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chore: remove logger info for chipper since its private #278

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Merged
merged 4 commits into from
Nov 6, 2023
Merged

chore: remove logger info for chipper since its private #278

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0d6e844
remove logger
yuming-long Nov 6, 2023
d61d35b
changelog nit
yuming-long Nov 6, 2023
5550b02
lintlint
yuming-long Nov 6, 2023
3489222
also remove the logger test for chipper
yuming-long Nov 6, 2023
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3 changes: 2 additions & 1 deletion CHANGELOG.md
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Original file line number Diff line number Diff line change
@@ -1,5 +1,6 @@
## 0.7.11-dev2
## 0.7.11-dev3

* chore: remove logger info for chipper since its private
* fix: update broken slack invite link in chipper logger info
* enhancement: Improve error message when # images extracted doesn't match # page layouts.
* fix: use automatic mixed precision on GPU for Chipper
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11 changes: 0 additions & 11 deletions test_unstructured_inference/models/test_model.py
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Expand Up @@ -35,17 +35,6 @@ def test_get_model(monkeypatch):
assert isinstance(models.get_model("checkbox"), MockModel)


def test_get_model_warns_on_chipper(monkeypatch, caplog):
monkeypatch.setattr(
models,
"UnstructuredChipperModel",
MockModel,
)
with mock.patch.object(models, "models", {}):
models.get_model("chipper")
assert caplog.records[0].levelname == "WARNING"


def test_raises_invalid_model():
with pytest.raises(models.UnknownModelException):
models.get_model("fake_model")
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2 changes: 1 addition & 1 deletion unstructured_inference/__version__.py
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@@ -1 +1 @@
__version__ = "0.7.11-dev2" # pragma: no cover
__version__ = "0.7.11-dev3" # pragma: no cover
8 changes: 0 additions & 8 deletions unstructured_inference/models/base.py
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@@ -1,6 +1,5 @@
from typing import Dict, Optional

from unstructured_inference.logger import logger
from unstructured_inference.models.chipper import MODEL_TYPES as CHIPPER_MODEL_TYPES
from unstructured_inference.models.chipper import UnstructuredChipperModel
from unstructured_inference.models.detectron2 import (
Expand Down Expand Up @@ -54,13 +53,6 @@ def get_model(model_name: Optional[str] = None, **kwargs) -> UnstructuredModel:
model = UnstructuredYoloXModel()
initialize_params = {**YOLOX_MODEL_TYPES[model_name], **kwargs}
elif model_name in CHIPPER_MODEL_TYPES:
logger.warning(
"The Chipper model is currently in Beta and is not yet ready for production use. "
"You can reach out to the Unstructured engineering team in the Unstructured "
"community Slack if you have any feedback on the Chipper model. "
"You can join the community Slack here: "
"https://short.unstructured.io/pzw05l7",
)
model = UnstructuredChipperModel()
initialize_params = {**CHIPPER_MODEL_TYPES[model_name], **kwargs}
elif model_name == "super_gradients":
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