From e801ea4c7d0fef5a7ca089a2f7c622b3399d9ffd Mon Sep 17 00:00:00 2001
From: Mickus Timothee <mickus@lx7-humtdk75.hum.helsinki.fi>
Date: Thu, 21 Sep 2023 11:38:30 +0300
Subject: [PATCH] more generic transform name

---
 docs/source/config_config.md              | 4 ++--
 examples/config_config.yaml               | 6 +++---
 onmt/tests/test_subword_marker.py         | 2 +-
 onmt/tests/test_transform.py              | 2 +-
 onmt/transforms/{bart.py => denoising.py} | 0
 onmt/utils/parse.py                       | 2 +-
 6 files changed, 8 insertions(+), 8 deletions(-)
 rename onmt/transforms/{bart.py => denoising.py} (100%)

diff --git a/docs/source/config_config.md b/docs/source/config_config.md
index 650439de..356df0dd 100644
--- a/docs/source/config_config.md
+++ b/docs/source/config_config.md
@@ -34,7 +34,7 @@ The meta-parameters under the `config_config` key:
 Path templates for source and target corpora, respectively.
 The path templates can contain the following variables that will be substituted by `config_config`:
 
-- Directional corpus mode 
+- Directional corpus mode
   - `{src_lang}`: The source language of the task
   - `{tgt_lang}`: The target language of the task
   - `{lang_pair}`: `{src_lang}-{tgt_lang}` for convenience
@@ -99,7 +99,7 @@ Generate translation configs for zero-shot directions.
 #### `transforms` and `ae_transforms`
 
 A list of transforms, for translation tasks and autoencoder tasks, respectively.
-Use this to apply subword segmentation, e.g. using `sentencepiece`, and `bart` noise for autoencoder.
+Use this to apply subword segmentation, e.g. using `sentencepiece`, and `ae_noise` noise for autoencoder.
 Both of these may change the sequence length, necessitating a `filtertoolong` transform.
 
 #### `enc_sharing_groups` and `dec_sharing_groups`
diff --git a/examples/config_config.yaml b/examples/config_config.yaml
index 47fe8ca0..c66dc3e4 100644
--- a/examples/config_config.yaml
+++ b/examples/config_config.yaml
@@ -16,7 +16,7 @@ config_config:
   ae_transforms:
     - sentencepiece
     - filtertoolong
-    - bart
+    - ae_noise
   enc_sharing_groups:
     - GROUP
     - FULL
@@ -27,7 +27,7 @@ config_config:
   translation_config_dir: config/translation.opus
   n_gpus_per_node: 4
   n_nodes: 2
-  
+
   # Note that this specifies the groups manually instead of clustering
   groups:
     "en": "en"
@@ -43,7 +43,7 @@ config_config:
 
 save_data: generated/opus.spm32k
 # vocabs serve two purposes: defines the vocab files, and gives the potential languages to consider
-src_vocab: 
+src_vocab:
   "af": "/scratch/project_2005099/data/opus/prepare_opus_data_tc_out/opusTC.afr.32k.spm.vocab"
   "da": "/scratch/project_2005099/data/opus/prepare_opus_data_tc_out/opusTC.dan.32k.spm.vocab"
   "en": "/scratch/project_2005099/data/opus/prepare_opus_data_tc_out/opusTC.eng.32k.spm.vocab"
diff --git a/onmt/tests/test_subword_marker.py b/onmt/tests/test_subword_marker.py
index 8987cbc0..afa17fcf 100644
--- a/onmt/tests/test_subword_marker.py
+++ b/onmt/tests/test_subword_marker.py
@@ -1,6 +1,6 @@
 import unittest
 
-from onmt.transforms.bart import word_start_finder
+from onmt.transforms.denoising import word_start_finder
 from onmt.utils.alignment import subword_map_by_joiner, subword_map_by_spacer
 from onmt.constants import SubwordMarker
 
diff --git a/onmt/tests/test_transform.py b/onmt/tests/test_transform.py
index 0cffb0c8..7d6b58f0 100644
--- a/onmt/tests/test_transform.py
+++ b/onmt/tests/test_transform.py
@@ -11,7 +11,7 @@
     make_transforms,
     TransformPipe,
 )
-from onmt.transforms.bart import BARTNoising
+from onmt.transforms.denoising import BARTNoising
 
 
 class TestTransform(unittest.TestCase):
diff --git a/onmt/transforms/bart.py b/onmt/transforms/denoising.py
similarity index 100%
rename from onmt/transforms/bart.py
rename to onmt/transforms/denoising.py
diff --git a/onmt/utils/parse.py b/onmt/utils/parse.py
index a0b4ae1d..b29729a1 100644
--- a/onmt/utils/parse.py
+++ b/onmt/utils/parse.py
@@ -168,7 +168,7 @@ def _get_all_transform(cls, opt):
         if hasattr(opt, 'lambda_align') and opt.lambda_align > 0.0:
             if not all_transforms.isdisjoint({'sentencepiece', 'bpe', 'onmt_tokenize'}):
                 raise ValueError('lambda_align is not compatible with on-the-fly tokenization.')
-            if not all_transforms.isdisjoint({'tokendrop', 'prefix', 'bart'}):
+            if not all_transforms.isdisjoint({'tokendrop', 'prefix', 'ae_noise'}):
                 raise ValueError('lambda_align is not compatible yet with potential token deletion/addition.')
         opt._all_transform = all_transforms