add the script
Browse files
fsmt-make-super-tiny-model.py
ADDED
@@ -0,0 +1,87 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
#!/usr/bin/env python
|
2 |
+
# coding: utf-8
|
3 |
+
# Copyright 2020 The HuggingFace Team. All rights reserved.
|
4 |
+
#
|
5 |
+
# Licensed under the Apache License, Version 2.0 (the "License");
|
6 |
+
# you may not use this file except in compliance with the License.
|
7 |
+
# You may obtain a copy of the License at
|
8 |
+
#
|
9 |
+
# http://www.apache.org/licenses/LICENSE-2.0
|
10 |
+
#
|
11 |
+
# Unless required by applicable law or agreed to in writing, software
|
12 |
+
# distributed under the License is distributed on an "AS IS" BASIS,
|
13 |
+
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
14 |
+
# See the License for the specific language governing permissions and
|
15 |
+
# limitations under the License.
|
16 |
+
|
17 |
+
# This script creates a super tiny model that is useful inside tests, when we just want to test that
|
18 |
+
# the machinery works, without needing to the check the quality of the outcomes.
|
19 |
+
#
|
20 |
+
# This version creates a tiny vocab first, and then a tiny model - so the outcome is truly tiny -
|
21 |
+
# all files ~60KB. As compared to taking a full-size model, reducing to the minimum its layers and
|
22 |
+
# emb dimensions, but keeping the full vocab + merges files, leading to ~3MB in total for all files.
|
23 |
+
# The latter is done by `fsmt-make-super-tiny-model.py`.
|
24 |
+
#
|
25 |
+
# It will be used then as "stas/tiny-wmt19-en-ru"
|
26 |
+
|
27 |
+
from pathlib import Path
|
28 |
+
import json
|
29 |
+
import tempfile
|
30 |
+
|
31 |
+
from transformers import FSMTTokenizer, FSMTConfig, FSMTForConditionalGeneration
|
32 |
+
from transformers.models.fsmt.tokenization_fsmt import VOCAB_FILES_NAMES
|
33 |
+
|
34 |
+
mname_tiny = "tiny-wmt19-en-ru"
|
35 |
+
|
36 |
+
# Build
|
37 |
+
|
38 |
+
# borrowed from a test
|
39 |
+
vocab = [ "l", "o", "w", "e", "r", "s", "t", "i", "d", "n", "w</w>", "r</w>", "t</w>", "lo", "low", "er</w>", "low</w>", "lowest</w>", "newer</w>", "wider</w>", "<unk>", ]
|
40 |
+
vocab_tokens = dict(zip(vocab, range(len(vocab))))
|
41 |
+
merges = ["l o 123", "lo w 1456", "e r</w> 1789", ""]
|
42 |
+
|
43 |
+
with tempfile.TemporaryDirectory() as tmpdirname:
|
44 |
+
build_dir = Path(tmpdirname)
|
45 |
+
src_vocab_file = build_dir / VOCAB_FILES_NAMES["src_vocab_file"]
|
46 |
+
tgt_vocab_file = build_dir / VOCAB_FILES_NAMES["tgt_vocab_file"]
|
47 |
+
merges_file = build_dir / VOCAB_FILES_NAMES["merges_file"]
|
48 |
+
with open(src_vocab_file, "w") as fp: fp.write(json.dumps(vocab_tokens))
|
49 |
+
with open(tgt_vocab_file, "w") as fp: fp.write(json.dumps(vocab_tokens))
|
50 |
+
with open(merges_file, "w") as fp : fp.write("\n".join(merges))
|
51 |
+
|
52 |
+
tokenizer = FSMTTokenizer(
|
53 |
+
langs=["en", "ru"],
|
54 |
+
src_vocab_size = len(vocab),
|
55 |
+
tgt_vocab_size = len(vocab),
|
56 |
+
src_vocab_file=src_vocab_file,
|
57 |
+
tgt_vocab_file=tgt_vocab_file,
|
58 |
+
merges_file=merges_file,
|
59 |
+
)
|
60 |
+
|
61 |
+
config = FSMTConfig(
|
62 |
+
langs=['ru', 'en'],
|
63 |
+
src_vocab_size=1000, tgt_vocab_size=1000,
|
64 |
+
d_model=4,
|
65 |
+
encoder_layers=1, decoder_layers=1,
|
66 |
+
encoder_ffn_dim=4, decoder_ffn_dim=4,
|
67 |
+
encoder_attention_heads=1, decoder_attention_heads=1,
|
68 |
+
)
|
69 |
+
|
70 |
+
tiny_model = FSMTForConditionalGeneration(config)
|
71 |
+
print(f"num of params {tiny_model.num_parameters()}")
|
72 |
+
|
73 |
+
# Test
|
74 |
+
batch = tokenizer(["Making tiny model"], return_tensors="pt")
|
75 |
+
outputs = tiny_model(**batch)
|
76 |
+
|
77 |
+
print("test output:", len(outputs.logits[0]))
|
78 |
+
|
79 |
+
# Save
|
80 |
+
tiny_model.half() # makes it smaller
|
81 |
+
tiny_model.save_pretrained(mname_tiny)
|
82 |
+
tokenizer.save_pretrained(mname_tiny)
|
83 |
+
|
84 |
+
print(f"Generated {mname_tiny}")
|
85 |
+
|
86 |
+
# Upload
|
87 |
+
# transformers-cli upload tiny-wmt19-en-ru
|