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Remove static pretrained maps from the library's internals (#29112)

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* [test_all] Remove static pretrained maps from the library's internals

* Deprecate archive maps instead of removing them

* Revert init changes

* [test_all] Deprecate instead of removing

* [test_all] PVT v2 support

* [test_all] Tests should all pass

* [test_all] Style

* Address review comments

* Update src/transformers/models/deprecated/_archive_maps.py

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update src/transformers/models/deprecated/_archive_maps.py

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* [test_all] trigger tests

* [test_all] LLAVA

* [test_all] Bad rebase

---------

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
This commit is contained in:
Lysandre Debut
2024-03-25 10:33:38 +01:00
committed by GitHub
parent 76a33a1092
commit 39114c0383
842 changed files with 4608 additions and 8613 deletions
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9
tests/models/mt5/test_modeling_mt5.py
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@@ -51,7 +51,6 @@ if is_torch_available():
MT5ForTokenClassification,
MT5Model,
)
from transformers.models.mt5.modeling_mt5 import MT5_PRETRAINED_MODEL_ARCHIVE_LIST
# Copied from tests.models.t5.test_modeling_t5.T5ModelTester with T5->MT5
@@ -546,7 +545,7 @@ class MT5ModelTester:
@require_torch
# Copied from tests.models.t5.test_modeling_t5.T5ModelTest with T5->MT5
# Copied from tests.models.t5.test_modeling_t5.T5ModelTest with T5->MT5, google-t5/t5-small->google/mt5-small
class MT5ModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixin, unittest.TestCase):
all_model_classes = (
(MT5Model, MT5ForConditionalGeneration, MT5ForSequenceClassification, MT5ForQuestionAnswering)
@@ -835,9 +834,9 @@ class MT5ModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixin,
@slow
def test_model_from_pretrained(self):
for model_name in MT5_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
model = MT5Model.from_pretrained(model_name)
self.assertIsNotNone(model)
model_name = "google/mt5-small"
model = MT5Model.from_pretrained(model_name)
self.assertIsNotNone(model)
@unittest.skip("Test has a segmentation fault on torch 1.8.0")
def test_export_to_onnx(self):