From 2c63c01cabfb8df3c2da0dcb4713256f5e09b2d4 Mon Sep 17 00:00:00 2001
From: Yoann Schneider <yschneider@teklia.com>
Date: Tue, 8 Aug 2023 13:49:58 +0000
Subject: [PATCH] Remove post processing as it's not used
---
dan/manager/metrics.py | 26 +++++-----
dan/manager/training.py | 13 +++--
dan/ocr/document/train.py | 1 +
dan/post_processing.py | 93 ----------------------------------
dan/utils.py | 3 --
docs/ref/post_processing.md | 3 --
docs/usage/train/parameters.md | 21 ++++----
mkdocs.yml | 1 -
tests/conftest.py | 1 +
9 files changed, 35 insertions(+), 127 deletions(-)
delete mode 100644 dan/post_processing.py
delete mode 100644 docs/ref/post_processing.md
diff --git a/dan/manager/metrics.py b/dan/manager/metrics.py
index 0b2472d9..015c0234 100644
--- a/dan/manager/metrics.py
+++ b/dan/manager/metrics.py
@@ -1,28 +1,26 @@
# -*- coding: utf-8 -*-
import re
+from operator import attrgetter
+from pathlib import Path
+from typing import Optional
import editdistance
import numpy as np
-from dan.post_processing import PostProcessingModuleSIMARA
-from dan.utils import SEM_MATCHING_TOKENS as SIMARA_MATCHING_TOKENS
+from dan.datasets.extract.utils import parse_tokens
class MetricManager:
- def __init__(self, metric_names, dataset_name):
+ def __init__(self, metric_names, dataset_name, tokens: Optional[Path]):
self.dataset_name = dataset_name
- if "simara" in dataset_name and "page" in dataset_name:
- self.post_processing_module = PostProcessingModuleSIMARA
- self.matching_tokens = SIMARA_MATCHING_TOKENS
- else:
- self.matching_tokens = dict()
-
- self.layout_tokens = "".join(
- list(self.matching_tokens.keys()) + list(self.matching_tokens.values())
- )
- if len(self.layout_tokens) == 0:
- self.layout_tokens = None
+ self.layout_tokens = None
+ if tokens:
+ tokens = parse_tokens(tokens)
+ self.layout_tokens = "".join(
+ list(map(attrgetter("start"), tokens.values()))
+ + list(map(attrgetter("end"), tokens.values()))
+ )
self.metric_names = metric_names
self.epoch_metrics = None
diff --git a/dan/manager/training.py b/dan/manager/training.py
index 8f4de234..735b7100 100644
--- a/dan/manager/training.py
+++ b/dan/manager/training.py
@@ -60,6 +60,7 @@ class GenericTrainingManager:
if self.params["training_params"]["use_ddp"]
else 1
)
+ self.tokens = self.params["dataset_params"].get("tokens")
def init_paths(self):
"""
@@ -617,7 +618,9 @@ class GenericTrainingManager:
] = self.latest_epoch
# init epoch metrics values
self.metric_manager["train"] = MetricManager(
- metric_names=metric_names, dataset_name=self.dataset_name
+ metric_names=metric_names,
+ dataset_name=self.dataset_name,
+ tokens=self.tokens,
)
with tqdm(total=len(self.dataset.train_loader.dataset)) as pbar:
pbar.set_description("EPOCH {}/{}".format(num_epoch, nb_epochs))
@@ -738,7 +741,9 @@ class GenericTrainingManager:
# initialize epoch metrics
self.metric_manager[set_name] = MetricManager(
- metric_names, dataset_name=self.dataset_name
+ metric_names=metric_names,
+ dataset_name=self.dataset_name,
+ tokens=self.tokens,
)
with tqdm(total=len(loader.dataset)) as pbar:
pbar.set_description("Evaluation E{}".format(self.latest_epoch))
@@ -787,7 +792,9 @@ class GenericTrainingManager:
# initialize epoch metrics
self.metric_manager[custom_name] = MetricManager(
- metric_names, self.dataset_name
+ metric_names=metric_names,
+ dataset_name=self.dataset_name,
+ tokens=self.tokens,
)
with tqdm(total=len(loader.dataset)) as pbar:
diff --git a/dan/ocr/document/train.py b/dan/ocr/document/train.py
index b6146a94..712c8a34 100644
--- a/dan/ocr/document/train.py
+++ b/dan/ocr/document/train.py
@@ -114,6 +114,7 @@ def get_config():
],
"augmentation": True,
},
+ "tokens": None,
},
"model_params": {
"models": {
diff --git a/dan/post_processing.py b/dan/post_processing.py
deleted file mode 100644
index 180d021f..00000000
--- a/dan/post_processing.py
+++ /dev/null
@@ -1,93 +0,0 @@
-# -*- coding: utf-8 -*-
-import numpy as np
-
-from dan.utils import SEM_MATCHING_TOKENS as SIMARA_MATCHING_TOKENS
-
-
-class PostProcessingModule:
- """
- Forward pass post processing
- Add/remove layout tokens only to:
- - respect token hierarchy
- - complete/remove unpaired tokens
- """
-
- def __init__(self):
- self.prediction = None
- self.confidence = None
-
- def post_processing(self):
- raise NotImplementedError
-
- def post_process(self, prediction, confidence_score=None):
- """
- Apply dataset-specific post-processing
- """
- self.prediction = list(prediction)
- self.confidence = (
- list(confidence_score) if confidence_score is not None else None
- )
- if self.confidence is not None:
- assert len(self.prediction) == len(self.confidence)
- return self.post_processing()
-
- def insert_label(self, index, label):
- """
- Insert token at specific index. The associated confidence score is set to 0.
- """
- self.prediction.insert(index, label)
- if self.confidence is not None:
- self.confidence.insert(index, 0)
-
- def del_label(self, index):
- """
- Remove the token at a specific index.
- """
- del self.prediction[index]
- if self.confidence is not None:
- del self.confidence[index]
-
-
-class PostProcessingModuleSIMARA(PostProcessingModule):
- """
- Specific post-processing for the SIMARA dataset at page level
- """
-
- def __init__(self):
- super(PostProcessingModuleSIMARA, self).__init__()
- self.matching_tokens = SIMARA_MATCHING_TOKENS
- self.reverse_matching_tokens = dict()
- for key in self.matching_tokens:
- self.reverse_matching_tokens[self.matching_tokens[key]] = key
-
- def post_processing(self):
- ind = 0
- begin_token = None
- while ind != len(self.prediction):
- char = self.prediction[ind]
- # a tag must be closed before starting a new one
- if char in self.matching_tokens.keys():
- if begin_token is None:
- ind += 1
- else:
- self.insert_label(ind, self.matching_tokens[begin_token])
- ind += 2
- begin_token = char
- continue
- # an end token without prior corresponding begin token is removed
- elif char in self.matching_tokens.values():
- if begin_token == self.reverse_matching_tokens[char]:
- ind += 1
- begin_token = None
- else:
- self.del_label(ind)
- continue
- else:
- ind += 1
- # a tag must be closed
- if begin_token is not None:
- self.insert_label(ind + 1, self.matching_tokens[begin_token])
- res = "".join(self.prediction)
- if self.confidence is not None:
- return res, np.array(self.confidence)
- return res
diff --git a/dan/utils.py b/dan/utils.py
index 84e73824..d58db8fa 100644
--- a/dan/utils.py
+++ b/dan/utils.py
@@ -4,9 +4,6 @@ from itertools import islice
import torch
import torchvision.io as torchvision
-# Layout begin-token to end-token
-SEM_MATCHING_TOKENS = {"ⓘ": "â’¾", "â““": "â’¹", "â“¢": "Ⓢ", "â“’": "â’¸", "â“Ÿ": "â“…", "â“": "â’¶"}
-
class MLflowNotInstalled(Exception):
"""
diff --git a/docs/ref/post_processing.md b/docs/ref/post_processing.md
deleted file mode 100644
index 2c92ad28..00000000
--- a/docs/ref/post_processing.md
+++ /dev/null
@@ -1,3 +0,0 @@
-# Post processing
-
-::: dan.post_processing
diff --git a/docs/usage/train/parameters.md b/docs/usage/train/parameters.md
index 731e970d..b031dab9 100644
--- a/docs/usage/train/parameters.md
+++ b/docs/usage/train/parameters.md
@@ -4,16 +4,17 @@ All hyperparameters are specified and editable in the training scripts `dan/ocr/
## Dataset parameters
-| Parameter | Description | Type | Default |
-| -------------------------------------- | -------------------------------------------------------------------------------------- | ------ | ---------------------------------------------------- |
-| `dataset_name` | Name of the dataset. | `str` | |
-| `dataset_level` | Level of the dataset. Should be named after the element type. | `str` | |
-| `dataset_variant` | Variant of the dataset. Usually empty for HTR datasets, `"_sem"` for HTR+NER datasets. | `str` | |
-| `dataset_path` | Path to the dataset. | `str` | |
-| `dataset_params.config.load_in_memory` | Load all images in CPU memory. | `bool` | `True` |
-| `dataset_params.config.worker_per_gpu` | Number of parallel processes per gpu for data loading. | `int` | `4` |
-| `dataset_params.config.preprocessings` | List of pre-processing functions to apply to input images. | `list` | (see [dedicated section](#data-preprocessing)) |
-| `dataset_params.config.augmentation` | Whether to use data augmentation on the training set. | `bool` | `True` (see [dedicated section](#data-augmentation)) |
+| Parameter | Description | Type | Default |
+| -------------------------------------- | --------------------------------------------------------------------------------------------------------------------- | -------------- | ---------------------------------------------------- |
+| `dataset_name` | Name of the dataset. | `str` | |
+| `dataset_level` | Level of the dataset. Should be named after the element type. | `str` | |
+| `dataset_variant` | Variant of the dataset. Usually empty for HTR datasets, `"_sem"` for HTR+NER datasets. | `str` | |
+| `dataset_path` | Path to the dataset. | `str` | |
+| `dataset_params.config.load_in_memory` | Load all images in CPU memory. | `bool` | `True` |
+| `dataset_params.config.worker_per_gpu` | Number of parallel processes per gpu for data loading. | `int` | `4` |
+| `dataset_params.config.preprocessings` | List of pre-processing functions to apply to input images. | `list` | (see [dedicated section](#data-preprocessing)) |
+| `dataset_params.config.augmentation` | Whether to use data augmentation on the training set. | `bool` | `True` (see [dedicated section](#data-augmentation)) |
+| `dataset_params.tokens` | Path to a NER tokens configuration file similar to [the one used for extraction](../datasets/extract.md#description). | `pathlib.Path` | None |
!!! warning
The variables `dataset_name`, `dataset_level`, `dataset_variant` and `dataset_path` must have values such that the data is located in `{dataset_path}/{dataset_name}_{dataset_level}{dataset_variant}`.
diff --git a/mkdocs.yml b/mkdocs.yml
index 79cc177c..253be65f 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -100,7 +100,6 @@ nav:
- Decoders: ref/decoder.md
- Models: ref/encoder.md
- MLflow: ref/mlflow.md
- - Post Processing: ref/post_processing.md
- Schedulers: ref/schedulers.md
- Transformations: ref/transforms.md
- Utils: ref/utils.md
diff --git a/tests/conftest.py b/tests/conftest.py
index 2eda7829..c0bcfb8c 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -60,6 +60,7 @@ def training_config():
],
"augmentation": True,
},
+ "tokens": None,
},
"model_params": {
"models": {
--
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