site-packages/requests/api.py", line 76, in get
return request('get', url, params=params, **kwargs)
File "/environment/python/versions/miniconda3-4.7.12/lib/python3.7/site-packages/requests/api.py", line 61, in request
return session.request(method=method, url=url, **kwargs)
File "/environment/python/versions/miniconda3-4.7.12/lib/python3.7/site-packages/requests/sessions.py", line 530, in request
resp = self.send(prep, **send_kwargs)
File "/environment/python/versions/miniconda3-4.7.12/lib/python3.7/site-packages/requests/sessions.py", line 665, in send
history = [resp for resp in gen]
File "/environment/python/versions/miniconda3-4.7.12/lib/python3.7/site-packages/requests/sessions.py", line 665, in
history = [resp for resp in gen]
File "/environment/python/versions/miniconda3-4.7.12/lib/python3.7/site-packages/requests/sessions.py", line 245, in resolve_redirects
**adapter_kwargs
File "/environment/python/versions/miniconda3-4.7.12/lib/python3.7/site-packages/requests/sessions.py", line 643, in send
r = adapter.send(request, **kwargs)
File "/environment/python/versions/miniconda3-4.7.12/lib/python3.7/site-packages/requests/adapters.py", line 510, in send
raise ProxyError(e, request=request)
requests.exceptions.ProxyError: HTTPSConnectionPool(host='dbpedia.org', port=443): Max retries exceeded with url: /data/ACF_Fiorentina.json (Caused by ProxyError('Cannot connect to proxy.', ConnectionResetError(104, 'Connection reset by peer')))

Hi, thanks for sharing this work. I want to test the performance when beam_size=1, and I found some related information on this page. Could you introduce a bit more about the second part Greedy best neural plan?

• There are multiple results (e.g. 45.97, 43.76, 43.74...), I am confused about which number should represent the final result when beam_size is 1

• The number list below for Greedy (e.g. 45.97) seems even higher than when beam_size=10. Could you point me out there?

• I also want to confirm that is the result report on the paper (47.4) generate at beam_size=50?

Many thanks.

Hi Amit,

I started revising WebNLG to fix typos, and integrated the misspellings you found.
However, this should be "rector" and this should be something else, but not "runway".

Thanks!

I trained the model and now I want to start the server, but when I run server.py the model is starting to train again. How can I change this?

Hi Amit,

thanks again for this work.

I was reading again your paper and I'm wondering if the answers collected for the fluency evaluation, and for the plan realization consistency evaluation are available or can be made available.

Hi, thanks for sharing the code. I am confused about the size of the dataset as I get various number from the different sources.

• In paper[1], the author shows there are 18102/871/971 triple-text pairs for training/dev/test set
• In your repo, I find 1642 triple-text pairs for dev set from chimera/git-assets/enriched/dev.json
• From repo[2], I get 18102/2268/2495 for training/dev/test(seen) set.

All samples found in chimera/git-assets/enriched/dev.json could be found from dev set of repo[2]

Could you give me some information about the various size of the dev/test dataset? Moreover, could you also share the test set for reproducing?

[1] "Deep graph convolutional encoders for structured data to text generation."
[2] webnlg_corpus

Hi! I'm having trouble loading the data checkpoints.

The specific output and error are:

WebNLG
Pre-process training data
Training Set
corpus Read Corpus 0:00:00.000065
graphify RDF to Graph 0:00:00.000024
spelling Fix Spelling 0:00:00.000018
entities Describe entities 0:00:00.000025
match-ents Match Entities 0:00:00.000042
match-plans Match Plans 0:00:00.000020
tokenize Tokenize Plans & Sentences 0:00:00.000017
to-json Export in a readable format 0:00:00.000022
Dev Set
corpus Read Corpus 0:00:00.000042
graphify RDF to Graph 0:00:00.000019
spelling Fix Spelling 0:00:00.000019
entities Describe entities 0:00:00.000020
match-ents Match Entities 0:00:00.000020
match-plans Match Plans 0:00:00.000019
tokenize Tokenize Plans & Sentences 0:00:00.000018
to-json Export in a readable format 0:00:00.000016
Train Planner
planner Learn planner 0:00:00.000036
Train Model
model Initialize OpenNMT 0:00:00.000034
expose Expose Train Data 0:00:00.000017
pre-process Pre-process Train and Dev 0:00:00.000018
train Train model EXEC /home/ubuntu/miniconda3/envs/env_pytorch/bin/python /home/ubuntu/chimera/model/../libs/OpenNMT/train.py -train_steps 30000 -save_checkpoint_steps 1000 -batch_size 16 -word_vec_size 300 -feat_vec_size 10 -feat_merge concat -layers 3 -copy_attn -position_encoding -data /tmp/tmpz79gzk1g/data -save_model /tmp/tmpo6y8o6dz/ -world_size 1 -gpu_ranks 0

------------------------------------------------ (so the error happened here) -------------------------------------------------------

Traceback (most recent call last):
File "/home/ubuntu/chimera/model/../libs/OpenNMT/train.py", line 109, in
main(opt)
File "/home/ubuntu/chimera/model/../libs/OpenNMT/train.py", line 39, in main
single_main(opt, 0)
File "/home/ubuntu/chimera/libs/OpenNMT/onmt/train_single.py", line 63, in main
vocab = torch.load(opt.data + '.vocab.pt')
File "/home/ubuntu/miniconda3/envs/env_pytorch/lib/python3.6/site-packages/torch/serialization.py", line 367, in load
return _load(f, map_location, pickle_module)
File "/home/ubuntu/miniconda3/envs/env_pytorch/lib/python3.6/site-packages/torch/serialization.py", line 528, in _load
magic_number = pickle_module.load(f)
_pickle.UnpicklingError: A load persistent id instruction was encountered,
but no persistent_load function was specified.

--------------------------------------- (the error is above)-------------------------------------

Could you kindly provide some help? I would be very grateful!

Hi,

thanks for the paper Step-by-Step: Separating Planning from Realization in Neural Data-to-Text Generation and for sharing the code.

I'm using WebNLG benchmark in my masters and I'd like to compare the texts generated by various models, so I'd like to know if I can copy the texts generated by your models* to my repository, adding a README.md pointing to this repository.

* I'm assuming they are in /AmitMY/chimera/tree/master/data/WebNLG/compare, named BIU_random_0.txt, BIU_random_1.txt, BIU_random_2.txt and BIU_nmt.txt

Another thing, when trying to run the server I get this

in chimera/server on  master [?] pedro🅒 chimera took 16s
☃ ☞  /Users/pedro/anaconda3/envs/chimera/bin/python3 /Users/pedro/Documents/git/chimera/model/../libs/OpenNMT/preprocess.py -train_src /var/folders/ds/s277rjy10757gqy93wzbj2zh0000gn/T/tmpp5w4h0m2 -train_tgt /var/folders/ds/s277rjy10757gqy93wzbj2zh0000gn/T/tmpvjs4y0u8 -valid_src /var/folders/ds/s277rjy10757gqy93wzbj2zh0000gn/T/tmpi_xl8h5_ -valid_tgt /var/folders/ds/s277rjy10757gqy93wzbj2zh0000gn/T/tmpz76g5m_6 -save_data /var/folders/ds/s277rjy10757gqy93wzbj2zh0000gn/T/tmpfybw2hlu/data -dynamic_dict
Traceback (most recent call last):
  File "/Users/pedro/Documents/git/chimera/model/../libs/OpenNMT/preprocess.py", line 15, in <module>
    from onmt.utils.logging import init_logger, logger
  File "/Users/pedro/Documents/git/chimera/libs/OpenNMT/onmt/__init__.py", line 4, in <module>
    import onmt.inputters
  File "/Users/pedro/Documents/git/chimera/libs/OpenNMT/onmt/inputters/__init__.py", line 6, in <module>
    from onmt.inputters.inputter import make_features, collect_features, \
  File "/Users/pedro/Documents/git/chimera/libs/OpenNMT/onmt/inputters/inputter.py", line 19, in <module>
    from onmt.utils.logging import logger
  File "/Users/pedro/Documents/git/chimera/libs/OpenNMT/onmt/utils/__init__.py", line 4, in <module>
    from onmt.utils.statistics import Statistics
  File "/Users/pedro/Documents/git/chimera/libs/OpenNMT/onmt/utils/statistics.py", line 7, in <module>
    from torch.distributed import get_rank
ImportError: cannot import name 'get_rank' from 'torch.distributed' (/Users/pedro/anaconda3/envs/chimera/lib/python3.7/site-packages/torch/distributed/__init__.py)
(chimera)

This is on a new conda environment. I looked into it, and turns out there is a problem in OpenNMT:
[(https://github.com/OpenNMT/OpenNMT-py/issues/1129)]
(I think this may be only for mac that doesnt have cuda). The fix is to go into
libs/OpenNMT/ and do a git checkout 2a2621d770adb593942d7999a59401aff35d646a.

In this repo you can change the setup.sh to clone that specific commit or do a git checkout for that specific commit. It should not affect anything else.

Thanks!

When I run the script on the test data, it looks like slow and sometimes seems no change. Could you tell me how to solve this issue? Thank you!

Dear Amit,

Thanks for the great work! I am trying to replicate the StrongNeural baseline described in your paper, but I failed to find it in this repository. Is there any chance for the baseline code to be released as well? Or in case I missed it could you please point me to the correct file? Thanks!

P.S. I attempted to send you an email to the gmail address listed in the paper but the mail delivery service couldn't find it.

I am trying to install all dependencies on a new Conda environment using Python 3.6 (on Ubuntu).

However, during the installation I meet an error: error: command 'gcc' failed with exit status 1 right after trying to install Torchtext (Building wheel for torchtext (setup.py) ... error).

I am still a newbie so It might seem obvious to you, but I just can't find the solution after several days.

Here is the full details:

`

(base) strooper@MARK-I:/PycharmProjects/Chimera$ conda activate chimera_env

(chimera_env) strooper@MARK-I:/PycharmProjects/Chimera$ chmod +x setup.sh

(chimera_env) strooper@MARK-I:~/PycharmProjects/Chimera$ ./setup.sh

Collecting dyNET==2.1

Using cached dyNET-2.1-cp36-cp36m-manylinux1_x86_64.whl (28.1 MB)

Collecting numpy==1.16.0

Using cached numpy-1.16.0-cp36-cp36m-manylinux1_x86_64.whl (17.3 MB)

Collecting tqdm==4.29.1

Using cached tqdm-4.29.1-py2.py3-none-any.whl (46 kB)

Processing /home/strooper/.cache/pip/wheels/79/c3/a1/cbdd8b154234b3e571d121b65be7d53354cc77e223e8f271c8/python_Levenshtein-0.12.0-cp36-cp36m-linux_x86_64.whl

Collecting dateparser==0.7.0

Using cached dateparser-0.7.0-py2.py3-none-any.whl (357 kB)

Processing /home/strooper/.cache/pip/wheels/82/65/d5/eb94274f37176d3907fcf972069738a40e760c92049d59f07d/nltk-3.4-py3-none-any.whl

Collecting ordered_set==3.1

Using cached ordered_set-3.1-py2.py3-none-any.whl (7.8 kB)

Processing /home/strooper/.cache/pip/wheels/64/3c/58/505efc53d589c476a9c354ed9d8b077738e3b216af70b5a9f2/regex-2018.11.22-cp36-cp36m-linux_x86_64.whl

Collecting torch==1.0.0

Using cached torch-1.0.0-cp36-cp36m-manylinux1_x86_64.whl (591.8 MB)

Collecting typing==3.6.6

Using cached typing-3.6.6-py3-none-any.whl (25 kB)

Collecting xmltodict==0.11.0

Using cached xmltodict-0.11.0-py2.py3-none-any.whl (7.2 kB)

Collecting Flask_Cors==3.0.6

Using cached Flask_Cors-3.0.6-py2.py3-none-any.whl (13 kB)

Collecting Flask==1.0.2

Using cached Flask-1.0.2-py2.py3-none-any.whl (91 kB)

Collecting cython

Using cached Cython-0.29.21-cp36-cp36m-manylinux1_x86_64.whl (2.0 MB)

Requirement already satisfied: setuptools in /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages (from python_Levenshtein==0.12.0->-r requirements.txt (line 4)) (49.6.0.post20200814)

Collecting pytz

Using cached pytz-2020.1-py2.py3-none-any.whl (510 kB)

Collecting python-dateutil

Using cached python_dateutil-2.8.1-py2.py3-none-any.whl (227 kB)

Collecting tzlocal

Using cached tzlocal-2.1-py2.py3-none-any.whl (16 kB)

Collecting six

Using cached six-1.15.0-py2.py3-none-any.whl (10 kB)

Collecting singledispatch

Using cached singledispatch-3.4.0.3-py2.py3-none-any.whl (12 kB)

Collecting click>=5.1

Using cached click-7.1.2-py2.py3-none-any.whl (82 kB)

Collecting Werkzeug>=0.14

Using cached Werkzeug-1.0.1-py2.py3-none-any.whl (298 kB)

Collecting Jinja2>=2.10

Using cached Jinja2-2.11.2-py2.py3-none-any.whl (125 kB)

Collecting itsdangerous>=0.24

Using cached itsdangerous-1.1.0-py2.py3-none-any.whl (16 kB)

Collecting MarkupSafe>=0.23

Using cached MarkupSafe-1.1.1-cp36-cp36m-manylinux1_x86_64.whl (27 kB)

Installing collected packages: numpy, cython, dyNET, tqdm, python-Levenshtein, pytz, regex, six, python-dateutil, tzlocal, dateparser, singledispatch, nltk, ordered-set, torch, typing, xmltodict, click, Werkzeug, MarkupSafe, Jinja2, itsdangerous, Flask, Flask-Cors

Successfully installed Flask-1.0.2 Flask-Cors-3.0.6 Jinja2-2.11.2 MarkupSafe-1.1.1 Werkzeug-1.0.1 click-7.1.2 cython-0.29.21 dateparser-0.7.0 dyNET-2.1 itsdangerous-1.1.0 nltk-3.4 numpy-1.16.0 ordered-set-3.1 python-Levenshtein-0.12.0 python-dateutil-2.8.1 pytz-2020.1 regex-2018.11.22 singledispatch-3.4.0.3 six-1.15.0 torch-1.0.0 tqdm-4.29.1 typing-3.6.6 tzlocal-2.1 xmltodict-0.11.0

[nltk_data] Downloading package punkt to /home/strooper/nltk_data...

[nltk_data]   Package punkt is already up-to-date!

mkdir: cannot create directory ‘libs’: File exists

Cloning into 'OpenNMT'...

remote: Enumerating objects: 35, done.

remote: Counting objects: 100% (35/35), done.

remote: Compressing objects: 100% (30/30), done.

remote: Total 16245 (delta 13), reused 12 (delta 5), pack-reused 16210

Receiving objects: 100% (16245/16245), 146.92 MiB | 12.08 MiB/s, done.

Resolving deltas: 100% (11741/11741), done.

Note: switching to '518a19d4fbda6dd90f18a838a9a8986e1a0e6663'.

You are in 'detached HEAD' state. You can look around, make experimental

changes and commit them, and you can discard any commits you make in this

state without impacting any branches by switching back to a branch.
If you want to create a new branch to retain commits you create, you may

do so (now or later) by using -c with the switch command. Example:
git switch -c <new-branch-name>
Or undo this operation with:
git switch -
Turn off this advice by setting config variable advice.detachedHead to false
Collecting git+https://github.com/pytorch/text (from -r requirements.txt (line 4))

Cloning https://github.com/pytorch/text to /tmp/pip-req-build-j_01jlq3

Requirement already satisfied: six in /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages (from -r requirements.txt (line 1)) (1.15.0)

Collecting tqdm==4.30.*

Using cached tqdm-4.30.0-py2.py3-none-any.whl (47 kB)

Requirement already satisfied: torch>=1.0 in /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages (from -r requirements.txt (line 3)) (1.0.0)

Processing /home/strooper/.cache/pip/wheels/6e/9c/ed/4499c9865ac1002697793e0ae05ba6be33553d098f3347fb94/future-0.18.2-py3-none-any.whl

Processing /home/strooper/.cache/pip/wheels/ee/c1/ad/ab1d6fd3b6e32d4444fe79f88d8832689a0d3c3a74188051ea/ConfigArgParse-1.2.3-py3-none-any.whl

Collecting requests

Using cached requests-2.24.0-py2.py3-none-any.whl (61 kB)

Requirement already satisfied: numpy in /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages (from torchtext==0.8.0a0+db31b5d->-r requirements.txt (line 4)) (1.16.0)

Collecting sentencepiece

Using cached sentencepiece-0.1.91-cp36-cp36m-manylinux1_x86_64.whl (1.1 MB)

Collecting chardet<4,>=3.0.2

Using cached chardet-3.0.4-py2.py3-none-any.whl (133 kB)

Collecting urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1

Using cached urllib3-1.25.10-py2.py3-none-any.whl (127 kB)

Requirement already satisfied: certifi>=2017.4.17 in /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages (from requests->torchtext==0.8.0a0+db31b5d->-r requirements.txt (line 4)) (2020.6.20)

Collecting idna<3,>=2.5

Using cached idna-2.10-py2.py3-none-any.whl (58 kB)

Building wheels for collected packages: torchtext

Building wheel for torchtext (setup.py) ... error

  ERROR: Command errored out with exit status 1:

   command: /home/strooper/anaconda3/envs/chimera_env/bin/python -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'/tmp/pip-req-build-j_01jlq3/setup.py'"'"'; file='"'"'/tmp/pip-req-build-j_01jlq3/setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(file);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, file, '"'"'exec'"'"'))' bdist_wheel -d /tmp/pip-wheel-kbtbv6gh

       cwd: /tmp/pip-req-build-j_01jlq3/

  Complete output (559 lines):

  -- Building version 0.8.0a0+db31b5d

  running bdist_wheel

  running build

  running build_py

  creating build

  creating build/lib.linux-x86_64-3.6

  creating build/lib.linux-x86_64-3.6/torchtext

  copying torchtext/vocab.py -> build/lib.linux-x86_64-3.6/torchtext

  copying torchtext/init.py -> build/lib.linux-x86_64-3.6/torchtext

  copying torchtext/version.py -> build/lib.linux-x86_64-3.6/torchtext

  copying torchtext/utils.py -> build/lib.linux-x86_64-3.6/torchtext

  creating build/lib.linux-x86_64-3.6/torchtext/experimental

  copying torchtext/experimental/vocab.py -> build/lib.linux-x86_64-3.6/torchtext/experimental

  copying torchtext/experimental/functional.py -> build/lib.linux-x86_64-3.6/torchtext/experimental

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  copying torchtext/datasets/sequence_tagging.py -> build/lib.linux-x86_64-3.6/torchtext/datasets

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  running build_ext

  -- The CXX compiler identification is GNU 9.3.0

  -- Check for working CXX compiler: /usr/bin/c++

  -- Check for working CXX compiler: /usr/bin/c++ -- works

  -- Detecting CXX compiler ABI info

  -- Detecting CXX compiler ABI info - done

  -- Detecting CXX compile features

  -- Detecting CXX compile features - done

  -- The C compiler identification is GNU 9.3.0

  -- Check for working C compiler: /usr/bin/cc

  -- Check for working C compiler: /usr/bin/cc -- works

  -- Detecting C compiler ABI info

  -- Detecting C compiler ABI info - done

  -- Detecting C compile features

  -- Detecting C compile features - done

  -- Configuring done

  -- Generating done

  -- Build files have been written to: /tmp/pip-req-build-j_01jlq3/third_party/build

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  In file included from /tmp/pip-req-build-j_01jlq3/third_party/sentencepiece/src/unigram_model.h:24,

                   from /tmp/pip-req-build-j_01jlq3/third_party/sentencepiece/src/unigram_model.cc:15:

  /tmp/pip-req-build-j_01jlq3/third_party/sentencepiece/src/freelist.h: In instantiation of ‘T sentencepiece::model::FreeList<T>::Allocate() [with T = sentencepiece::unigram::Lattice::Node]’:

  /tmp/pip-req-build-j_01jlq3/third_party/sentencepiece/src/unigram_model.cc:83:41:   required from here

  /tmp/pip-req-build-j_01jlq3/third_party/sentencepiece/src/freelist.h:62:13: warning: ‘void memset(void, int, size_t)’ clearing an object of non-trivial type ‘struct sentencepiece::unigram::Lattice::Node’; use assignment or value-initialization instead [-Wclass-memaccess]

     62 |       memset(chunk, 0, sizeof(chunk) * chunk_size_);

        |       ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

  In file included from /tmp/pip-req-build-j_01jlq3/third_party/sentencepiece/src/unigram_model.cc:15:

  /tmp/pip-req-build-j_01jlq3/third_party/sentencepiece/src/unigram_model.h:38:10: note: ‘struct sentencepiece::unigram::Lattice::Node’ declared here

     38 |   struct Node {

        |          ^~~~

  In file included from /tmp/pip-req-build-j_01jlq3/third_party/sentencepiece/src/unigram_model.h:24,

                   from /tmp/pip-req-build-j_01jlq3/third_party/sentencepiece/src/unigram_model.cc:15:

  /tmp/pip-req-build-j_01jlq3/third_party/sentencepiece/src/freelist.h: In instantiation of ‘void sentencepiece::model::FreeList<T>::Free() [with T = sentencepiece::unigram::Lattice::Node]’:

  /tmp/pip-req-build-j_01jlq3/third_party/sentencepiece/src/unigram_model.cc:93:24:   required from here

  /tmp/pip-req-build-j_01jlq3/third_party/sentencepiece/src/freelist.h:39:13: warning: ‘void memset(void*, int, size_t)’ clearing an object of non-trivial type ‘struct sentencepiece::unigram::Lattice::Node’; use assignment or value-initialization instead [-Wclass-memaccess]

     39 |       memset(chunk, 0, sizeof(chunk) * chunk_size_);

        |       ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

  In file included from /tmp/pip-req-build-j_01jlq3/third_party/sentencepiece/src/unigram_model.cc:15:

  /tmp/pip-req-build-j_01jlq3/third_party/sentencepiece/src/unigram_model.h:38:10: note: ‘struct sentencepiece::unigram::Lattice::Node’ declared here

     38 |   struct Node {

        |          ^~~~

  [ 61%] Building CXX object src/CMakeFiles/sentencepiece-static.dir/util.cc.o

  [ 62%] Building CXX object src/CMakeFiles/sentencepiece-static.dir/word_model.cc.o

  [ 64%] Building CXX object src/CMakeFiles/sentencepiece-static.dir/__/third_party/absl/strings/string_view.cc.o

  [ 66%] Linking CXX static library libsentencepiece.a

  [ 66%] Built target sentencepiece-static

  Scanning dependencies of target sentencepiece_train-static

  [ 67%] Building CXX object src/CMakeFiles/sentencepiece_train-static.dir/builder.cc.o

  [ 69%] Building CXX object src/CMakeFiles/sentencepiece_train-static.dir/unicode_script.cc.o

  [ 71%] Building CXX object src/CMakeFiles/sentencepiece_train-static.dir/trainer_factory.cc.o

  [ 72%] Building CXX object src/CMakeFiles/sentencepiece_train-static.dir/trainer_interface.cc.o

  [ 74%] Building CXX object src/CMakeFiles/sentencepiece_train-static.dir/unigram_model_trainer.cc.o

  [ 76%] Building CXX object src/CMakeFiles/sentencepiece_train-static.dir/word_model_trainer.cc.o

  [ 77%] Building CXX object src/CMakeFiles/sentencepiece_train-static.dir/char_model_trainer.cc.o

  [ 79%] Building CXX object src/CMakeFiles/sentencepiece_train-static.dir/bpe_model_trainer.cc.o

  [ 81%] Building CXX object src/CMakeFiles/sentencepiece_train-static.dir/sentencepiece_trainer.cc.o

  [ 83%] Linking CXX static library libsentencepiece_train.a

  [ 83%] Built target sentencepiece_train-static

  Scanning dependencies of target spm_normalize

  [ 84%] Building CXX object src/CMakeFiles/spm_normalize.dir/spm_normalize_main.cc.o

  [ 86%] Linking CXX executable spm_normalize

  [ 86%] Built target spm_normalize

  Scanning dependencies of target spm_decode

  [ 88%] Building CXX object src/CMakeFiles/spm_decode.dir/spm_decode_main.cc.o

  [ 89%] Linking CXX executable spm_decode

  [ 89%] Built target spm_decode

  Scanning dependencies of target spm_encode

  [ 91%] Building CXX object src/CMakeFiles/spm_encode.dir/spm_encode_main.cc.o

  [ 93%] Linking CXX executable spm_encode

  [ 93%] Built target spm_encode

  Scanning dependencies of target spm_train

  [ 94%] Building CXX object src/CMakeFiles/spm_train.dir/spm_train_main.cc.o

  [ 96%] Linking CXX executable spm_train

  [ 96%] Built target spm_train

  Scanning dependencies of target spm_export_vocab

  [ 98%] Building CXX object src/CMakeFiles/spm_export_vocab.dir/spm_export_vocab_main.cc.o

  [100%] Linking CXX executable spm_export_vocab

  [100%] Built target spm_export_vocab

  Install the project...

  -- Install configuration: "Release"

  -- Installing: /tmp/pip-req-build-j_01jlq3/third_party/build/lib/pkgconfig/sentencepiece.pc

  -- Installing: /tmp/pip-req-build-j_01jlq3/third_party/build/lib/libsentencepiece.a

  -- Installing: /tmp/pip-req-build-j_01jlq3/third_party/build/lib/libsentencepiece_train.a

  -- Installing: /tmp/pip-req-build-j_01jlq3/third_party/build/bin/spm_encode

  -- Installing: /tmp/pip-req-build-j_01jlq3/third_party/build/bin/spm_decode

  -- Installing: /tmp/pip-req-build-j_01jlq3/third_party/build/bin/spm_normalize

  -- Installing: /tmp/pip-req-build-j_01jlq3/third_party/build/bin/spm_train

  -- Installing: /tmp/pip-req-build-j_01jlq3/third_party/build/bin/spm_export_vocab

  -- Installing: /tmp/pip-req-build-j_01jlq3/third_party/build/include/sentencepiece_trainer.h

  -- Installing: /tmp/pip-req-build-j_01jlq3/third_party/build/include/sentencepiece_processor.h

  building 'torchtext._torchtext' extension

  creating build/temp.linux-x86_64-3.6

  creating build/temp.linux-x86_64-3.6/tmp

  creating build/temp.linux-x86_64-3.6/tmp/pip-req-build-j_01jlq3

  creating build/temp.linux-x86_64-3.6/tmp/pip-req-build-j_01jlq3/torchtext

  creating build/temp.linux-x86_64-3.6/tmp/pip-req-build-j_01jlq3/torchtext/csrc

  gcc -pthread -B /home/strooper/anaconda3/envs/chimera_env/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -I/tmp/pip-req-build-j_01jlq3/torchtext/csrc -I/tmp/pip-req-build-j_01jlq3/third_party/build/include -I/home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include -I/home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/torch/csrc/api/include -I/home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/TH -I/home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/THC -I/home/strooper/anaconda3/envs/chimera_env/include/python3.6m -c /tmp/pip-req-build-j_01jlq3/torchtext/csrc/regex.cpp -o build/temp.linux-x86_64-3.6/tmp/pip-req-build-j_01jlq3/torchtext/csrc/regex.o -O3 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=_torchtext -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11

  cc1plus: warning: command line option ‘-Wstrict-prototypes’ is valid for C/ObjC but not for C++

  In file included from /tmp/pip-req-build-j_01jlq3/torchtext/csrc/regex.cpp:1:

  /tmp/pip-req-build-j_01jlq3/torchtext/csrc/regex.h:6:41: error: expected class-name before ‘{’ token

      6 | struct Regex : torch::CustomClassHolder {

        |                                         ^

  In file included from /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/core/ScalarType.h:3,

                   from /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/core/Scalar.h:10,

                   from /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/ATen/core/Type.h:8,

                   from /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/ATen/Type.h:2,

                   from /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/ATen/Context.h:4,

                   from /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/ATen/ATen.h:5,

                   from /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/torch/csrc/api/include/torch/types.h:3,

                   from /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/torch/script.h:3,

                   from /tmp/pip-req-build-j_01jlq3/torchtext/csrc/regex.h:3,

                   from /tmp/pip-req-build-j_01jlq3/torchtext/csrc/regex.cpp:1:

  /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/util/ArrayRef.h: In instantiation of ‘constexpr c10::ArrayRef<T>::ArrayRef(const std::initializer_list<_Tp>&) [with T = long int]’:

  /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/ATen/core/TensorImpl.h:1364:34:   required from here

  /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/util/ArrayRef.h:97:39: warning: initializing ‘c10::ArrayRef<long int>::Data’ from ‘std::initializer_list<long int>::begin’ does not extend the lifetime of the underlying array [-Winit-list-lifetime]

     97 |       : Data(Vec.begin() == Vec.end() ? static_cast<T>(nullptr) : Vec.begin()),

  /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/util/ArrayRef.h: In instantiation of ‘constexpr c10::ArrayRef<T>::ArrayRef(const std::initializer_list<_Tp>&) [with T = unsigned char]’:

  /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/ATen/NativeFunctions.h:64:1:   required from here

  /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/util/ArrayRef.h:97:39: warning: initializing ‘c10::ArrayRef<unsigned char>::Data’ from ‘std::initializer_list<unsigned char>::begin’ does not extend the lifetime of the underlying array [-Winit-list-lifetime]

  /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/util/ArrayRef.h: In instantiation of ‘constexpr c10::ArrayRef<T>::ArrayRef(const std::initializer_list<_Tp>&) [with T = signed char]’:

  /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/ATen/NativeFunctions.h:64:1:   required from here

  /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/util/ArrayRef.h:97:39: warning: initializing ‘c10::ArrayRef<signed char>::Data’ from ‘std::initializer_list<signed char>::begin’ does not extend the lifetime of the underlying array [-Winit-list-lifetime]

  /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/util/ArrayRef.h: In instantiation of ‘constexpr c10::ArrayRef<T>::ArrayRef(const std::initializer_list<_Tp>&) [with T = short int]’:

  /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/ATen/NativeFunctions.h:64:1:   required from here

  /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/util/ArrayRef.h:97:39: warning: initializing ‘c10::ArrayRef<short int>::Data’ from ‘std::initializer_list<short int>::begin’ does not extend the lifetime of the underlying array [-Winit-list-lifetime]

  /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/util/ArrayRef.h: In instantiation of ‘constexpr c10::ArrayRef<T>::ArrayRef(const std::initializer_list<_Tp>&) [with T = int]’:

  /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/ATen/NativeFunctions.h:64:1:   required from here

  /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/util/ArrayRef.h:97:39: warning: initializing ‘c10::ArrayRef<int>::Data’ from ‘std::initializer_list<int>::begin’ does not extend the lifetime of the underlying array [-Winit-list-lifetime]

  /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/util/ArrayRef.h: In instantiation of ‘constexpr c10::ArrayRef<T>::ArrayRef(const std::initializer_list<_Tp>&) [with T = float]’:

  /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/ATen/NativeFunctions.h:64:1:   required from here

  /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/util/ArrayRef.h:97:39: warning: initializing ‘c10::ArrayRef<float>::Data’ from ‘std::initializer_list<float>::begin’ does not extend the lifetime of the underlying array [-Winit-list-lifetime]

  /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/util/ArrayRef.h: In instantiation of ‘constexpr c10::ArrayRef<T>::ArrayRef(const std::initializer_list<_Tp>&) [with T = double]’:

  /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/ATen/NativeFunctions.h:64:1:   required from here

  /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/util/ArrayRef.h:97:39: warning: initializing ‘c10::ArrayRef<double>::Data’ from ‘std::initializer_list<double>::begin’ does not extend the lifetime of the underlying array [-Winit-list-lifetime]

  error: command 'gcc' failed with exit status 1

  ----------------------------------------

  ERROR: Failed building wheel for torchtext

Running setup.py clean for torchtext

Failed to build torchtext

DEPRECATION: Could not build wheels for torchtext which do not use PEP 517. pip will fall back to legacy 'setup.py install' for these. pip 21.0 will remove support for this functionality. A possible replacement is to fix the wheel build issue reported above. You can find discussion regarding this at pypa/pip#8368.

Installing collected packages: tqdm, future, configargparse, chardet, urllib3, idna, requests, sentencepiece, torchtext

Attempting uninstall: tqdm

Found existing installation: tqdm 4.29.1

Uninstalling tqdm-4.29.1:

Successfully uninstalled tqdm-4.29.1

Running setup.py install for torchtext ... error

    ERROR: Command errored out with exit status 1:

     command: /home/strooper/anaconda3/envs/chimera_env/bin/python -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'/tmp/pip-req-build-j_01jlq3/setup.py'"'"'; file='"'"'/tmp/pip-req-build-j_01jlq3/setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(file);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, file, '"'"'exec'"'"'))' install --record /tmp/pip-record-lu1zvlhq/install-record.txt --single-version-externally-managed --compile --install-headers /home/strooper/anaconda3/envs/chimera_env/include/python3.6m/torchtext

         cwd: /tmp/pip-req-build-j_01jlq3/

    Complete output (448 lines):

    -- Building version 0.8.0a0+db31b5d

    running install

    running build

    running build_py

    creating build

    creating build/lib.linux-x86_64-3.6

    creating build/lib.linux-x86_64-3.6/torchtext

    copying torchtext/vocab.py -> build/lib.linux-x86_64-3.6/torchtext

    copying torchtext/init.py -> build/lib.linux-x86_64-3.6/torchtext

    copying torchtext/version.py -> build/lib.linux-x86_64-3.6/torchtext

    copying torchtext/utils.py -> build/lib.linux-x86_64-3.6/torchtext

    creating build/lib.linux-x86_64-3.6/torchtext/experimental

    copying torchtext/experimental/vocab.py -> build/lib.linux-x86_64-3.6/torchtext/experimental

    copying torchtext/experimental/functional.py -> build/lib.linux-x86_64-3.6/torchtext/experimental

    copying torchtext/experimental/init.py -> build/lib.linux-x86_64-3.6/torchtext/experimental

    copying torchtext/experimental/vectors.py -> build/lib.linux-x86_64-3.6/torchtext/experimental

    copying torchtext/experimental/transforms.py -> build/lib.linux-x86_64-3.6/torchtext/experimental

    creating build/lib.linux-x86_64-3.6/torchtext/datasets

    copying torchtext/datasets/nli.py -> build/lib.linux-x86_64-3.6/torchtext/datasets

    copying torchtext/datasets/init.py -> build/lib.linux-x86_64-3.6/torchtext/datasets

    copying torchtext/datasets/sst.py -> build/lib.linux-x86_64-3.6/torchtext/datasets

    copying torchtext/datasets/text_classification.py -> build/lib.linux-x86_64-3.6/torchtext/datasets

    copying torchtext/datasets/sequence_tagging.py -> build/lib.linux-x86_64-3.6/torchtext/datasets

    copying torchtext/datasets/translation.py -> build/lib.linux-x86_64-3.6/torchtext/datasets

    copying torchtext/datasets/unsupervised_learning.py -> build/lib.linux-x86_64-3.6/torchtext/datasets

    copying torchtext/datasets/imdb.py -> build/lib.linux-x86_64-3.6/torchtext/datasets

    copying torchtext/datasets/trec.py -> build/lib.linux-x86_64-3.6/torchtext/datasets

    copying torchtext/datasets/language_modeling.py -> build/lib.linux-x86_64-3.6/torchtext/datasets

    copying torchtext/datasets/babi.py -> build/lib.linux-x86_64-3.6/torchtext/datasets

    creating build/lib.linux-x86_64-3.6/torchtext/data

    copying torchtext/data/functional.py -> build/lib.linux-x86_64-3.6/torchtext/data

    copying torchtext/data/metrics.py -> build/lib.linux-x86_64-3.6/torchtext/data

    copying torchtext/data/batch.py -> build/lib.linux-x86_64-3.6/torchtext/data

    copying torchtext/data/init.py -> build/lib.linux-x86_64-3.6/torchtext/data

    copying torchtext/data/dataset.py -> build/lib.linux-x86_64-3.6/torchtext/data

    copying torchtext/data/example.py -> build/lib.linux-x86_64-3.6/torchtext/data

    copying torchtext/data/field.py -> build/lib.linux-x86_64-3.6/torchtext/data

    copying torchtext/data/utils.py -> build/lib.linux-x86_64-3.6/torchtext/data

    copying torchtext/data/pipeline.py -> build/lib.linux-x86_64-3.6/torchtext/data

    copying torchtext/data/iterator.py -> build/lib.linux-x86_64-3.6/torchtext/data

    creating build/lib.linux-x86_64-3.6/torchtext/nn

    copying torchtext/nn/init.py -> build/lib.linux-x86_64-3.6/torchtext/nn

    creating build/lib.linux-x86_64-3.6/torchtext/experimental/datasets

    copying torchtext/experimental/datasets/init.py -> build/lib.linux-x86_64-3.6/torchtext/experimental/datasets

    copying torchtext/experimental/datasets/text_classification.py -> build/lib.linux-x86_64-3.6/torchtext/experimental/datasets

    copying torchtext/experimental/datasets/sequence_tagging.py -> build/lib.linux-x86_64-3.6/torchtext/experimental/datasets

    copying torchtext/experimental/datasets/translation.py -> build/lib.linux-x86_64-3.6/torchtext/experimental/datasets

    copying torchtext/experimental/datasets/question_answer.py -> build/lib.linux-x86_64-3.6/torchtext/experimental/datasets

    copying torchtext/experimental/datasets/language_modeling.py -> build/lib.linux-x86_64-3.6/torchtext/experimental/datasets

    creating build/lib.linux-x86_64-3.6/torchtext/experimental/datasets/raw

    copying torchtext/experimental/datasets/raw/init.py -> build/lib.linux-x86_64-3.6/torchtext/experimental/datasets/raw

    copying torchtext/experimental/datasets/raw/text_classification.py -> build/lib.linux-x86_64-3.6/torchtext/experimental/datasets/raw

    copying torchtext/experimental/datasets/raw/sequence_tagging.py -> build/lib.linux-x86_64-3.6/torchtext/experimental/datasets/raw

    copying torchtext/experimental/datasets/raw/translation.py -> build/lib.linux-x86_64-3.6/torchtext/experimental/datasets/raw

    copying torchtext/experimental/datasets/raw/question_answer.py -> build/lib.linux-x86_64-3.6/torchtext/experimental/datasets/raw

    copying torchtext/experimental/datasets/raw/language_modeling.py -> build/lib.linux-x86_64-3.6/torchtext/experimental/datasets/raw

    creating build/lib.linux-x86_64-3.6/torchtext/nn/modules

    copying torchtext/nn/modules/multiheadattention.py -> build/lib.linux-x86_64-3.6/torchtext/nn/modules

    copying torchtext/nn/modules/init.py -> build/lib.linux-x86_64-3.6/torchtext/nn/modules

    running build_ext

    -- The CXX compiler identification is GNU 9.3.0

    -- Check for working CXX compiler: /usr/bin/c++

    -- Check for working CXX compiler: /usr/bin/c++ -- works

    -- Detecting CXX compiler ABI info

    -- Detecting CXX compiler ABI info - done

    -- Detecting CXX compile features

    -- Detecting CXX compile features - done

    -- The C compiler identification is GNU 9.3.0

    -- Check for working C compiler: /usr/bin/cc

    -- Check for working C compiler: /usr/bin/cc -- works

    -- Detecting C compiler ABI info

    -- Detecting C compiler ABI info - done

    -- Detecting C compile features

    -- Detecting C compile features - done

    -- Configuring done

    -- Generating done

    -- Build files have been written to: /tmp/pip-req-build-j_01jlq3/third_party/build

    *** Command list Thirdparty **

    [

    {

      "directory": "/tmp/pip-req-build-j_01jlq3/third_party/build/re2",

      "command": "/usr/bin/c++   -I/tmp/pip-req-build-j_01jlq3/third_party/re2  -fPIC -D_GLIBCXX_USE_CXX11_ABI=0 -O3 -DNDEBUG   -pthread -std=gnu++11 -o CMakeFiles/re2.dir/re2/bitstate.cc.o -c /tmp/pip-req-build-j_01jlq3/third_party/re2/re2/bitstate.cc",

      "file": "/tmp/pip-req-build-j_01jlq3/third_party/re2/re2/bitstate.cc"

    },

    {

      "directory": "/tmp/pip-req-build-j_01jlq3/third_party/build/re2",

      "command": "/usr/bin/c++   -I/tmp/pip-req-build-j_01jlq3/third_party/re2  -fPIC -D_GLIBCXX_USE_CXX11_ABI=0 -O3 -DNDEBUG   -pthread -std=gnu++11 -o CMakeFiles/re2.dir/re2/compile.cc.o -c /tmp/pip-req-build-j_01jlq3/third_party/re2/re2/compile.cc",

      "file": "/tmp/pip-req-build-j_01jlq3/third_party/re2/re2/compile.cc"

    },

    {

      "directory": "/tmp/pip-req-build-j_01jlq3/third_party/build/re2",

      "command": "/usr/bin/c++   -I/tmp/pip-req-build-j_01jlq3/third_party/re2  -fPIC -D_GLIBCXX_USE_CXX11_ABI=0 -O3 -DNDEBUG   -pthread -std=gnu++11 -o CMakeFiles/re2.dir/re2/dfa.cc.o -c /tmp/pip-req-build-j_01jlq3/third_party/re2/re2/dfa.cc",

      "file": "/tmp/pip-req-build-j_01jlq3/third_party/re2/re2/dfa.cc"

    },

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    building 'torchtext._torchtext' extension

    creating build/temp.linux-x86_64-3.6

    creating build/temp.linux-x86_64-3.6/tmp

    creating build/temp.linux-x86_64-3.6/tmp/pip-req-build-j_01jlq3

    creating build/temp.linux-x86_64-3.6/tmp/pip-req-build-j_01jlq3/torchtext

    creating build/temp.linux-x86_64-3.6/tmp/pip-req-build-j_01jlq3/torchtext/csrc

    gcc -pthread -B /home/strooper/anaconda3/envs/chimera_env/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -I/tmp/pip-req-build-j_01jlq3/torchtext/csrc -I/tmp/pip-req-build-j_01jlq3/third_party/build/include -I/home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include -I/home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/torch/csrc/api/include -I/home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/TH -I/home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/THC -I/home/strooper/anaconda3/envs/chimera_env/include/python3.6m -c /tmp/pip-req-build-j_01jlq3/torchtext/csrc/regex.cpp -o build/temp.linux-x86_64-3.6/tmp/pip-req-build-j_01jlq3/torchtext/csrc/regex.o -O3 -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=_torchtext -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11

    cc1plus: warning: command line option ‘-Wstrict-prototypes’ is valid for C/ObjC but not for C++

    In file included from /tmp/pip-req-build-j_01jlq3/torchtext/csrc/regex.cpp:1:

    /tmp/pip-req-build-j_01jlq3/torchtext/csrc/regex.h:6:41: error: expected class-name before ‘{’ token

        6 | struct Regex : torch::CustomClassHolder {

          |                                         ^

    In file included from /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/core/ScalarType.h:3,

                     from /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/core/Scalar.h:10,

                     from /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/ATen/core/Type.h:8,

                     from /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/ATen/Type.h:2,

                     from /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/ATen/Context.h:4,

                     from /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/ATen/ATen.h:5,

                     from /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/torch/csrc/api/include/torch/types.h:3,

                     from /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/torch/script.h:3,

                     from /tmp/pip-req-build-j_01jlq3/torchtext/csrc/regex.h:3,

                     from /tmp/pip-req-build-j_01jlq3/torchtext/csrc/regex.cpp:1:

    /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/util/ArrayRef.h: In instantiation of ‘constexpr c10::ArrayRef<T>::ArrayRef(const std::initializer_list<_Tp>&) [with T = long int]’:

    /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/ATen/core/TensorImpl.h:1364:34:   required from here

    /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/util/ArrayRef.h:97:39: warning: initializing ‘c10::ArrayRef<long int>::Data’ from ‘std::initializer_list<long int>::begin’ does not extend the lifetime of the underlying array [-Winit-list-lifetime]

       97 |       : Data(Vec.begin() == Vec.end() ? static_cast<T>(nullptr) : Vec.begin()),

    /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/util/ArrayRef.h: In instantiation of ‘constexpr c10::ArrayRef<T>::ArrayRef(const std::initializer_list<_Tp>&) [with T = unsigned char]’:

    /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/ATen/NativeFunctions.h:64:1:   required from here

    /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/util/ArrayRef.h:97:39: warning: initializing ‘c10::ArrayRef<unsigned char>::Data’ from ‘std::initializer_list<unsigned char>::begin’ does not extend the lifetime of the underlying array [-Winit-list-lifetime]

    /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/util/ArrayRef.h: In instantiation of ‘constexpr c10::ArrayRef<T>::ArrayRef(const std::initializer_list<_Tp>&) [with T = signed char]’:

    /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/ATen/NativeFunctions.h:64:1:   required from here

    /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/util/ArrayRef.h:97:39: warning: initializing ‘c10::ArrayRef<signed char>::Data’ from ‘std::initializer_list<signed char>::begin’ does not extend the lifetime of the underlying array [-Winit-list-lifetime]

    /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/util/ArrayRef.h: In instantiation of ‘constexpr c10::ArrayRef<T>::ArrayRef(const std::initializer_list<_Tp>&) [with T = short int]’:

    /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/ATen/NativeFunctions.h:64:1:   required from here

    /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/util/ArrayRef.h:97:39: warning: initializing ‘c10::ArrayRef<short int>::Data’ from ‘std::initializer_list<short int>::begin’ does not extend the lifetime of the underlying array [-Winit-list-lifetime]

    /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/util/ArrayRef.h: In instantiation of ‘constexpr c10::ArrayRef<T>::ArrayRef(const std::initializer_list<_Tp>&) [with T = int]’:

    /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/ATen/NativeFunctions.h:64:1:   required from here

    /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/util/ArrayRef.h:97:39: warning: initializing ‘c10::ArrayRef<int>::Data’ from ‘std::initializer_list<int>::begin’ does not extend the lifetime of the underlying array [-Winit-list-lifetime]

    /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/util/ArrayRef.h: In instantiation of ‘constexpr c10::ArrayRef<T>::ArrayRef(const std::initializer_list<_Tp>&) [with T = float]’:

    /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/ATen/NativeFunctions.h:64:1:   required from here

    /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/util/ArrayRef.h:97:39: warning: initializing ‘c10::ArrayRef<float>::Data’ from ‘std::initializer_list<float>::begin’ does not extend the lifetime of the underlying array [-Winit-list-lifetime]

    /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/util/ArrayRef.h: In instantiation of ‘constexpr c10::ArrayRef<T>::ArrayRef(const std::initializer_list<_Tp>&) [with T = double]’:

    /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/ATen/NativeFunctions.h:64:1:   required from here

    /home/strooper/anaconda3/envs/chimera_env/lib/python3.6/site-packages/torch/lib/include/c10/util/ArrayRef.h:97:39: warning: initializing ‘c10::ArrayRef<double>::Data’ from ‘std::initializer_list<double>::begin’ does not extend the lifetime of the underlying array [-Winit-list-lifetime]

    error: command 'gcc' failed with exit status 1

    ----------------------------------------

ERROR: Command errored out with exit status 1: /home/strooper/anaconda3/envs/chimera_env/bin/python -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'/tmp/pip-req-build-j_01jlq3/setup.py'"'"'; file='"'"'/tmp/pip-req-build-j_01jlq3/setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(file);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, file, '"'"'exec'"'"'))' install --record /tmp/pip-record-lu1zvlhq/install-record.txt --single-version-externally-managed --compile --install-headers /home/strooper/anaconda3/envs/chimera_env/include/python3.6m/torchtext Check the logs for full command output.

Hi there,

I have been trying to run this for the past couple of weeks, and it seems one needs a beefy computer to run through the process. In the reader.py code, where the multiprocessing is used, at some point in the planning, I believe the system goes either into a very deep recursion, or it explores too many branches, and eventually, the system runs out of memory. I've tried this on a machine with 64gb of ram and it eats that up too. The problem occurs around iteration 890 in the create_plans method of the DataReader class. I'm going to try and debug this to see if I can limit depth or size or run time as lack of a feasible plan. A small memory optimization is to replace Pool with ThreadPool.

This error comes up trying to run the system:
`**********************************************************************
Resource punkt not found.
Please use the NLTK Downloader to obtain the resource:

import nltk
nltk.download('punkt')

Attempted to load tokenizers/punkt/PY3/english.pickle

Searched in:
- '/home/pedro/nltk_data'
- '/home/pedro/anaconda3/nltk_data'
- '/home/pedro/anaconda3/share/nltk_data'
- '/home/pedro/anaconda3/lib/nltk_data'
- '/usr/share/nltk_data'
- '/usr/local/share/nltk_data'
- '/usr/lib/nltk_data'
- '/usr/local/lib/nltk_data'
- ''
**********************************************************************`

Its a simple fix, just add in some python file or on a python command line:

import nltk
nltk.download('punkt')

File "/content/chimera/utils/dbpedia.py", line 36, in get_dbpedia_entity r.raise_for_status() # raises exception when not a 2xx response File "/usr/local/lib/python3.7/dist-packages/requests/models.py", line 941, in raise_for_status raise HTTPError(http_error_msg, response=self) requests.exceptions.HTTPError: 500 Server Error: SPARQL Request Failed for url: https://dbpedia.org/data/Drogheda_United_F.C..json

It looks like DBPEDIA does not give the proper response for some reason. How can I fix this?