| id | label | text | doc_id | Scale | isStats | |
|---|---|---|---|---|---|---|
| PMC6738403_T1 | Operation | Identification of regional specific DAGs | PMC6738403 | Key | ||
| PMC6738403_T2 | Software | DESeq2 | PMC6738403 | |||
| PMC6738403_T3 | Data | raw read counts | PMC6738403 | |||
| PMC6738403_T4 | Data | regional specific DAGs | PMC6738403 | |||
| PMC6738403_T5 | Operation | filtering | PMC6738403 | |||
| PMC6738403_T6 | Data | genes with low read counts | PMC6738403 | |||
| PMC6738403_T7 | Software | DESeq2 | PMC6738403 | |||
| PMC6738403_T8 | Operation | identify | PMC6738403 | |||
| PMC6738403_T9 | Data | 3 surrogate variables | PMC6738403 |
| 2024-02-02 14:17:00.526334: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`. | |
| 2024-02-02 14:17:00.530107: I tensorflow/tsl/cuda/cudart_stub.cc:28] Could not find cuda drivers on your machine, GPU will not be used. | |
| 2024-02-02 14:17:00.593324: I tensorflow/tsl/cuda/cudart_stub.cc:28] Could not find cuda drivers on your machine, GPU will not be used. | |
| 2024-02-02 14:17:00.594029: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations. | |
| To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags. | |
| 2024-02-02 14:17:02.705549: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT | |
| Tr |
| import transformers | |
| def txt2subwords(text): | |
| "Convert the text to bert subwords" | |
| tok = 'dmis-lab/biobert-base-cased-v1.2' | |
| print("using tokenizer: ", tok) | |
| tokenizer = transformers.BertTokenizer.from_pretrained(tok) | |
| raw_tokens = tokenizer.tokenize(text) | |
| tokens = [token[2:] if token.startswith("##") else token for token in raw_tokens] | |
| # todo: how to handle [CLS] and [SEP] tokens and [UNK] tokens | |
| idx = 0 |
| @prefix ns1: <http://example.org/> . | |
| ns1:T11 a ns1:Version ; | |
| ns1:Name "3" ; | |
| ns1:Scale "" ; | |
| ns1:describes ns1:T10 . | |
| ns1:T12 a ns1:Library ; | |
| ns1:Name "matrix2png" ; | |
| ns1:Scale "" . |
| 1. Locate all research papers that use Tool X | |
| 2. Represent every data event (as mentioned) in the paper, thereby illustrating the relationships among data, operations, and operators. | |
| 3. Summarise the experimental workflow within an article, enabling us toanalyse the structure of an experimen |
| Id Type StartNode EndNode | |
| R1 describes T11 T10 | |
| R10 isAfter T13 T24 | |
| R11 isAfter T14 T13 | |
| R12 isAfter T15 T14 | |
| R13 isAfter T17 T15 | |
| R2 inputOf T16 T15 | |
| R3 outputOf T17 T18 | |
| R4 inputOf T22 T13 | |
| R5 inputOf T23 T13 |
| fddd@fddd-XPS-13-9380:~/.local/bin$ ./sapientacli ~/Documents/testpaper.pdf | |
| Traceback (most recent call last): | |
| File "/home/fddd/.local/bin/./sapientacli", line 8, in <module> | |
| sys.exit(main()) | |
| File "/home/fddd/.local/lib/python3.10/site-packages/click/core.py", line 829, in __call__ | |
| return self.main(*args, **kwargs) | |
| File "/home/fddd/.local/lib/python3.10/site-packages/click/core.py", line 782, in main | |
| rv = self.invoke(ctx) | |
| File "/home/fddd/.local/lib/python3.10/site-packages/click/core.py", line 1066, in invoke | |
| return ctx.invoke(self.callback, **ctx.params) |
I think my installation was correct. Although the crfsuite link didn't work, so I downloaded it from the official website.
fuqi@fuqi-XPS-13-9380:~/Software/SAPIENTA$ sudo python2 setup.py develop
running develop
running egg_info
writing SAPIENTA.egg-info/PKG-INFO
writing top-level names to SAPIENTA.egg-info/top_level.txt
writing dependency_links to SAPIENTA.egg-info/dependency_links.txt
| As phones, computers and other electronics have grown ever smaller, their optical components have stubbornly refused to shrink. Notably, it is hard to make tiny lenses with traditional glass-cutting and glass-curving techniques, and the elements in a glass lens often need to be stacked to focus light properly. Engineers have recently figured out much of the physics behind much smaller, lighter alternatives know as metalenses. The lenses could allow for greater miniaturization of microscopes and other laboratory tools, as well as of consumer products, such as cameras, virtual reality headsets and optical sensors for the Internet of Things. and they could enhance the functionality of optical fiber." |
| def bootstrap(invec): | |
| idx = npr.randint(0, len(invec), len(invec)) | |
| return [invec[i] for i in idx] | |
| def estimatePi0(p, numBoot=100, numLambda=100, maxLambda=0.95): | |
| p.sort() | |
| n=len(p) | |
| lambdas=np.linspace(maxLambda/numLambda,maxLambda,numLambda) | |
| Wls=np.array([n-np.argmax(p>=l) for l in lambdas]) | |
| pi0s=np.array([Wls[i] / (n * (1 - lambdas[i])) for i in range(numLambda)]) |