| #!/usr/bin/env python | |
| # coding: utf-8 | |
| # Copyright 2021 The HuggingFace Team. All rights reserved. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| # This script creates a tiny random model | |
| # | |
| # It will be used then as "hf-internal-testing/tiny-electra" | |
| # ***To build from scratch*** | |
| # | |
| # 1. clone sentencepiece into a parent dir | |
| # git clone https://github.com/google/sentencepiece | |
| # | |
| # 2. create a new repo at https://huggingface.co/new | |
| # make sure to choose 'hf-internal-testing' as the Owner | |
| # | |
| # 3. clone | |
| # git clone https://huggingface.co/hf-internal-testing/tiny-electra | |
| # cd tiny-electra | |
| # 4. start with some pre-existing script from one of the https://huggingface.co/hf-internal-testing/ tiny model repos, e.g. | |
| # wget https://huggingface.co/hf-internal-testing/tiny-electra/raw/main/make-xlm-roberta.py | |
| # chmod a+x ./make-tiny-electra.py | |
| # mv ./make-tiny-xlm-roberta.py ./make-tiny-electra.py | |
| # | |
| # 5. automatically rename things from the old names to new ones | |
| # perl -pi -e 's|XLMRoberta|Electra|g' make-tiny-electra.py | |
| # perl -pi -e 's|xlm-roberta|electra|g' make-tiny-electra.py | |
| # | |
| # 6. edit and re-run this script while fixing it up | |
| # ./make-tiny-electra.py | |
| # | |
| # 7. add/commit/push | |
| # git add * | |
| # git commit -m "new tiny model" | |
| # git push | |
| # ***To update*** | |
| # | |
| # 1. clone the existing repo | |
| # git clone https://huggingface.co/hf-internal-testing/tiny-electra | |
| # cd tiny-electra | |
| # | |
| # 2. edit and re-run this script after doing whatever changes are needed | |
| # ./make-tiny-electra.py | |
| # | |
| # 3. commit/push | |
| # git commit -m "new tiny model" | |
| # git push | |
| import sys | |
| import os | |
| from transformers import ElectraTokenizerFast, ElectraConfig, ElectraForMaskedLM | |
| mname_orig = "google/electra-small-generator" | |
| mname_tiny = "tiny-electra" | |
| ### Tokenizer | |
| # Shrink the orig vocab to keep things small (just enough to tokenize any word, so letters+symbols) | |
| # ElectraTokenizerFast is fully defined by a tokenizer.json, which contains the vocab and the ids, so we just need to truncate it wisely | |
| import subprocess | |
| tokenizer_fast = ElectraTokenizerFast.from_pretrained(mname_orig) | |
| vocab_keep_items = 5120 | |
| tmp_dir = f"/tmp/{mname_tiny}" | |
| tokenizer_fast.save_pretrained(tmp_dir) | |
| # resize tokenizer.json (vocab.txt will be automatically resized on save_pretrained) | |
| # perl -pi -e 's|(2999).*|$1}}}|' tokenizer.json # 0-indexed, so vocab_keep_items-1! | |
| closing_pat = "}}}" | |
| cmd = (f"perl -pi -e s|({vocab_keep_items-1}).*|$1{closing_pat}| {tmp_dir}/tokenizer.json").split() | |
| result = subprocess.run(cmd, capture_output=True, text=True) | |
| # reload with modified tokenizer | |
| tokenizer_fast_tiny = ElectraTokenizerFast.from_pretrained(tmp_dir) | |
| # it seems that ElectraTokenizer is not needed and ElectraTokenizerFast does the job | |
| ### Config | |
| config_tiny = ElectraConfig.from_pretrained(mname_orig) | |
| print(config_tiny) | |
| # remember to update this to the actual config as each model is different and then shrink the numbers | |
| config_tiny.update(dict( | |
| embedding_size=64, | |
| hidden_size=64, | |
| intermediate_size=64, | |
| max_position_embeddings=512, | |
| num_attention_heads=2, | |
| num_hidden_layers=2, | |
| vocab_size=vocab_keep_items, | |
| )) | |
| print("New config", config_tiny) | |
| ### Model | |
| model_tiny = ElectraForMaskedLM(config_tiny) | |
| print(f"{mname_tiny}: num of params {model_tiny.num_parameters()}") | |
| model_tiny.resize_token_embeddings(len(tokenizer_fast_tiny)) | |
| # Test | |
| inputs = tokenizer_fast_tiny("The capital of France is [MASK].", return_tensors="pt") | |
| outputs = model_tiny(**inputs) | |
| print("Test with normal tokenizer:", len(outputs.logits[0])) | |
| # Save | |
| model_tiny.half() # makes it smaller | |
| model_tiny.save_pretrained(".") | |
| tokenizer_fast_tiny.save_pretrained(".") | |
| #print(model_tiny) | |
| readme = "README.md" | |
| if not os.path.exists(readme): | |
| with open(readme, "w") as f: | |
| f.write(f"This is a {mname_tiny} random model to be used for basic testing.\n") | |
| print(f"Generated {mname_tiny}") | |