CU-8699np02n Improve legacy conversion

medcat-v2/medcat/config/config.py

@@ -1,3 +1,4 @@
+import os
 from typing import (Optional, Iterator, Iterable, TypeVar, cast, Type, Any,
                     Literal)
 from typing import Protocol, runtime_checkable
@@ -12,6 +13,9 @@
 from medcat.utils.defaults import workers
 from medcat.utils.envsnapshot import Environment, get_environment_info
 from medcat.utils.iterutils import callback_iterator
+from medcat.utils.defaults import (
+    avoid_legacy_conversion, doing_legacy_conversion_message,
+    LegacyConversionDisabledError)
 from medcat.storage.serialisables import SerialisingStrategy
 from medcat.storage.serialisers import deserialise
 
@@ -80,6 +84,13 @@ def merge_config(self, other: dict):
 
     @classmethod
     def load(cls, path: str) -> Self:
+        if os.path.isfile(path) and path.endswith(".dat"):
+            if avoid_legacy_conversion():
+                raise LegacyConversionDisabledError(cls.__name__)
+            doing_legacy_conversion_message(logger, cls.__name__, path)
+            from medcat.utils.legacy.convert_config import (
+                get_config_from_old_per_cls)
+            return cast(Self, get_config_from_old_per_cls(path, cls))
         obj = deserialise(path)
         if not isinstance(obj, cls):
             raise ValueError(f"The path '{path}' is not a {cls.__name__}!")

medcat-v2/medcat/utils/legacy/convert_config.py

@@ -1,12 +1,13 @@
 import json
-from typing import Any, cast, Optional
+from typing import Any, cast, Optional, Type
 import logging
 
 from pydantic import BaseModel
 
 from medcat.config import Config
 
 from medcat.utils.legacy.helpers import fix_old_style_cnf
+from medcat.config.config import SerialisableBaseModel
 
 
 logger = logging.getLogger(__name__)
@@ -185,3 +186,34 @@ def get_config_from_old(path: str) -> Config:
     with open(path) as f:
         old_cnf_data = json.load(f)
     return get_config_from_nested_dict(old_cnf_data)
+
+
+def get_config_from_old_per_cls(
+        path: str, cls: Type[SerialisableBaseModel]) -> SerialisableBaseModel:
+    """Convert the saved v1 config into a v2 Config for a specific class.
+
+    Args:
+        path (str): The v1 config path.
+        cls (Type[SerialisableBaseModel]): The class to convert to.
+
+    Returns:
+        SerialisableBaseModel: The converted config.
+    """
+    from medcat.config.config_meta_cat import ConfigMetaCAT
+    from medcat.config.config_transformers_ner import ConfigTransformersNER
+    from medcat.config.config_rel_cat import ConfigRelCAT
+    if cls is Config:
+        return get_config_from_old(path)
+    elif cls is ConfigMetaCAT:
+        from medcat.utils.legacy.convert_meta_cat import (
+            load_cnf as load_meta_cat_cnf)
+        return load_meta_cat_cnf(path)
+    elif cls is ConfigTransformersNER:
+        from medcat.utils.legacy.convert_deid import (
+            get_cnf as load_deid_cnf)
+        return load_deid_cnf(path)
+    elif cls is ConfigRelCAT:
+        from medcat.utils.legacy.convert_rel_cat import (
+            load_cnf as load_rel_cat_cnf)
+        return load_rel_cat_cnf(path)
+    raise ValueError(f"The config at '{path}' is not a {cls.__name__}!")

medcat-v2/tests/resources/mct_v1_deid_cnf.json

@@ -0,0 +1 @@
+{"general": {"name": "NOT-DEID", "model_name": "roberta-base", "seed": 13, "description": "No description", "pipe_batch_size_in_chars": 20000000, "ner_aggregation_strategy": "simple", "chunking_overlap_window": 5, "test_size": 0.2, "last_train_on": null, "verbose_metrics": false}}

medcat-v2/tests/resources/mct_v1_meta_cat_cnf.json

@@ -0,0 +1 @@
+{"general": {"device": "cpu", "disable_component_lock": false, "seed": 13, "description": "No description", "category_name": "TEST CATEGORY", "alternative_category_names": [], "category_value2id": {}, "alternative_class_names": [[]], "vocab_size": 3, "lowercase": true, "cntx_left": 15, "cntx_right": 10, "replace_center": null, "batch_size_eval": 5000, "annotate_overlapping": false, "tokenizer_name": "bbpe", "save_and_reuse_tokens": false, "pipe_batch_size_in_chars": 20000000, "span_group": null}, "model": {"model_name": "lstm", "model_variant": "bert-base-uncased", "model_freeze_layers": true, "num_layers": 2, "input_size": 300, "hidden_size": 300, "dropout": 0.5, "phase_number": 0, "category_undersample": "", "model_architecture_config": {"fc2": true, "fc3": false, "lr_scheduler": true}, "num_directions": 2, "nclasses": 2, "padding_idx": -1, "emb_grad": true, "ignore_cpos": false}, "train": {"batch_size": 100, "nepochs": 50, "lr": 0.001, "test_size": 0.1, "shuffle_data": true, "class_weights": null, "compute_class_weights": false, "score_average": "weighted", "prerequisites": {}, "cui_filter": null, "auto_save_model": true, "last_train_on": null, "metric": {"base": "weighted avg", "score": "f1-score"}, "loss_funct": "cross_entropy", "gamma": 2}}

medcat-v2/tests/resources/mct_v1_rel_cat_cnf.json

@@ -0,0 +1 @@
+{"general": {"device": "cpu", "relation_type_filter_pairs": [], "vocab_size": null, "lowercase": true, "cntx_left": 15, "cntx_right": 15, "window_size": 300, "limit_samples_per_class": -1, "addl_rels_max_sample_size": 200, "create_addl_rels": false, "create_addl_rels_by_type": false, "tokenizer_name": "bert", "model_name": "bert-unknown", "log_level": 20, "max_seq_length": 512, "tokenizer_special_tokens": false, "annotation_schema_tag_ids": [30522, 30523, 30524, 30525], "tokenizer_relation_annotation_special_tokens_tags": ["[s1]", "[e1]", "[s2]", "[e2]"], "tokenizer_other_special_tokens": {"pad_token": "[PAD]"}, "labels2idx": {}, "idx2labels": {}, "pin_memory": true, "seed": 13, "task": "train", "language": "en"}, "model": {"input_size": 300, "hidden_size": 768, "hidden_layers": 3, "model_size": 5120, "dropout": 0.2, "num_directions": 2, "freeze_layers": true, "padding_idx": -1, "emb_grad": true, "ignore_cpos": false, "llama_use_pooled_output": false}, "train": {"nclasses": 2, "batch_size": 25, "nepochs": 1, "lr": 0.0001, "stratified_batching": false, "batching_samples_per_class": [], "batching_minority_limit": 0, "adam_betas": [0.9, 0.999], "adam_weight_decay": 0, "adam_epsilon": 1e-08, "test_size": 0.2, "gradient_acc_steps": 1, "multistep_milestones": [2, 4, 6, 8, 12, 15, 18, 20, 22, 24, 26, 30], "multistep_lr_gamma": 0.8, "max_grad_norm": 1.0, "shuffle_data": true, "class_weights": null, "enable_class_weights": false, "score_average": "weighted", "auto_save_model": true}}

medcat-v2/tests/utils/legacy/test_convert_config.py

@@ -1,14 +1,19 @@
+from typing import Type, Any
 import os
 
 from medcat.utils.legacy import convert_config
 
 from medcat.config import Config
+from medcat.config.config import SerialisableBaseModel
+from medcat.config.config_meta_cat import ConfigMetaCAT
+from medcat.config.config_rel_cat import ConfigRelCAT
+from medcat.config.config_transformers_ner import ConfigTransformersNER
 
 import unittest
 
 
-TESTS_PATH = os.path.abspath(os.path.join(os.path.dirname(__file__),
-                                          "..", ".."))
+from ... import RESOURCES_PATH
+TESTS_PATH = os.path.dirname(RESOURCES_PATH)
 
 
 class ValAndModelGetterTests(unittest.TestCase):
@@ -78,3 +83,47 @@ def test_migrates_partial(self):
     def test_preprocesses_sets(self):
         self.assertEqual(self.cnf.preprocessing.words_to_skip,
                          self.EXP_WORDS_TO_SKIP)
+
+
+class PerClsConfigConversionTests(unittest.TestCase):
+    # paths, classes, expected path, expected value
+    # NOTE: These are hard-coded values I know I changed in the confgis
+    #       before saving
+    PATHS_AND_CLASSES: list[str, Type[SerialisableBaseModel], str, Any] = [
+        (os.path.join(RESOURCES_PATH,
+                      "mct_v1_cnf.json"), Config,
+         'meta.description', "FAKE MODEL"),
+        (os.path.join(RESOURCES_PATH,
+         "mct_v1_meta_cat_cnf.json"), ConfigMetaCAT,
+         "general.category_name", 'TEST CATEGORY'),
+        (os.path.join(RESOURCES_PATH,
+         "mct_v1_rel_cat_cnf.json"), ConfigRelCAT,
+         "general.model_name", 'bert-unknown'),
+        (os.path.join(RESOURCES_PATH,
+         "mct_v1_deid_cnf.json"), ConfigTransformersNER,
+         "general.name", 'NOT-DEID'),
+    ]
+
+    @classmethod
+    def setUpClass(cls):
+        return super().setUpClass()
+
+    def _get_attr_nested(self, obj: SerialisableBaseModel, path: str) -> Any:
+        """Get an attribute from a nested object using a dot-separated path."""
+        parts = path.split('.')
+        for part in parts:
+            obj = getattr(obj, part)
+        return obj
+
+    def assert_can_convert(
+            self, path, cls: Type[SerialisableBaseModel],
+            exp_path: str, exp_value: Any):
+        cnf = convert_config.get_config_from_old_per_cls(path, cls)
+        self.assertIsInstance(cnf, cls, f"Failed for {cls.__name__}")
+        self.assertEqual(self._get_attr_nested(cnf, exp_path), exp_value,
+                         f"Failed for {cls.__name__} at {exp_path}")
+
+    def test_can_convert(self):
+        for path, cls, exp_path, exp_value in self.PATHS_AND_CLASSES:
+            with self.subTest(f"Testing {cls.__name__} at {path}"):
+                self.assert_can_convert(path, cls, exp_path, exp_value)