# Guideline to Convert Training Data CLUERNER2020 to MindRecord For Bert Fine Tuning
<!-- TOC -->
-[What does the example do](#what-does-the-example-do)
-[How to use the example to process CLUERNER2020](#how-to-use-the-example-to-process-cluerner2020)
-[Download CLUERNER2020 and unzip](#download-cluerner2020-and-unzip)
-[Generate MindRecord](#generate-mindrecord)
-[Create MindDataset By MindRecord](#create-minddataset-by-mindrecord)
<!-- /TOC -->
## What does the example do
This example is based on [CLUERNER2020](https://www.cluebenchmarks.com/introduce.html) training data, generating MindRecord file, and finally used for Bert Fine Tuning progress.
1. run.sh: generate MindRecord entry script
2. run_read.py: create MindDataset by MindRecord entry script.
- create_dataset.py: use MindDataset to read MindRecord to generate dataset.
## How to use the example to process CLUERNER2020
Download CLUERNER2020, convert it to MindRecord, use MindDataset to read MindRecord.
[INFO] ME(17603:139620983514944,MainProcess):2020-04-28-16:56:12.498.235 [mindspore/mindrecord/filewriter.py:313] The list of mindrecord files created are: ['data/train.mindrecord'], and the list of index files are: ['data/train.mindrecord.db']
...
[INFO] ME(17603,python):2020-04-28-16:56:13.400.175 [mindspore/ccsrc/mindrecord/io/shard_writer.cc:667] WriteRawData] Write 1 records successfully.
[INFO] ME(17603,python):2020-04-28-16:56:13.400.863 [mindspore/ccsrc/mindrecord/io/shard_writer.cc:667] WriteRawData] Write 1 records successfully.
[INFO] ME(17603,python):2020-04-28-16:56:13.401.534 [mindspore/ccsrc/mindrecord/io/shard_writer.cc:667] WriteRawData] Write 1 records successfully.
[INFO] ME(17603,python):2020-04-28-16:56:13.402.179 [mindspore/ccsrc/mindrecord/io/shard_writer.cc:667] WriteRawData] Write 1 records successfully.
[INFO] ME(17603,python):2020-04-28-16:56:13.402.702 [mindspore/ccsrc/mindrecord/io/shard_writer.cc:667] WriteRawData] Write 1 records successfully.
...
[INFO] ME(17603:139620983514944,MainProcess):2020-04-28-16:56:13.431.208 [mindspore/mindrecord/filewriter.py:313] The list of mindrecord files created are: ['data/dev.mindrecord'], and the list of index files are: ['data/dev.mindrecord.db']
# Guideline to Convert Training Data enwiki to MindRecord For Bert Pre Training
<!-- TOC -->
-[What does the example do](#what-does-the-example-do)
-[How to use the example to process enwiki](#how-to-use-the-example-to-process-enwiki)
-[Download enwiki training data](#download-enwiki-training-data)
-[Process the enwiki](#process-the-enwiki)
-[Generate MindRecord](#generate-mindrecord)
-[Create MindDataset By MindRecord](#create-minddataset-by-mindrecord)
<!-- /TOC -->
## What does the example do
This example is based on [enwiki](https://dumps.wikimedia.org/enwiki) training data, generating MindRecord file, and finally used for Bert network training.
1. run.sh: generate MindRecord entry script.
2. run_read.py: create MindDataset by MindRecord entry script.
- create_dataset.py: use MindDataset to read MindRecord to generate dataset.
## How to use the example to process enwiki
Download enwiki data, process it, convert it to MindRecord, use MindDataset to read MindRecord.
# Guideline to Convert Training Data zhwiki to MindRecord For Bert Pre Training
<!-- TOC -->
-[What does the example do](#what-does-the-example-do)
-[Run simple test](#run-simple-test)
-[How to use the example to process zhwiki](#how-to-use-the-example-to-process-zhwiki)
-[Download zhwiki training data](#download-zhwiki-training-data)
-[Extract the zhwiki](#extract-the-zhwiki)
-[Generate MindRecord](#generate-mindrecord)
-[Create MindDataset By MindRecord](#create-minddataset-by-mindrecord)
<!-- /TOC -->
## What does the example do
This example is based on [zhwiki](https://dumps.wikimedia.org/zhwiki) training data, generating MindRecord file, and finally used for Bert network training.
1. run.sh: generate MindRecord entry script.
2. run_read.py: create MindDataset by MindRecord entry script.
- create_dataset.py: use MindDataset to read MindRecord to generate dataset.
## Run simple test
Follow the step:
```bash
bash run_simple.sh # generate output/simple.mindrecord* by ../../../third_party/to_mindrecord/zhwiki/sample_text.txt
bash run_read_simple.sh # use MindDataset to read output/simple.mindrecord*
```
## How to use the example to process zhwiki
Download zhwiki data, extract it, convert it to MindRecord, use MindDataset to read MindRecord.
> Caution: This process maybe slow, please wait patiently. If you do not have a machine with enough memory and cpu, it is recommended that you modify the script to generate mindrecord in step by step.
2. The output like this:
```
patching file create_pretraining_data_patched.py (read from create_pretraining_data.py)
Begin preprocess input file: ./data/extract/AA/wiki_00
Begin output file: AAwiki_00.mindrecord
Total task: 5, processing: 1
Begin preprocess input file: ./data/extract/AA/wiki_01
Begin output file: AAwiki_01.mindrecord
Total task: 5, processing: 2
Begin preprocess input file: ./data/extract/AA/wiki_02
Begin output file: AAwiki_02.mindrecord
Total task: 5, processing: 3
Begin preprocess input file: ./data/extract/AB/wiki_02
## the file is a patch which is about just change data_processor_seq.py the part of generated tfrecord to MindRecord in [CLUEbenchmark/CLUENER2020](https://github.com/CLUEbenchmark/CLUENER2020/tree/master/tf_version)
## the file is a patch which is about just change create_pretraining_data.py the part of generated tfrecord to MindRecord in [google-research/bert](https://github.com/google-research/bert)
+ parser.add_argument("--partition_number", type=int, default=1, help='The MindRecord file will be split into the number of partition.')
+ parser.add_argument("--vocab_file", type=str, required=True, help='The vocabulary file than the BERT model was trained on.')
+ parser.add_argument("--do_lower_case", type=bool, default=False, help='Whether to lower case the input text. Should be True for uncased models and False for cased models.')
+ parser.add_argument("--do_whole_word_mask", type=bool, default=False, help='Whether to use whole word masking rather than per-WordPiece masking.')
+ parser.add_argument("--short_seq_prob", type=float, default=0.1, help='Probability of creating sequences which are shorter than the maximum length.')
This text is included to make sure Unicode is handled properly: 力加勝北区ᴵᴺᵀᵃছজটডণত
Text should be one-sentence-per-line, with empty lines between documents.
This sample text is public domain and was randomly selected from Project Guttenberg.
The rain had only ceased with the gray streaks of morning at Blazing Star, and the settlement awoke to a moral sense of cleanliness, and the finding of forgotten knives, tin cups, and smaller camp utensils, where the heavy showers had washed away the debris and dust heaps before the cabin doors.
Indeed, it was recorded in Blazing Star that a fortunate early riser had once picked up on the highway a solid chunk of gold quartz which the rain had freed from its incumbering soil, and washed into immediate and glittering popularity.
Possibly this may have been the reason why early risers in that locality, during the rainy season, adopted a thoughtful habit of body, and seldom lifted their eyes to the rifted or india-ink washed skies above them.
"Cass" Beard had risen early that morning, but not with a view to discovery.
A leak in his cabin roof,--quite consistent with his careless, improvident habits,--had roused him at 4 A. M., with a flooded "bunk" and wet blankets.
The chips from his wood pile refused to kindle a fire to dry his bed-clothes, and he had recourse to a more provident neighbor's to supply the deficiency.
This was nearly opposite.
Mr. Cassius crossed the highway, and stopped suddenly.
Something glittered in the nearest red pool before him.
Gold, surely!
But, wonderful to relate, not an irregular, shapeless fragment of crude ore, fresh from Nature's crucible, but a bit of jeweler's handicraft in the form of a plain gold ring.
Looking at it more attentively, he saw that it bore the inscription, "May to Cass."
Like most of his fellow gold-seekers, Cass was superstitious.
The fountain of classic wisdom, Hypatia herself.
As the ancient sage--the name is unimportant to a monk--pumped water nightly that he might study by day, so I, the guardian of cloaks and parasols, at the sacred doors of her lecture-room, imbibe celestial knowledge.
From my youth I felt in me a soul above the matter-entangled herd.
She revealed to me the glorious fact, that I am a spark of Divinity itself.
A fallen star, I am, sir!' continued he, pensively, stroking his lean stomach--'a fallen star!--fallen, if the dignity of philosophy will allow of the simile, among the hogs of the lower world--indeed, even into the hog-bucket itself. Well, after all, I will show you the way to the Archbishop's.
There is a philosophic pleasure in opening one's treasures to the modest young.
Perhaps you will assist me by carrying this basket of fruit?' And the little man jumped up, put his basket on Philammon's head, and trotted off up a neighbouring street.
Philammon followed, half contemptuous, half wondering at what this philosophy might be, which could feed the self-conceit of anything so abject as his ragged little apish guide;
but the novel roar and whirl of the street, the perpetual stream of busy faces, the line of curricles, palanquins, laden asses, camels, elephants, which met and passed him, and squeezed him up steps and into doorways, as they threaded their way through the great Moon-gate into the ample street beyond, drove everything from his mind but wondering curiosity, and a vague, helpless dread of that great living wilderness, more terrible than any dead wilderness of sand which he had left behind.
Already he longed for the repose, the silence of the Laura--for faces which knew him and smiled upon him; but it was too late to turn back now.
His guide held on for more than a mile up the great main street, crossed in the centre of the city, at right angles, by one equally magnificent, at each end of which, miles away, appeared, dim and distant over the heads of the living stream of passengers, the yellow sand-hills of the desert;
while at the end of the vista in front of them gleamed the blue harbour, through a network of countless masts.
At last they reached the quay at the opposite end of the street;
and there burst on Philammon's astonished eyes a vast semicircle of blue sea, ringed with palaces and towers.
He stopped involuntarily; and his little guide stopped also, and looked askance at the young monk, to watch the effect which that grand panorama should produce on him.
