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| var sheetId = "Your_sheet_id"; | |
| var sheetName = "Forrm_tab_name"; | |
| var schema = { | |
| timeStamp: 0, | |
| title: 3, | |
| authors: 2, | |
| isRead: 1, | |
| sourceShort: 4, | |
| year: 5, |
himkt
/ optuna_demo.py
Created
July 22, 2020 06:00
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| from optuna.integration import AllenNLPExecutor | |
| import optuna | |
| def objective(trial: optuna.Trial) -> float: | |
| trial.suggest_float("embedding_dropout", 0.0, 0.5) | |
| executor = AllenNLPExecutor(trial, "./config.jsonnet", "result", include_package="allennlp_models") | |
| return executor.run() | |
himkt
/ config.jsonnet
Created
July 22, 2020 05:47
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| { | |
| "dataset_reader":{ | |
| "type": "sst_tokens", | |
| "use_subtrees": true, | |
| "granularity": "5-class" | |
| }, | |
| "validation_dataset_reader":{ | |
| "type": "sst_tokens", | |
| "use_subtrees": false, | |
| "granularity": "5-class" |
himkt
/ classifier.json
Created
July 18, 2020 21:31
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| { | |
| "dataset_reader": { | |
| "lazy": false, | |
| "token_indexers": { | |
| "tokens": { | |
| "lowercase_tokens": true, | |
| "type": "single_id" | |
| } | |
| }, | |
| "tokenizer": { |
himkt
/ poetry-log.bash
Created
July 16, 2020 10:01
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| Sending build context to Docker daemon 81.92kB | |
| Step 1/7 : FROM ubuntu:20.04 | |
| ---> adafef2e596e | |
| Step 2/7 : RUN apt update -y && apt install -y python3 python3-dev python3-venv python3-pip | |
| ---> Using cache | |
| ---> 5ed03d347c2e | |
| Step 3/7 : RUN pip3 install poetry | |
| ---> Using cache | |
| ---> ea3716a0aa47 |
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| # -*- coding: utf-8 -*- | |
| from setuptools import setup | |
| packages = \ | |
| ['konoha', | |
| 'konoha.api', | |
| 'konoha.data', | |
| 'konoha.integrations', | |
| 'konoha.word_tokenizers'] |
himkt
/ pyproject.toml
Created
July 16, 2020 09:56
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| [tool.poetry] | |
| name = "konoha" | |
| version = "4.4.0" | |
| description = "A tiny sentence/word tokenizer for Japanese text written in Python" | |
| authors = ["himkt <[email protected]>"] | |
| [tool.poetry.dependencies] | |
| python = "^3.6.1" | |
| janome = {version = "^0.3.10", optional = true} | |
| natto-py = {version = "^0.9.0", optional = true} |
himkt
/ gist:a9046c050ef1ac5081eda9888e3e4a57
Created
July 15, 2020 05:05
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| > python allennlp_simple.py (feature/allennlp-pruner| ● 3) | |
| 3000it [00:11, 255.15it/s] | |
| 3000it [00:01, 1724.34it/s] | |
| 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3000/3000 [00:00<00:00, 5099.38it/s] | |
| 400000it [00:02, 156772.51it/s] | |
| /home/ubuntu/work/github.com/himkt/optuna/optuna/_experimental.py:84: ExperimentalWarning |
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| // Use dev.jsonl for training to reduce computation time. | |
| // local TRAIN_PATH = 'https://s3-us-west-2.amazonaws.com/allennlp/datasets/imdb/dev.jsonl'; | |
| local VALIDATION_PATH = 'https://s3-us-west-2.amazonaws.com/allennlp/datasets/imdb/test.jsonl'; | |
| local DROPOUT = std.extVar('DROPOUT'); | |
| local EMBEDDING_DIM = std.extVar('EMBEDDING_DIM'); | |
| local CNN_FIELDS(max_filter_size, embedding_dim, hidden_size, num_filters) = { | |
| type: 'cnn', | |
| ngram_filter_sizes: std.range(1, max_filter_size), | |
| num_filters: num_filters, | |
| embedding_dim: embedding_dim, |
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| ============================= test session starts ============================== | |
| platform linux -- Python 3.7.7, pytest-5.4.3, py-1.8.2, pluggy-0.13.1 | |
| rootdir: /workspaces/optuna | |
| plugins: nbval-0.9.5 | |
| collected 10 items | |
| tests/integration_tests/test_fastai.py . [ 10%] | |
| tests/integration_tests/allennlp_tests/test_allennlp.py ....FFFF. [100%] | |
| =================================== FAILURES =================================== |
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