From c7c24d4c806e50bedec67c059ab3b43676638939 Mon Sep 17 00:00:00 2001
From: Tirth Patel <tirthasheshpatel@gmail.com>
Date: Fri, 20 Oct 2023 20:37:57 +0000
Subject: [PATCH 01/14] Remove SentencePieceTrainer from
 keras_nlp/models/albert

---
 .../models/albert/albert_classifier_test.py   |  33 +++-----
 .../albert_masked_lm_preprocessor_test.py     |  29 +++----
 .../models/albert/albert_masked_lm_test.py    |  32 +++-----
 .../models/albert/albert_preprocessor_test.py |  29 +++----
 .../models/albert/albert_tokenizer_test.py    |  51 +++++-------
 .../test_data/albert_sentencepiece.proto      | Bin 0 -> 237831 bytes
 .../test_data/albert_sentencepiece_bad.proto  | Bin 0 -> 237677 bytes
 .../create_albert_test_proto.py               |  73 ++++++++++++++++++
 8 files changed, 138 insertions(+), 109 deletions(-)
 create mode 100644 keras_nlp/tests/test_data/albert_sentencepiece.proto
 create mode 100644 keras_nlp/tests/test_data/albert_sentencepiece_bad.proto
 create mode 100644 tools/sentencepiece_testing/create_albert_test_proto.py

diff --git a/keras_nlp/models/albert/albert_classifier_test.py b/keras_nlp/models/albert/albert_classifier_test.py
index e2581df6a1..4fe1fc1761 100644
--- a/keras_nlp/models/albert/albert_classifier_test.py
+++ b/keras_nlp/models/albert/albert_classifier_test.py
@@ -12,10 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import io
+import pathlib
 
 import pytest
-import sentencepiece
 
 from keras_nlp.models.albert.albert_backbone import AlbertBackbone
 from keras_nlp.models.albert.albert_classifier import AlbertClassifier
@@ -27,26 +26,18 @@
 class AlbertClassifierTest(TestCase):
     def setUp(self):
         # Setup model.
-        vocab_data = ["the quick brown fox", "the earth is round"]
-        bytes_io = io.BytesIO()
-        sentencepiece.SentencePieceTrainer.train(
-            sentence_iterator=iter(vocab_data),
-            model_writer=bytes_io,
-            vocab_size=12,
-            model_type="WORD",
-            pad_id=0,
-            unk_id=1,
-            bos_id=2,
-            eos_id=3,
-            pad_piece="<pad>",
-            unk_piece="<unk>",
-            bos_piece="[CLS]",
-            eos_piece="[SEP]",
-            user_defined_symbols="[MASK]",
-        )
         self.preprocessor = AlbertPreprocessor(
-            AlbertTokenizer(proto=bytes_io.getvalue()),
-            sequence_length=5,
+            AlbertTokenizer(
+                proto=str(
+                    (
+                        pathlib.Path(__file__).parent.parent.parent
+                        / "tests"
+                        / "test_data"
+                        / "albert_sentencepiece.proto"
+                    ).absolute()
+                ),
+                sequence_length=5,
+            )
         )
         self.backbone = AlbertBackbone(
             vocabulary_size=self.preprocessor.tokenizer.vocabulary_size(),
diff --git a/keras_nlp/models/albert/albert_masked_lm_preprocessor_test.py b/keras_nlp/models/albert/albert_masked_lm_preprocessor_test.py
index 36eef72f39..c993abf3e9 100644
--- a/keras_nlp/models/albert/albert_masked_lm_preprocessor_test.py
+++ b/keras_nlp/models/albert/albert_masked_lm_preprocessor_test.py
@@ -12,10 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import io
+import pathlib
 
 import pytest
-import sentencepiece
 
 from keras_nlp.models.albert.albert_masked_lm_preprocessor import (
     AlbertMaskedLMPreprocessor,
@@ -26,24 +25,16 @@
 
 class AlbertMaskedLMPreprocessorTest(TestCase):
     def setUp(self):
-        vocab_data = ["the quick brown fox", "the earth is round"]
-        bytes_io = io.BytesIO()
-        sentencepiece.SentencePieceTrainer.train(
-            sentence_iterator=iter(vocab_data),
-            model_writer=bytes_io,
-            vocab_size=12,
-            model_type="WORD",
-            pad_id=0,
-            unk_id=1,
-            bos_id=2,
-            eos_id=3,
-            pad_piece="<pad>",
-            unk_piece="<unk>",
-            bos_piece="[CLS]",
-            eos_piece="[SEP]",
-            user_defined_symbols="[MASK]",
+        self.tokenizer = AlbertTokenizer(
+            proto=str(
+                (
+                    pathlib.Path(__file__).parent.parent.parent
+                    / "tests"
+                    / "test_data"
+                    / "albert_sentencepiece.proto"
+                ).absolute()
+            )
         )
-        self.tokenizer = AlbertTokenizer(proto=bytes_io.getvalue())
         self.init_kwargs = {
             "tokenizer": self.tokenizer,
             # Simplify our testing by masking every available token.
diff --git a/keras_nlp/models/albert/albert_masked_lm_test.py b/keras_nlp/models/albert/albert_masked_lm_test.py
index 456b0edda4..8273fc9581 100644
--- a/keras_nlp/models/albert/albert_masked_lm_test.py
+++ b/keras_nlp/models/albert/albert_masked_lm_test.py
@@ -12,10 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import io
+import pathlib
 
 import pytest
-import sentencepiece
 
 from keras_nlp.models.albert.albert_backbone import AlbertBackbone
 from keras_nlp.models.albert.albert_masked_lm import AlbertMaskedLM
@@ -29,25 +28,18 @@
 class AlbertMaskedLMTest(TestCase):
     def setUp(self):
         # Setup model.
-        vocab_data = ["the quick brown fox", "the earth is round"]
-        bytes_io = io.BytesIO()
-        sentencepiece.SentencePieceTrainer.train(
-            sentence_iterator=iter(vocab_data),
-            model_writer=bytes_io,
-            vocab_size=12,
-            model_type="WORD",
-            pad_id=0,
-            unk_id=1,
-            bos_id=2,
-            eos_id=3,
-            pad_piece="<pad>",
-            unk_piece="<unk>",
-            bos_piece="[CLS]",
-            eos_piece="[SEP]",
-            user_defined_symbols="[MASK]",
-        )
         self.preprocessor = AlbertMaskedLMPreprocessor(
-            AlbertTokenizer(proto=bytes_io.getvalue()),
+            AlbertTokenizer(
+                proto=str(
+                    (
+                        pathlib.Path(__file__).parent.parent.parent
+                        / "tests"
+                        / "test_data"
+                        / "albert_sentencepiece.proto"
+                    ).absolute()
+                ),
+                sequence_length=5,
+            ),
             # Simplify our testing by masking every available token.
             mask_selection_rate=1.0,
             mask_token_rate=1.0,
diff --git a/keras_nlp/models/albert/albert_preprocessor_test.py b/keras_nlp/models/albert/albert_preprocessor_test.py
index 95cb2c832e..07c49dd59c 100644
--- a/keras_nlp/models/albert/albert_preprocessor_test.py
+++ b/keras_nlp/models/albert/albert_preprocessor_test.py
@@ -12,10 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import io
+import pathlib
 
 import pytest
-import sentencepiece
 
 from keras_nlp.models.albert.albert_preprocessor import AlbertPreprocessor
 from keras_nlp.models.albert.albert_tokenizer import AlbertTokenizer
@@ -24,24 +23,16 @@
 
 class AlbertPreprocessorTest(TestCase):
     def setUp(self):
-        vocab_data = ["the quick brown fox", "the earth is round"]
-        bytes_io = io.BytesIO()
-        sentencepiece.SentencePieceTrainer.train(
-            sentence_iterator=iter(vocab_data),
-            model_writer=bytes_io,
-            vocab_size=12,
-            model_type="WORD",
-            pad_id=0,
-            unk_id=1,
-            bos_id=2,
-            eos_id=3,
-            pad_piece="<pad>",
-            unk_piece="<unk>",
-            bos_piece="[CLS]",
-            eos_piece="[SEP]",
-            user_defined_symbols="[MASK]",
+        self.tokenizer = AlbertTokenizer(
+            proto=str(
+                (
+                    pathlib.Path(__file__).parent.parent.parent
+                    / "tests"
+                    / "test_data"
+                    / "albert_sentencepiece.proto"
+                ).absolute()
+            )
         )
-        self.tokenizer = AlbertTokenizer(proto=bytes_io.getvalue())
         self.init_kwargs = {
             "tokenizer": self.tokenizer,
             "sequence_length": 8,
diff --git a/keras_nlp/models/albert/albert_tokenizer_test.py b/keras_nlp/models/albert/albert_tokenizer_test.py
index e645436c09..ee47225f1e 100644
--- a/keras_nlp/models/albert/albert_tokenizer_test.py
+++ b/keras_nlp/models/albert/albert_tokenizer_test.py
@@ -12,10 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import io
+import pathlib
 
 import pytest
-import sentencepiece
 
 from keras_nlp.models.albert.albert_tokenizer import AlbertTokenizer
 from keras_nlp.tests.test_case import TestCase
@@ -23,24 +22,16 @@
 
 class AlbertTokenizerTest(TestCase):
     def setUp(self):
-        vocab_data = ["the quick brown fox", "the earth is round"]
-        bytes_io = io.BytesIO()
-        sentencepiece.SentencePieceTrainer.train(
-            sentence_iterator=iter(vocab_data),
-            model_writer=bytes_io,
-            vocab_size=12,
-            model_type="WORD",
-            pad_id=0,
-            unk_id=1,
-            bos_id=2,
-            eos_id=3,
-            pad_piece="<pad>",
-            unk_piece="<unk>",
-            bos_piece="[CLS]",
-            eos_piece="[SEP]",
-            user_defined_symbols="[MASK]",
-        )
-        self.init_kwargs = {"proto": bytes_io.getvalue()}
+        self.init_kwargs = {
+            "proto": str(
+                (
+                    pathlib.Path(__file__).parent.parent.parent
+                    / "tests"
+                    / "test_data"
+                    / "albert_sentencepiece.proto"
+                ).absolute()
+            )
+        }
         self.input_data = ["the quick brown fox.", "the earth is round."]
 
     def test_tokenizer_basics(self):
@@ -52,17 +43,17 @@ def test_tokenizer_basics(self):
         )
 
     def test_errors_missing_special_tokens(self):
-        bytes_io = io.BytesIO()
-        sentencepiece.SentencePieceTrainer.train(
-            sentence_iterator=iter(["abc"]),
-            model_writer=bytes_io,
-            vocab_size=5,
-            pad_id=-1,
-            eos_id=-1,
-            bos_id=-1,
-        )
         with self.assertRaises(ValueError):
-            AlbertTokenizer(proto=bytes_io.getvalue())
+            AlbertTokenizer(
+                proto=str(
+                    (
+                        pathlib.Path(__file__).parent.parent.parent
+                        / "tests"
+                        / "test_data"
+                        / "albert_sentencepiece_bad.proto"
+                    ).absolute()
+                )
+            )
 
     @pytest.mark.large
     def test_smallest_preset(self):
diff --git a/keras_nlp/tests/test_data/albert_sentencepiece.proto b/keras_nlp/tests/test_data/albert_sentencepiece.proto
new file mode 100644
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GIT binary patch
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diff --git a/keras_nlp/tests/test_data/albert_sentencepiece_bad.proto b/keras_nlp/tests/test_data/albert_sentencepiece_bad.proto
new file mode 100644
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HcmV?d00001

diff --git a/tools/sentencepiece_testing/create_albert_test_proto.py b/tools/sentencepiece_testing/create_albert_test_proto.py
new file mode 100644
index 0000000000..991d6c133b
--- /dev/null
+++ b/tools/sentencepiece_testing/create_albert_test_proto.py
@@ -0,0 +1,73 @@
+# Copyright 2023 The KerasNLP Authors
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import io
+import pathlib
+
+import sentencepiece
+
+
+def _train_sentencepiece(data, *args, **kwargs):
+    bytes_io = io.BytesIO()
+    sentencepiece.SentencePieceTrainer.train(
+        sentence_iterator=iter(data), model_writer=bytes_io, *args, **kwargs
+    )
+    return bytes_io
+
+
+def main():
+    bytes_io = _train_sentencepiece(
+        ["the quick brown fox", "the earth is round"],
+        vocab_size=12,
+        model_type="WORD",
+        pad_id=0,
+        unk_id=1,
+        bos_id=2,
+        eos_id=3,
+        pad_piece="<pad>",
+        unk_piece="<unk>",
+        bos_piece="[CLS]",
+        eos_piece="[SEP]",
+        user_defined_symbols="[MASK]",
+    )
+    with open(
+        pathlib.Path(__file__).parent.parent.parent
+        / "keras_nlp"
+        / "tests"
+        / "test_data"
+        / "albert_sentencepiece.proto",
+        mode="wb",
+    ) as f:
+        f.write(bytes_io.getbuffer())
+
+    bytes_io = _train_sentencepiece(
+        ["abc"],
+        vocab_size=5,
+        pad_id=-1,
+        eos_id=-1,
+        bos_id=-1,
+    )
+    with open(
+        pathlib.Path(__file__).parent.parent.parent
+        / "keras_nlp"
+        / "tests"
+        / "test_data"
+        / "albert_sentencepiece_bad.proto",
+        mode="wb",
+    ) as f:
+        f.write(bytes_io.getbuffer())
+
+
+if __name__ == "__main__":
+    main()

From 4261061a81e5c90945691bc35c3a0c90d0abf9cb Mon Sep 17 00:00:00 2001
From: Tirth Patel <tirthasheshpatel@gmail.com>
Date: Fri, 20 Oct 2023 21:31:51 +0000
Subject: [PATCH 02/14] Remove SentencePieceTrainer from
 keras_nlp/models/deberta_v3

---
 .../deberta_v3/deberta_v3_classifier_test.py  |  31 ++++-----
 .../deberta_v3_masked_lm_preprocessor_test.py |  29 +++-----
 .../deberta_v3/deberta_v3_masked_lm_test.py   |  31 ++++-----
 .../deberta_v3_preprocessor_test.py           |  29 +++-----
 .../deberta_v3/deberta_v3_tokenizer_test.py   |  49 ++++++--------
 .../test_data/deberta_v3_sentencepiece.proto  | Bin 0 -> 237831 bytes
 .../deberta_v3_sentencepiece_bad.proto        | Bin 0 -> 237677 bytes
 .../deberta_v3_tokenizer_sentencepiece.proto  | Bin 0 -> 237805 bytes
 tools/sentencepiece_testing/__init__.py       |  13 ++++
 .../create_albert_test_proto.py               |  34 ++--------
 .../create_deberta_v3_test_proto.py           |  62 ++++++++++++++++++
 tools/sentencepiece_testing/utils.py          |  37 +++++++++++
 12 files changed, 178 insertions(+), 137 deletions(-)
 create mode 100644 keras_nlp/tests/test_data/deberta_v3_sentencepiece.proto
 create mode 100644 keras_nlp/tests/test_data/deberta_v3_sentencepiece_bad.proto
 create mode 100644 keras_nlp/tests/test_data/deberta_v3_tokenizer_sentencepiece.proto
 create mode 100644 tools/sentencepiece_testing/__init__.py
 create mode 100644 tools/sentencepiece_testing/create_deberta_v3_test_proto.py
 create mode 100644 tools/sentencepiece_testing/utils.py

diff --git a/keras_nlp/models/deberta_v3/deberta_v3_classifier_test.py b/keras_nlp/models/deberta_v3/deberta_v3_classifier_test.py
index 046c18dd5e..cd6d8f3d6e 100644
--- a/keras_nlp/models/deberta_v3/deberta_v3_classifier_test.py
+++ b/keras_nlp/models/deberta_v3/deberta_v3_classifier_test.py
@@ -12,10 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import io
+import pathlib
 
 import pytest
-import sentencepiece
 
 from keras_nlp.models.deberta_v3.deberta_v3_backbone import DebertaV3Backbone
 from keras_nlp.models.deberta_v3.deberta_v3_classifier import (
@@ -31,25 +30,17 @@
 class DebertaV3ClassifierTest(TestCase):
     def setUp(self):
         # Setup model.
-        vocab_data = ["the quick brown fox", "the earth is round"]
-        bytes_io = io.BytesIO()
-        sentencepiece.SentencePieceTrainer.train(
-            sentence_iterator=iter(vocab_data),
-            model_writer=bytes_io,
-            vocab_size=12,
-            model_type="WORD",
-            pad_id=0,
-            bos_id=1,
-            eos_id=2,
-            unk_id=3,
-            pad_piece="[PAD]",
-            bos_piece="[CLS]",
-            eos_piece="[SEP]",
-            unk_piece="[UNK]",
-            user_defined_symbols="[MASK]",
-        )
         self.preprocessor = DebertaV3Preprocessor(
-            DebertaV3Tokenizer(proto=bytes_io.getvalue()),
+            DebertaV3Tokenizer(
+                proto=str(
+                    (
+                        pathlib.Path(__file__).parent.parent.parent
+                        / "tests"
+                        / "test_data"
+                        / "deberta_v3_sentencepiece.proto"
+                    ).absolute()
+                )
+            ),
             sequence_length=5,
         )
         self.backbone = DebertaV3Backbone(
diff --git a/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_preprocessor_test.py b/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_preprocessor_test.py
index faf1ee1a8f..4b7d490b66 100644
--- a/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_preprocessor_test.py
+++ b/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_preprocessor_test.py
@@ -12,10 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import io
+import pathlib
 
 import pytest
-import sentencepiece
 
 from keras_nlp.models.deberta_v3.deberta_v3_masked_lm_preprocessor import (
     DebertaV3MaskedLMPreprocessor,
@@ -26,24 +25,16 @@
 
 class DebertaV3MaskedLMPreprocessorTest(TestCase):
     def setUp(self):
-        vocab_data = ["the quick brown fox", "the earth is round"]
-        bytes_io = io.BytesIO()
-        sentencepiece.SentencePieceTrainer.train(
-            sentence_iterator=iter(vocab_data),
-            model_writer=bytes_io,
-            vocab_size=12,
-            model_type="WORD",
-            pad_id=0,
-            bos_id=1,
-            eos_id=2,
-            unk_id=3,
-            pad_piece="[PAD]",
-            bos_piece="[CLS]",
-            eos_piece="[SEP]",
-            unk_piece="[UNK]",
-            user_defined_symbols="[MASK]",
+        self.tokenizer = DebertaV3Tokenizer(
+            proto=str(
+                (
+                    pathlib.Path(__file__).parent.parent.parent
+                    / "tests"
+                    / "test_data"
+                    / "deberta_v3_sentencepiece.proto"
+                ).absolute()
+            )
         )
-        self.tokenizer = DebertaV3Tokenizer(proto=bytes_io.getvalue())
         self.init_kwargs = {
             "tokenizer": self.tokenizer,
             # Simplify our testing by masking every available token.
diff --git a/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_test.py b/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_test.py
index 62f84b508c..c93049ec2d 100644
--- a/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_test.py
+++ b/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_test.py
@@ -12,10 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import io
+import pathlib
 
 import pytest
-import sentencepiece
 
 from keras_nlp.models.deberta_v3.deberta_v3_backbone import DebertaV3Backbone
 from keras_nlp.models.deberta_v3.deberta_v3_masked_lm import DebertaV3MaskedLM
@@ -29,25 +28,17 @@
 class DebertaV3MaskedLMTest(TestCase):
     def setUp(self):
         # Setup model.
-        vocab_data = ["the quick brown fox", "the earth is round"]
-        bytes_io = io.BytesIO()
-        sentencepiece.SentencePieceTrainer.train(
-            sentence_iterator=iter(vocab_data),
-            model_writer=bytes_io,
-            vocab_size=12,
-            model_type="WORD",
-            pad_id=0,
-            bos_id=1,
-            eos_id=2,
-            unk_id=3,
-            pad_piece="[PAD]",
-            bos_piece="[CLS]",
-            eos_piece="[SEP]",
-            unk_piece="[UNK]",
-            user_defined_symbols="[MASK]",
-        )
         self.preprocessor = DebertaV3MaskedLMPreprocessor(
-            DebertaV3Tokenizer(proto=bytes_io.getvalue()),
+            DebertaV3Tokenizer(
+                proto=str(
+                    (
+                        pathlib.Path(__file__).parent.parent.parent
+                        / "tests"
+                        / "test_data"
+                        / "deberta_v3_sentencepiece.proto"
+                    ).absolute()
+                )
+            ),
             # Simplify our testing by masking every available token.
             mask_selection_rate=1.0,
             mask_token_rate=1.0,
diff --git a/keras_nlp/models/deberta_v3/deberta_v3_preprocessor_test.py b/keras_nlp/models/deberta_v3/deberta_v3_preprocessor_test.py
index f6f648ab83..920c6cbe26 100644
--- a/keras_nlp/models/deberta_v3/deberta_v3_preprocessor_test.py
+++ b/keras_nlp/models/deberta_v3/deberta_v3_preprocessor_test.py
@@ -12,10 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import io
+import pathlib
 
 import pytest
-import sentencepiece
 
 from keras_nlp.models.deberta_v3.deberta_v3_preprocessor import (
     DebertaV3Preprocessor,
@@ -26,24 +25,16 @@
 
 class DebertaV3PreprocessorTest(TestCase):
     def setUp(self):
-        vocab_data = ["the quick brown fox", "the earth is round"]
-        bytes_io = io.BytesIO()
-        sentencepiece.SentencePieceTrainer.train(
-            sentence_iterator=iter(vocab_data),
-            model_writer=bytes_io,
-            vocab_size=12,
-            model_type="WORD",
-            pad_id=0,
-            bos_id=1,
-            eos_id=2,
-            unk_id=3,
-            pad_piece="[PAD]",
-            bos_piece="[CLS]",
-            eos_piece="[SEP]",
-            unk_piece="[UNK]",
-            user_defined_symbols="[MASK]",
+        self.tokenizer = DebertaV3Tokenizer(
+            proto=str(
+                (
+                    pathlib.Path(__file__).parent.parent.parent
+                    / "tests"
+                    / "test_data"
+                    / "deberta_v3_sentencepiece.proto"
+                ).absolute()
+            )
         )
-        self.tokenizer = DebertaV3Tokenizer(proto=bytes_io.getvalue())
         self.init_kwargs = {
             "tokenizer": self.tokenizer,
             "sequence_length": 8,
diff --git a/keras_nlp/models/deberta_v3/deberta_v3_tokenizer_test.py b/keras_nlp/models/deberta_v3/deberta_v3_tokenizer_test.py
index c542de786d..2123971f62 100644
--- a/keras_nlp/models/deberta_v3/deberta_v3_tokenizer_test.py
+++ b/keras_nlp/models/deberta_v3/deberta_v3_tokenizer_test.py
@@ -12,10 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import io
+import pathlib
 
 import pytest
-import sentencepiece
 
 from keras_nlp.models.deberta_v3.deberta_v3_tokenizer import DebertaV3Tokenizer
 from keras_nlp.tests.test_case import TestCase
@@ -23,24 +22,16 @@
 
 class DebertaV3TokenizerTest(TestCase):
     def setUp(self):
-        vocab_data = ["the quick brown fox", "the earth is round"]
-        bytes_io = io.BytesIO()
-        sentencepiece.SentencePieceTrainer.train(
-            sentence_iterator=iter(vocab_data),
-            model_writer=bytes_io,
-            vocab_size=11,
-            model_type="WORD",
-            pad_id=0,
-            bos_id=1,
-            eos_id=2,
-            unk_id=3,
-            pad_piece="[PAD]",
-            bos_piece="[CLS]",
-            eos_piece="[SEP]",
-            unk_piece="[UNK]",
+        proto = str(
+            (
+                pathlib.Path(__file__).parent.parent.parent
+                / "tests"
+                / "test_data"
+                / "deberta_v3_tokenizer_sentencepiece.proto"
+            ).absolute()
         )
-        self.tokenizer = DebertaV3Tokenizer(proto=bytes_io.getvalue())
-        self.init_kwargs = {"proto": bytes_io.getvalue()}
+        self.tokenizer = DebertaV3Tokenizer(proto=proto)
+        self.init_kwargs = {"proto": proto}
         self.input_data = ["the quick brown fox.", "the earth is round."]
 
     def test_tokenizer_basics(self):
@@ -52,17 +43,17 @@ def test_tokenizer_basics(self):
         )
 
     def test_errors_missing_special_tokens(self):
-        bytes_io = io.BytesIO()
-        sentencepiece.SentencePieceTrainer.train(
-            sentence_iterator=iter(["abc"]),
-            model_writer=bytes_io,
-            vocab_size=5,
-            pad_id=-1,
-            eos_id=-1,
-            bos_id=-1,
-        )
         with self.assertRaises(ValueError):
-            DebertaV3Tokenizer(proto=bytes_io.getvalue())
+            DebertaV3Tokenizer(
+                proto=str(
+                    (
+                        pathlib.Path(__file__).parent.parent.parent
+                        / "tests"
+                        / "test_data"
+                        / "deberta_v3_sentencepiece_bad.proto"
+                    ).absolute()
+                )
+            )
 
     def test_mask_token_handling(self):
         tokenizer = DebertaV3Tokenizer(**self.init_kwargs)
diff --git a/keras_nlp/tests/test_data/deberta_v3_sentencepiece.proto b/keras_nlp/tests/test_data/deberta_v3_sentencepiece.proto
new file mode 100644
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diff --git a/keras_nlp/tests/test_data/deberta_v3_sentencepiece_bad.proto b/keras_nlp/tests/test_data/deberta_v3_sentencepiece_bad.proto
new file mode 100644
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diff --git a/keras_nlp/tests/test_data/deberta_v3_tokenizer_sentencepiece.proto b/keras_nlp/tests/test_data/deberta_v3_tokenizer_sentencepiece.proto
new file mode 100644
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literal 0
HcmV?d00001

diff --git a/tools/sentencepiece_testing/__init__.py b/tools/sentencepiece_testing/__init__.py
new file mode 100644
index 0000000000..ba0c2545e4
--- /dev/null
+++ b/tools/sentencepiece_testing/__init__.py
@@ -0,0 +1,13 @@
+# Copyright 2023 The KerasNLP Authors
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
diff --git a/tools/sentencepiece_testing/create_albert_test_proto.py b/tools/sentencepiece_testing/create_albert_test_proto.py
index 991d6c133b..8774a395f7 100644
--- a/tools/sentencepiece_testing/create_albert_test_proto.py
+++ b/tools/sentencepiece_testing/create_albert_test_proto.py
@@ -12,18 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import io
-import pathlib
-
-import sentencepiece
-
-
-def _train_sentencepiece(data, *args, **kwargs):
-    bytes_io = io.BytesIO()
-    sentencepiece.SentencePieceTrainer.train(
-        sentence_iterator=iter(data), model_writer=bytes_io, *args, **kwargs
-    )
-    return bytes_io
+from tools.sentencepiece_testing.utils import _save
+from tools.sentencepiece_testing.utils import _train_sentencepiece
 
 
 def main():
@@ -41,15 +31,7 @@ def main():
         eos_piece="[SEP]",
         user_defined_symbols="[MASK]",
     )
-    with open(
-        pathlib.Path(__file__).parent.parent.parent
-        / "keras_nlp"
-        / "tests"
-        / "test_data"
-        / "albert_sentencepiece.proto",
-        mode="wb",
-    ) as f:
-        f.write(bytes_io.getbuffer())
+    _save(bytes_io, "albert_sentencepiece.proto")
 
     bytes_io = _train_sentencepiece(
         ["abc"],
@@ -58,15 +40,7 @@ def main():
         eos_id=-1,
         bos_id=-1,
     )
-    with open(
-        pathlib.Path(__file__).parent.parent.parent
-        / "keras_nlp"
-        / "tests"
-        / "test_data"
-        / "albert_sentencepiece_bad.proto",
-        mode="wb",
-    ) as f:
-        f.write(bytes_io.getbuffer())
+    _save(bytes_io, "albert_sentencepiece_bad.proto")
 
 
 if __name__ == "__main__":
diff --git a/tools/sentencepiece_testing/create_deberta_v3_test_proto.py b/tools/sentencepiece_testing/create_deberta_v3_test_proto.py
new file mode 100644
index 0000000000..b0317ada10
--- /dev/null
+++ b/tools/sentencepiece_testing/create_deberta_v3_test_proto.py
@@ -0,0 +1,62 @@
+# Copyright 2023 The KerasNLP Authors
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from tools.sentencepiece_testing.utils import _save
+from tools.sentencepiece_testing.utils import _train_sentencepiece
+
+
+def main():
+    bytes_io = _train_sentencepiece(
+        ["the quick brown fox", "the earth is round"],
+        vocab_size=12,
+        model_type="WORD",
+        pad_id=0,
+        bos_id=1,
+        eos_id=2,
+        unk_id=3,
+        pad_piece="[PAD]",
+        bos_piece="[CLS]",
+        eos_piece="[SEP]",
+        unk_piece="[UNK]",
+        user_defined_symbols="[MASK]",
+    )
+    _save(bytes_io, "deberta_v3_sentencepiece.proto")
+
+    bytes_io = _train_sentencepiece(
+        ["the quick brown fox", "the earth is round"],
+        vocab_size=11,
+        model_type="WORD",
+        pad_id=0,
+        bos_id=1,
+        eos_id=2,
+        unk_id=3,
+        pad_piece="[PAD]",
+        bos_piece="[CLS]",
+        eos_piece="[SEP]",
+        unk_piece="[UNK]",
+    )
+    _save(bytes_io, "deberta_v3_tokenizer_sentencepiece.proto")
+
+    bytes_io = _train_sentencepiece(
+        ["abc"],
+        vocab_size=5,
+        pad_id=-1,
+        eos_id=-1,
+        bos_id=-1,
+    )
+    _save(bytes_io, "deberta_v3_sentencepiece_bad.proto")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tools/sentencepiece_testing/utils.py b/tools/sentencepiece_testing/utils.py
new file mode 100644
index 0000000000..e735438656
--- /dev/null
+++ b/tools/sentencepiece_testing/utils.py
@@ -0,0 +1,37 @@
+# Copyright 2023 The KerasNLP Authors
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import io
+import pathlib
+
+import sentencepiece
+
+
+def _train_sentencepiece(data, *args, **kwargs):
+    bytes_io = io.BytesIO()
+    sentencepiece.SentencePieceTrainer.train(
+        sentence_iterator=iter(data), model_writer=bytes_io, *args, **kwargs
+    )
+    return bytes_io
+
+
+def _save(bytes_io, filename):
+    with open(
+        pathlib.Path(__file__).parent.parent.parent
+        / "keras_nlp"
+        / "tests"
+        / "test_data"
+        / filename,
+        mode="wb",
+    ) as f:
+        f.write(bytes_io.getbuffer())

From dba4ac5c26e2721615e4dcb2750741f141b51326 Mon Sep 17 00:00:00 2001
From: Tirth Patel <tirthasheshpatel@gmail.com>
Date: Fri, 20 Oct 2023 21:54:00 +0000
Subject: [PATCH 03/14] Remove SentencePieceTrainer from keras_nlp/models/f_net

---
 .../models/f_net/f_net_classifier_test.py     |  31 ++++-------
 .../f_net_masked_lm_preprocessor_test.py      |  29 ++++------
 .../models/f_net/f_net_masked_lm_test.py      |  31 ++++-------
 .../models/f_net/f_net_preprocessor_test.py   |  29 ++++------
 .../models/f_net/f_net_tokenizer_test.py      |  51 ++++++++----------
 .../tests/test_data/f_net_sentencepiece.proto | Bin 0 -> 237831 bytes
 .../test_data/f_net_sentencepiece_bad.proto   | Bin 0 -> 237677 bytes
 .../create_f_net_test_proto.py                |  47 ++++++++++++++++
 8 files changed, 110 insertions(+), 108 deletions(-)
 create mode 100644 keras_nlp/tests/test_data/f_net_sentencepiece.proto
 create mode 100644 keras_nlp/tests/test_data/f_net_sentencepiece_bad.proto
 create mode 100644 tools/sentencepiece_testing/create_f_net_test_proto.py

diff --git a/keras_nlp/models/f_net/f_net_classifier_test.py b/keras_nlp/models/f_net/f_net_classifier_test.py
index b972f64655..7e3be57dd4 100644
--- a/keras_nlp/models/f_net/f_net_classifier_test.py
+++ b/keras_nlp/models/f_net/f_net_classifier_test.py
@@ -12,10 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import io
+import pathlib
 
 import pytest
-import sentencepiece
 
 from keras_nlp.models.f_net.f_net_backbone import FNetBackbone
 from keras_nlp.models.f_net.f_net_classifier import FNetClassifier
@@ -27,25 +26,17 @@
 class FNetClassifierTest(TestCase):
     def setUp(self):
         # Setup model.
-        vocab_data = ["the quick brown fox", "the earth is round"]
-        bytes_io = io.BytesIO()
-        sentencepiece.SentencePieceTrainer.train(
-            sentence_iterator=iter(vocab_data),
-            model_writer=bytes_io,
-            vocab_size=12,
-            model_type="WORD",
-            pad_id=0,
-            unk_id=1,
-            bos_id=2,
-            eos_id=3,
-            pad_piece="<pad>",
-            unk_piece="<unk>",
-            bos_piece="[CLS]",
-            eos_piece="[SEP]",
-            user_defined_symbols="[MASK]",
-        )
         self.preprocessor = FNetPreprocessor(
-            FNetTokenizer(proto=bytes_io.getvalue()),
+            FNetTokenizer(
+                proto=str(
+                    (
+                        pathlib.Path(__file__).parent.parent.parent
+                        / "tests"
+                        / "test_data"
+                        / "f_net_sentencepiece.proto"
+                    ).absolute()
+                )
+            ),
             sequence_length=5,
         )
         self.backbone = FNetBackbone(
diff --git a/keras_nlp/models/f_net/f_net_masked_lm_preprocessor_test.py b/keras_nlp/models/f_net/f_net_masked_lm_preprocessor_test.py
index eb7036005a..80e8d51704 100644
--- a/keras_nlp/models/f_net/f_net_masked_lm_preprocessor_test.py
+++ b/keras_nlp/models/f_net/f_net_masked_lm_preprocessor_test.py
@@ -12,10 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import io
+import pathlib
 
 import pytest
-import sentencepiece
 
 from keras_nlp.models.f_net.f_net_masked_lm_preprocessor import (
     FNetMaskedLMPreprocessor,
@@ -26,24 +25,16 @@
 
 class FNetMaskedLMPreprocessorTest(TestCase):
     def setUp(self):
-        vocab_data = ["the quick brown fox", "the earth is round"]
-        bytes_io = io.BytesIO()
-        sentencepiece.SentencePieceTrainer.train(
-            sentence_iterator=iter(vocab_data),
-            model_writer=bytes_io,
-            vocab_size=12,
-            model_type="WORD",
-            pad_id=0,
-            unk_id=1,
-            bos_id=2,
-            eos_id=3,
-            pad_piece="<pad>",
-            unk_piece="<unk>",
-            bos_piece="[CLS]",
-            eos_piece="[SEP]",
-            user_defined_symbols="[MASK]",
+        self.tokenizer = FNetTokenizer(
+            proto=str(
+                (
+                    pathlib.Path(__file__).parent.parent.parent
+                    / "tests"
+                    / "test_data"
+                    / "f_net_sentencepiece.proto"
+                ).absolute()
+            )
         )
-        self.tokenizer = FNetTokenizer(proto=bytes_io.getvalue())
         self.init_kwargs = {
             "tokenizer": self.tokenizer,
             # Simplify our testing by masking every available token.
diff --git a/keras_nlp/models/f_net/f_net_masked_lm_test.py b/keras_nlp/models/f_net/f_net_masked_lm_test.py
index dc8bb8e9b3..5ea72ae44b 100644
--- a/keras_nlp/models/f_net/f_net_masked_lm_test.py
+++ b/keras_nlp/models/f_net/f_net_masked_lm_test.py
@@ -12,10 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import io
+import pathlib
 
 import pytest
-import sentencepiece
 
 from keras_nlp.models.f_net.f_net_backbone import FNetBackbone
 from keras_nlp.models.f_net.f_net_masked_lm import FNetMaskedLM
@@ -29,25 +28,17 @@
 class FNetMaskedLMTest(TestCase):
     def setUp(self):
         # Setup model.
-        vocab_data = ["the quick brown fox", "the earth is round"]
-        bytes_io = io.BytesIO()
-        sentencepiece.SentencePieceTrainer.train(
-            sentence_iterator=iter(vocab_data),
-            model_writer=bytes_io,
-            vocab_size=12,
-            model_type="WORD",
-            pad_id=0,
-            unk_id=1,
-            bos_id=2,
-            eos_id=3,
-            pad_piece="<pad>",
-            unk_piece="<unk>",
-            bos_piece="[CLS]",
-            eos_piece="[SEP]",
-            user_defined_symbols="[MASK]",
-        )
         self.preprocessor = FNetMaskedLMPreprocessor(
-            FNetTokenizer(proto=bytes_io.getvalue()),
+            FNetTokenizer(
+                proto=str(
+                    (
+                        pathlib.Path(__file__).parent.parent.parent
+                        / "tests"
+                        / "test_data"
+                        / "f_net_sentencepiece.proto"
+                    ).absolute()
+                )
+            ),
             # Simplify our testing by masking every available token.
             mask_selection_rate=1.0,
             mask_token_rate=1.0,
diff --git a/keras_nlp/models/f_net/f_net_preprocessor_test.py b/keras_nlp/models/f_net/f_net_preprocessor_test.py
index f5470c700d..9625e4474c 100644
--- a/keras_nlp/models/f_net/f_net_preprocessor_test.py
+++ b/keras_nlp/models/f_net/f_net_preprocessor_test.py
@@ -12,10 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import io
+import pathlib
 
 import pytest
-import sentencepiece
 
 from keras_nlp.models.f_net.f_net_preprocessor import FNetPreprocessor
 from keras_nlp.models.f_net.f_net_tokenizer import FNetTokenizer
@@ -24,24 +23,16 @@
 
 class FNetPreprocessorTest(TestCase):
     def setUp(self):
-        vocab_data = ["the quick brown fox", "the earth is round"]
-        bytes_io = io.BytesIO()
-        sentencepiece.SentencePieceTrainer.train(
-            sentence_iterator=iter(vocab_data),
-            model_writer=bytes_io,
-            vocab_size=12,
-            model_type="WORD",
-            pad_id=0,
-            unk_id=1,
-            bos_id=2,
-            eos_id=3,
-            pad_piece="<pad>",
-            unk_piece="<unk>",
-            bos_piece="[CLS]",
-            eos_piece="[SEP]",
-            user_defined_symbols="[MASK]",
+        self.tokenizer = FNetTokenizer(
+            proto=str(
+                (
+                    pathlib.Path(__file__).parent.parent.parent
+                    / "tests"
+                    / "test_data"
+                    / "f_net_sentencepiece.proto"
+                ).absolute()
+            )
         )
-        self.tokenizer = FNetTokenizer(proto=bytes_io.getvalue())
         self.init_kwargs = {
             "tokenizer": self.tokenizer,
             "sequence_length": 8,
diff --git a/keras_nlp/models/f_net/f_net_tokenizer_test.py b/keras_nlp/models/f_net/f_net_tokenizer_test.py
index 80b7f9e037..0a43fd5e40 100644
--- a/keras_nlp/models/f_net/f_net_tokenizer_test.py
+++ b/keras_nlp/models/f_net/f_net_tokenizer_test.py
@@ -12,10 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import io
+import pathlib
 
 import pytest
-import sentencepiece
 
 from keras_nlp.models.f_net.f_net_tokenizer import FNetTokenizer
 from keras_nlp.tests.test_case import TestCase
@@ -23,24 +22,16 @@
 
 class FNetTokenizerTest(TestCase):
     def setUp(self):
-        vocab_data = ["the quick brown fox", "the earth is round"]
-        bytes_io = io.BytesIO()
-        sentencepiece.SentencePieceTrainer.train(
-            sentence_iterator=iter(vocab_data),
-            model_writer=bytes_io,
-            vocab_size=12,
-            model_type="WORD",
-            pad_id=0,
-            unk_id=1,
-            bos_id=2,
-            eos_id=3,
-            pad_piece="<pad>",
-            unk_piece="<unk>",
-            bos_piece="[CLS]",
-            eos_piece="[SEP]",
-            user_defined_symbols="[MASK]",
-        )
-        self.init_kwargs = {"proto": bytes_io.getvalue()}
+        self.init_kwargs = {
+            "proto": str(
+                (
+                    pathlib.Path(__file__).parent.parent.parent
+                    / "tests"
+                    / "test_data"
+                    / "f_net_sentencepiece.proto"
+                ).absolute()
+            )
+        }
         self.input_data = ["the quick brown fox.", "the earth is round."]
 
     def test_tokenizer_basics(self):
@@ -52,17 +43,17 @@ def test_tokenizer_basics(self):
         )
 
     def test_errors_missing_special_tokens(self):
-        bytes_io = io.BytesIO()
-        sentencepiece.SentencePieceTrainer.train(
-            sentence_iterator=iter(["abc"]),
-            model_writer=bytes_io,
-            vocab_size=5,
-            pad_id=-1,
-            eos_id=-1,
-            bos_id=-1,
-        )
         with self.assertRaises(ValueError):
-            FNetTokenizer(proto=bytes_io.getvalue())
+            FNetTokenizer(
+                proto=str(
+                    (
+                        pathlib.Path(__file__).parent.parent.parent
+                        / "tests"
+                        / "test_data"
+                        / "f_net_sentencepiece_bad.proto"
+                    ).absolute()
+                )
+            )
 
     @pytest.mark.large
     def test_smallest_preset(self):
diff --git a/keras_nlp/tests/test_data/f_net_sentencepiece.proto b/keras_nlp/tests/test_data/f_net_sentencepiece.proto
new file mode 100644
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GIT binary patch
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diff --git a/keras_nlp/tests/test_data/f_net_sentencepiece_bad.proto b/keras_nlp/tests/test_data/f_net_sentencepiece_bad.proto
new file mode 100644
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diff --git a/tools/sentencepiece_testing/create_f_net_test_proto.py b/tools/sentencepiece_testing/create_f_net_test_proto.py
new file mode 100644
index 0000000000..7294b19043
--- /dev/null
+++ b/tools/sentencepiece_testing/create_f_net_test_proto.py
@@ -0,0 +1,47 @@
+# Copyright 2023 The KerasNLP Authors
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from tools.sentencepiece_testing.utils import _save
+from tools.sentencepiece_testing.utils import _train_sentencepiece
+
+
+def main():
+    bytes_io = _train_sentencepiece(
+        ["the quick brown fox", "the earth is round"],
+        vocab_size=12,
+        model_type="WORD",
+        pad_id=0,
+        unk_id=1,
+        bos_id=2,
+        eos_id=3,
+        pad_piece="<pad>",
+        unk_piece="<unk>",
+        bos_piece="[CLS]",
+        eos_piece="[SEP]",
+        user_defined_symbols="[MASK]",
+    )
+    _save(bytes_io, "f_net_sentencepiece.proto")
+
+    bytes_io = _train_sentencepiece(
+        ["abc"],
+        vocab_size=5,
+        pad_id=-1,
+        eos_id=-1,
+        bos_id=-1,
+    )
+    _save(bytes_io, "f_net_sentencepiece_bad.proto")
+
+
+if __name__ == "__main__":
+    main()

From e316ff7ebc59fcb190913c3e24c571ca88e601c9 Mon Sep 17 00:00:00 2001
From: Tirth Patel <tirthasheshpatel@gmail.com>
Date: Fri, 20 Oct 2023 22:07:54 +0000
Subject: [PATCH 04/14] Remove SentencePieceTrainer from keras_nlp/models/t5

---
 keras_nlp/models/t5/t5_tokenizer_test.py      |  54 +++++++-----------
 .../tests/test_data/t5_sentencepiece.proto    | Bin 0 -> 237814 bytes
 .../test_data/t5_sentencepiece_bad.proto      | Bin 0 -> 237677 bytes
 .../create_t5_test_proto.py                   |  46 +++++++++++++++
 4 files changed, 67 insertions(+), 33 deletions(-)
 create mode 100644 keras_nlp/tests/test_data/t5_sentencepiece.proto
 create mode 100644 keras_nlp/tests/test_data/t5_sentencepiece_bad.proto
 create mode 100644 tools/sentencepiece_testing/create_t5_test_proto.py

diff --git a/keras_nlp/models/t5/t5_tokenizer_test.py b/keras_nlp/models/t5/t5_tokenizer_test.py
index f8cef35c30..32b3d05860 100644
--- a/keras_nlp/models/t5/t5_tokenizer_test.py
+++ b/keras_nlp/models/t5/t5_tokenizer_test.py
@@ -12,10 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import io
-
-import sentencepiece
-import tensorflow as tf
+import pathlib
 
 from keras_nlp.models.t5.t5_tokenizer import T5Tokenizer
 from keras_nlp.tests.test_case import TestCase
@@ -23,25 +20,16 @@
 
 class T5TokenizerTest(TestCase):
     def setUp(self):
-        bytes_io = io.BytesIO()
-        vocab_data = tf.data.Dataset.from_tensor_slices(
-            ["the quick brown fox", "the earth is round"]
-        )
-        sentencepiece.SentencePieceTrainer.train(
-            sentence_iterator=vocab_data.as_numpy_iterator(),
-            model_writer=bytes_io,
-            vocab_size=11,
-            model_type="WORD",
-            bos_id=-1,
-            pad_id=0,
-            eos_id=1,
-            unk_id=2,
-            pad_piece="<pad>",
-            eos_piece="</s>",
-            unk_piece="<unk>",
-            user_defined_symbols="[MASK]",
-        )
-        self.init_kwargs = {"proto": bytes_io.getvalue()}
+        self.init_kwargs = {
+            "proto": str(
+                (
+                    pathlib.Path(__file__).parent.parent.parent
+                    / "tests"
+                    / "test_data"
+                    / "t5_sentencepiece.proto"
+                )
+            )
+        }
         self.input_data = ["the quick brown fox.", "the earth is round."]
 
     def test_tokenizer_basics(self):
@@ -53,14 +41,14 @@ def test_tokenizer_basics(self):
         )
 
     def test_errors_missing_special_tokens(self):
-        bytes_io = io.BytesIO()
-        sentencepiece.SentencePieceTrainer.train(
-            sentence_iterator=iter(["abc"]),
-            model_writer=bytes_io,
-            vocab_size=5,
-            pad_id=-1,
-            eos_id=-1,
-            bos_id=-1,
-        )
         with self.assertRaises(ValueError):
-            T5Tokenizer(proto=bytes_io.getvalue())
+            T5Tokenizer(
+                proto=str(
+                    (
+                        pathlib.Path(__file__).parent.parent.parent
+                        / "tests"
+                        / "test_data"
+                        / "t5_sentencepiece_bad.proto"
+                    )
+                )
+            )
diff --git a/keras_nlp/tests/test_data/t5_sentencepiece.proto b/keras_nlp/tests/test_data/t5_sentencepiece.proto
new file mode 100644
index 0000000000000000000000000000000000000000..ce7ecf0c49af113fd3fc85c354d8f485e52286dd
GIT binary patch
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diff --git a/keras_nlp/tests/test_data/t5_sentencepiece_bad.proto b/keras_nlp/tests/test_data/t5_sentencepiece_bad.proto
new file mode 100644
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diff --git a/tools/sentencepiece_testing/create_t5_test_proto.py b/tools/sentencepiece_testing/create_t5_test_proto.py
new file mode 100644
index 0000000000..a51b7c6048
--- /dev/null
+++ b/tools/sentencepiece_testing/create_t5_test_proto.py
@@ -0,0 +1,46 @@
+# Copyright 2023 The KerasNLP Authors
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from tools.sentencepiece_testing.utils import _save
+from tools.sentencepiece_testing.utils import _train_sentencepiece
+
+
+def main():
+    bytes_io = _train_sentencepiece(
+        ["the quick brown fox", "the earth is round"],
+        vocab_size=11,
+        model_type="WORD",
+        bos_id=-1,
+        pad_id=0,
+        eos_id=1,
+        unk_id=2,
+        pad_piece="<pad>",
+        eos_piece="</s>",
+        unk_piece="<unk>",
+        user_defined_symbols="[MASK]",
+    )
+    _save(bytes_io, "t5_sentencepiece.proto")
+
+    bytes_io = _train_sentencepiece(
+        ["abc"],
+        vocab_size=5,
+        pad_id=-1,
+        eos_id=-1,
+        bos_id=-1,
+    )
+    _save(bytes_io, "t5_sentencepiece_bad.proto")
+
+
+if __name__ == "__main__":
+    main()

From 89936726cc84f4339324c1849a6151eadaf1fa00 Mon Sep 17 00:00:00 2001
From: Tirth Patel <tirthasheshpatel@gmail.com>
Date: Fri, 20 Oct 2023 22:39:04 +0000
Subject: [PATCH 05/14] Remove SentencePieceTrainer from
 keras_nlp/models/xlm_roberta

---
 .../xlm_roberta_classifier_test.py            |  25 +++++-----
 ...xlm_roberta_masked_lm_preprocessor_test.py |  24 ++++------
 .../xlm_roberta/xlm_roberta_masked_lm_test.py |  26 +++++------
 .../xlm_roberta/xlm_roberta_tokenizer_test.py |  26 +++++------
 ...xlm_roberta_classifier_sentencepiece.proto | Bin 0 -> 237751 bytes
 .../test_data/xlm_roberta_sentencepiece.proto | Bin 0 -> 237777 bytes
 .../create_xlm_roberta_test_proto.py          |  43 ++++++++++++++++++
 7 files changed, 86 insertions(+), 58 deletions(-)
 create mode 100644 keras_nlp/tests/test_data/xlm_roberta_classifier_sentencepiece.proto
 create mode 100644 keras_nlp/tests/test_data/xlm_roberta_sentencepiece.proto
 create mode 100644 tools/sentencepiece_testing/create_xlm_roberta_test_proto.py

diff --git a/keras_nlp/models/xlm_roberta/xlm_roberta_classifier_test.py b/keras_nlp/models/xlm_roberta/xlm_roberta_classifier_test.py
index c123cc6bc0..f578afdd4d 100644
--- a/keras_nlp/models/xlm_roberta/xlm_roberta_classifier_test.py
+++ b/keras_nlp/models/xlm_roberta/xlm_roberta_classifier_test.py
@@ -12,10 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import io
+import pathlib
 
 import pytest
-import sentencepiece
 
 from keras_nlp.models.xlm_roberta.xlm_roberta_backbone import XLMRobertaBackbone
 from keras_nlp.models.xlm_roberta.xlm_roberta_classifier import (
@@ -33,19 +32,17 @@
 class XLMRobertaClassifierTest(TestCase):
     def setUp(self):
         # Setup model.
-        vocab_data = ["the quick brown fox", "the earth is round"]
-        bytes_io = io.BytesIO()
-        sentencepiece.SentencePieceTrainer.train(
-            sentence_iterator=iter(vocab_data),
-            model_writer=bytes_io,
-            vocab_size=10,
-            model_type="WORD",
-            unk_id=0,
-            bos_id=1,
-            eos_id=2,
-        )
         self.preprocessor = XLMRobertaPreprocessor(
-            XLMRobertaTokenizer(proto=bytes_io.getvalue()),
+            XLMRobertaTokenizer(
+                proto=str(
+                    (
+                        pathlib.Path(__file__).parent.parent.parent
+                        / "tests"
+                        / "test_data"
+                        / "xlm_roberta_classifier_sentencepiece.proto"
+                    ).absolute()
+                )
+            ),
             sequence_length=5,
         )
         self.backbone = XLMRobertaBackbone(
diff --git a/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_preprocessor_test.py b/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_preprocessor_test.py
index 6dd0bc0f71..09e9e3f531 100644
--- a/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_preprocessor_test.py
+++ b/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_preprocessor_test.py
@@ -12,10 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import io
+import pathlib
 
 import pytest
-import sentencepiece
 
 from keras_nlp.models.xlm_roberta.xlm_roberta_masked_lm_preprocessor import (
     XLMRobertaMaskedLMPreprocessor,
@@ -28,19 +27,16 @@
 
 class XLMRobertaMaskedLMPreprocessorTest(TestCase):
     def setUp(self):
-        vocab_data = ["the quick brown fox", "the earth is round"]
-        bytes_io = io.BytesIO()
-        sentencepiece.SentencePieceTrainer.train(
-            sentence_iterator=iter(vocab_data),
-            model_writer=bytes_io,
-            vocab_size=11,
-            model_type="WORD",
-            unk_id=0,
-            bos_id=1,
-            eos_id=2,
-            user_defined_symbols="[MASK]",
+        self.tokenizer = XLMRobertaTokenizer(
+            proto=str(
+                (
+                    pathlib.Path(__file__).parent.parent.parent
+                    / "tests"
+                    / "test_data"
+                    / "xlm_roberta_sentencepiece.proto"
+                ).absolute()
+            )
         )
-        self.tokenizer = XLMRobertaTokenizer(proto=bytes_io.getvalue())
         self.init_kwargs = {
             "tokenizer": self.tokenizer,
             # Simplify our testing by masking every available token.
diff --git a/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_test.py b/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_test.py
index 81fafbe4dc..cb0089e47a 100644
--- a/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_test.py
+++ b/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_test.py
@@ -12,10 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import io
+import pathlib
 
 import pytest
-import sentencepiece
 
 from keras_nlp.models.xlm_roberta.xlm_roberta_backbone import XLMRobertaBackbone
 from keras_nlp.models.xlm_roberta.xlm_roberta_masked_lm import (
@@ -33,20 +32,17 @@
 class XLMRobertaMaskedLMTest(TestCase):
     def setUp(self):
         # Setup model.
-        vocab_data = ["the quick brown fox", "the earth is round"]
-        bytes_io = io.BytesIO()
-        sentencepiece.SentencePieceTrainer.train(
-            sentence_iterator=iter(vocab_data),
-            model_writer=bytes_io,
-            vocab_size=11,
-            model_type="WORD",
-            unk_id=0,
-            bos_id=1,
-            eos_id=2,
-            user_defined_symbols="[MASK]",
-        )
         self.preprocessor = XLMRobertaMaskedLMPreprocessor(
-            XLMRobertaTokenizer(proto=bytes_io.getvalue()),
+            XLMRobertaTokenizer(
+                proto=str(
+                    (
+                        pathlib.Path(__file__).parent.parent.parent
+                        / "tests"
+                        / "test_data"
+                        / "xlm_roberta_sentencepiece.proto"
+                    ).absolute()
+                )
+            ),
             # Simplify our testing by masking every available token.
             mask_selection_rate=1.0,
             mask_token_rate=1.0,
diff --git a/keras_nlp/models/xlm_roberta/xlm_roberta_tokenizer_test.py b/keras_nlp/models/xlm_roberta/xlm_roberta_tokenizer_test.py
index a58ee4c74b..6ccdbd3788 100644
--- a/keras_nlp/models/xlm_roberta/xlm_roberta_tokenizer_test.py
+++ b/keras_nlp/models/xlm_roberta/xlm_roberta_tokenizer_test.py
@@ -12,10 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import io
+import pathlib
 
 import pytest
-import sentencepiece
 
 from keras_nlp.models.xlm_roberta.xlm_roberta_tokenizer import (
     XLMRobertaTokenizer,
@@ -25,19 +24,16 @@
 
 class XLMRobertaTokenizerTest(TestCase):
     def setUp(self):
-        vocab_data = ["the quick brown fox", "the earth is round"]
-        bytes_io = io.BytesIO()
-        sentencepiece.SentencePieceTrainer.train(
-            sentence_iterator=iter(vocab_data),
-            model_writer=bytes_io,
-            vocab_size=11,
-            model_type="WORD",
-            unk_id=0,
-            bos_id=1,
-            eos_id=2,
-            user_defined_symbols="[MASK]",
-        )
-        self.init_kwargs = {"proto": bytes_io.getvalue()}
+        self.init_kwargs = {
+            "proto": str(
+                (
+                    pathlib.Path(__file__).parent.parent.parent
+                    / "tests"
+                    / "test_data"
+                    / "xlm_roberta_sentencepiece.proto"
+                ).absolute()
+            )
+        }
         self.input_data = ["the quick brown fox.", "the earth is round."]
 
     def test_tokenizer_basics(self):
diff --git a/keras_nlp/tests/test_data/xlm_roberta_classifier_sentencepiece.proto b/keras_nlp/tests/test_data/xlm_roberta_classifier_sentencepiece.proto
new file mode 100644
index 0000000000000000000000000000000000000000..893aedad07cee3216d5ee6fe6044fc6525eb1a98
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diff --git a/keras_nlp/tests/test_data/xlm_roberta_sentencepiece.proto b/keras_nlp/tests/test_data/xlm_roberta_sentencepiece.proto
new file mode 100644
index 0000000000000000000000000000000000000000..fd8e4cdd9884e41e2fdbf579373fe4051ab8bb2f
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diff --git a/tools/sentencepiece_testing/create_xlm_roberta_test_proto.py b/tools/sentencepiece_testing/create_xlm_roberta_test_proto.py
new file mode 100644
index 0000000000..5fd5eb74c3
--- /dev/null
+++ b/tools/sentencepiece_testing/create_xlm_roberta_test_proto.py
@@ -0,0 +1,43 @@
+# Copyright 2023 The KerasNLP Authors
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from tools.sentencepiece_testing.utils import _save
+from tools.sentencepiece_testing.utils import _train_sentencepiece
+
+
+def main():
+    bytes_io = _train_sentencepiece(
+        ["the quick brown fox", "the earth is round"],
+        vocab_size=10,
+        model_type="WORD",
+        unk_id=0,
+        bos_id=1,
+        eos_id=2,
+    )
+    _save(bytes_io, "xlm_roberta_classifier_sentencepiece.proto")
+
+    bytes_io = _train_sentencepiece(
+        ["the quick brown fox", "the earth is round"],
+        vocab_size=11,
+        model_type="WORD",
+        unk_id=0,
+        bos_id=1,
+        eos_id=2,
+        user_defined_symbols="[MASK]",
+    )
+    _save(bytes_io, "xlm_roberta_sentencepiece.proto")
+
+
+if __name__ == "__main__":
+    main()

From 5e6c26c4b2558aff4493a65e4df634ee1e91415d Mon Sep 17 00:00:00 2001
From: Tirth Patel <tirthasheshpatel@gmail.com>
Date: Fri, 20 Oct 2023 22:42:24 +0000
Subject: [PATCH 06/14] Remove the .absolute() calls

---
 .../models/albert/albert_classifier_test.py   | 10 ++++------
 .../albert_masked_lm_preprocessor_test.py     | 10 ++++------
 .../models/albert/albert_masked_lm_test.py    | 10 ++++------
 .../models/albert/albert_preprocessor_test.py | 10 ++++------
 .../models/albert/albert_tokenizer_test.py    | 20 ++++++++-----------
 .../deberta_v3/deberta_v3_classifier_test.py  | 10 ++++------
 .../deberta_v3_masked_lm_preprocessor_test.py | 10 ++++------
 .../deberta_v3/deberta_v3_masked_lm_test.py   | 10 ++++------
 .../deberta_v3_preprocessor_test.py           | 10 ++++------
 .../deberta_v3/deberta_v3_tokenizer_test.py   | 20 ++++++++-----------
 .../models/f_net/f_net_classifier_test.py     | 10 ++++------
 .../f_net_masked_lm_preprocessor_test.py      | 10 ++++------
 .../models/f_net/f_net_masked_lm_test.py      | 10 ++++------
 .../models/f_net/f_net_preprocessor_test.py   | 10 ++++------
 .../models/f_net/f_net_tokenizer_test.py      | 20 ++++++++-----------
 .../xlm_roberta_classifier_test.py            | 10 ++++------
 ...xlm_roberta_masked_lm_preprocessor_test.py | 10 ++++------
 .../xlm_roberta/xlm_roberta_masked_lm_test.py | 10 ++++------
 .../xlm_roberta/xlm_roberta_tokenizer_test.py | 10 ++++------
 19 files changed, 88 insertions(+), 132 deletions(-)

diff --git a/keras_nlp/models/albert/albert_classifier_test.py b/keras_nlp/models/albert/albert_classifier_test.py
index 4fe1fc1761..7cd105eb72 100644
--- a/keras_nlp/models/albert/albert_classifier_test.py
+++ b/keras_nlp/models/albert/albert_classifier_test.py
@@ -29,12 +29,10 @@ def setUp(self):
         self.preprocessor = AlbertPreprocessor(
             AlbertTokenizer(
                 proto=str(
-                    (
-                        pathlib.Path(__file__).parent.parent.parent
-                        / "tests"
-                        / "test_data"
-                        / "albert_sentencepiece.proto"
-                    ).absolute()
+                    pathlib.Path(__file__).parent.parent.parent
+                    / "tests"
+                    / "test_data"
+                    / "albert_sentencepiece.proto"
                 ),
                 sequence_length=5,
             )
diff --git a/keras_nlp/models/albert/albert_masked_lm_preprocessor_test.py b/keras_nlp/models/albert/albert_masked_lm_preprocessor_test.py
index c993abf3e9..9b52a91f06 100644
--- a/keras_nlp/models/albert/albert_masked_lm_preprocessor_test.py
+++ b/keras_nlp/models/albert/albert_masked_lm_preprocessor_test.py
@@ -27,12 +27,10 @@ class AlbertMaskedLMPreprocessorTest(TestCase):
     def setUp(self):
         self.tokenizer = AlbertTokenizer(
             proto=str(
-                (
-                    pathlib.Path(__file__).parent.parent.parent
-                    / "tests"
-                    / "test_data"
-                    / "albert_sentencepiece.proto"
-                ).absolute()
+                pathlib.Path(__file__).parent.parent.parent
+                / "tests"
+                / "test_data"
+                / "albert_sentencepiece.proto"
             )
         )
         self.init_kwargs = {
diff --git a/keras_nlp/models/albert/albert_masked_lm_test.py b/keras_nlp/models/albert/albert_masked_lm_test.py
index 8273fc9581..9e0bd1f22e 100644
--- a/keras_nlp/models/albert/albert_masked_lm_test.py
+++ b/keras_nlp/models/albert/albert_masked_lm_test.py
@@ -31,12 +31,10 @@ def setUp(self):
         self.preprocessor = AlbertMaskedLMPreprocessor(
             AlbertTokenizer(
                 proto=str(
-                    (
-                        pathlib.Path(__file__).parent.parent.parent
-                        / "tests"
-                        / "test_data"
-                        / "albert_sentencepiece.proto"
-                    ).absolute()
+                    pathlib.Path(__file__).parent.parent.parent
+                    / "tests"
+                    / "test_data"
+                    / "albert_sentencepiece.proto"
                 ),
                 sequence_length=5,
             ),
diff --git a/keras_nlp/models/albert/albert_preprocessor_test.py b/keras_nlp/models/albert/albert_preprocessor_test.py
index 07c49dd59c..2b3983f89f 100644
--- a/keras_nlp/models/albert/albert_preprocessor_test.py
+++ b/keras_nlp/models/albert/albert_preprocessor_test.py
@@ -25,12 +25,10 @@ class AlbertPreprocessorTest(TestCase):
     def setUp(self):
         self.tokenizer = AlbertTokenizer(
             proto=str(
-                (
-                    pathlib.Path(__file__).parent.parent.parent
-                    / "tests"
-                    / "test_data"
-                    / "albert_sentencepiece.proto"
-                ).absolute()
+                pathlib.Path(__file__).parent.parent.parent
+                / "tests"
+                / "test_data"
+                / "albert_sentencepiece.proto"
             )
         )
         self.init_kwargs = {
diff --git a/keras_nlp/models/albert/albert_tokenizer_test.py b/keras_nlp/models/albert/albert_tokenizer_test.py
index ee47225f1e..d5bd15f135 100644
--- a/keras_nlp/models/albert/albert_tokenizer_test.py
+++ b/keras_nlp/models/albert/albert_tokenizer_test.py
@@ -24,12 +24,10 @@ class AlbertTokenizerTest(TestCase):
     def setUp(self):
         self.init_kwargs = {
             "proto": str(
-                (
-                    pathlib.Path(__file__).parent.parent.parent
-                    / "tests"
-                    / "test_data"
-                    / "albert_sentencepiece.proto"
-                ).absolute()
+                pathlib.Path(__file__).parent.parent.parent
+                / "tests"
+                / "test_data"
+                / "albert_sentencepiece.proto"
             )
         }
         self.input_data = ["the quick brown fox.", "the earth is round."]
@@ -46,12 +44,10 @@ def test_errors_missing_special_tokens(self):
         with self.assertRaises(ValueError):
             AlbertTokenizer(
                 proto=str(
-                    (
-                        pathlib.Path(__file__).parent.parent.parent
-                        / "tests"
-                        / "test_data"
-                        / "albert_sentencepiece_bad.proto"
-                    ).absolute()
+                    pathlib.Path(__file__).parent.parent.parent
+                    / "tests"
+                    / "test_data"
+                    / "albert_sentencepiece_bad.proto"
                 )
             )
 
diff --git a/keras_nlp/models/deberta_v3/deberta_v3_classifier_test.py b/keras_nlp/models/deberta_v3/deberta_v3_classifier_test.py
index cd6d8f3d6e..167f84da6e 100644
--- a/keras_nlp/models/deberta_v3/deberta_v3_classifier_test.py
+++ b/keras_nlp/models/deberta_v3/deberta_v3_classifier_test.py
@@ -33,12 +33,10 @@ def setUp(self):
         self.preprocessor = DebertaV3Preprocessor(
             DebertaV3Tokenizer(
                 proto=str(
-                    (
-                        pathlib.Path(__file__).parent.parent.parent
-                        / "tests"
-                        / "test_data"
-                        / "deberta_v3_sentencepiece.proto"
-                    ).absolute()
+                    pathlib.Path(__file__).parent.parent.parent
+                    / "tests"
+                    / "test_data"
+                    / "deberta_v3_sentencepiece.proto"
                 )
             ),
             sequence_length=5,
diff --git a/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_preprocessor_test.py b/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_preprocessor_test.py
index 4b7d490b66..4b7439d1ba 100644
--- a/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_preprocessor_test.py
+++ b/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_preprocessor_test.py
@@ -27,12 +27,10 @@ class DebertaV3MaskedLMPreprocessorTest(TestCase):
     def setUp(self):
         self.tokenizer = DebertaV3Tokenizer(
             proto=str(
-                (
-                    pathlib.Path(__file__).parent.parent.parent
-                    / "tests"
-                    / "test_data"
-                    / "deberta_v3_sentencepiece.proto"
-                ).absolute()
+                pathlib.Path(__file__).parent.parent.parent
+                / "tests"
+                / "test_data"
+                / "deberta_v3_sentencepiece.proto"
             )
         )
         self.init_kwargs = {
diff --git a/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_test.py b/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_test.py
index c93049ec2d..09dc92ae5d 100644
--- a/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_test.py
+++ b/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_test.py
@@ -31,12 +31,10 @@ def setUp(self):
         self.preprocessor = DebertaV3MaskedLMPreprocessor(
             DebertaV3Tokenizer(
                 proto=str(
-                    (
-                        pathlib.Path(__file__).parent.parent.parent
-                        / "tests"
-                        / "test_data"
-                        / "deberta_v3_sentencepiece.proto"
-                    ).absolute()
+                    pathlib.Path(__file__).parent.parent.parent
+                    / "tests"
+                    / "test_data"
+                    / "deberta_v3_sentencepiece.proto"
                 )
             ),
             # Simplify our testing by masking every available token.
diff --git a/keras_nlp/models/deberta_v3/deberta_v3_preprocessor_test.py b/keras_nlp/models/deberta_v3/deberta_v3_preprocessor_test.py
index 920c6cbe26..c6719c96d1 100644
--- a/keras_nlp/models/deberta_v3/deberta_v3_preprocessor_test.py
+++ b/keras_nlp/models/deberta_v3/deberta_v3_preprocessor_test.py
@@ -27,12 +27,10 @@ class DebertaV3PreprocessorTest(TestCase):
     def setUp(self):
         self.tokenizer = DebertaV3Tokenizer(
             proto=str(
-                (
-                    pathlib.Path(__file__).parent.parent.parent
-                    / "tests"
-                    / "test_data"
-                    / "deberta_v3_sentencepiece.proto"
-                ).absolute()
+                pathlib.Path(__file__).parent.parent.parent
+                / "tests"
+                / "test_data"
+                / "deberta_v3_sentencepiece.proto"
             )
         )
         self.init_kwargs = {
diff --git a/keras_nlp/models/deberta_v3/deberta_v3_tokenizer_test.py b/keras_nlp/models/deberta_v3/deberta_v3_tokenizer_test.py
index 2123971f62..342492a5a8 100644
--- a/keras_nlp/models/deberta_v3/deberta_v3_tokenizer_test.py
+++ b/keras_nlp/models/deberta_v3/deberta_v3_tokenizer_test.py
@@ -23,12 +23,10 @@
 class DebertaV3TokenizerTest(TestCase):
     def setUp(self):
         proto = str(
-            (
-                pathlib.Path(__file__).parent.parent.parent
-                / "tests"
-                / "test_data"
-                / "deberta_v3_tokenizer_sentencepiece.proto"
-            ).absolute()
+            pathlib.Path(__file__).parent.parent.parent
+            / "tests"
+            / "test_data"
+            / "deberta_v3_tokenizer_sentencepiece.proto"
         )
         self.tokenizer = DebertaV3Tokenizer(proto=proto)
         self.init_kwargs = {"proto": proto}
@@ -46,12 +44,10 @@ def test_errors_missing_special_tokens(self):
         with self.assertRaises(ValueError):
             DebertaV3Tokenizer(
                 proto=str(
-                    (
-                        pathlib.Path(__file__).parent.parent.parent
-                        / "tests"
-                        / "test_data"
-                        / "deberta_v3_sentencepiece_bad.proto"
-                    ).absolute()
+                    pathlib.Path(__file__).parent.parent.parent
+                    / "tests"
+                    / "test_data"
+                    / "deberta_v3_sentencepiece_bad.proto"
                 )
             )
 
diff --git a/keras_nlp/models/f_net/f_net_classifier_test.py b/keras_nlp/models/f_net/f_net_classifier_test.py
index 7e3be57dd4..50e3d5abe4 100644
--- a/keras_nlp/models/f_net/f_net_classifier_test.py
+++ b/keras_nlp/models/f_net/f_net_classifier_test.py
@@ -29,12 +29,10 @@ def setUp(self):
         self.preprocessor = FNetPreprocessor(
             FNetTokenizer(
                 proto=str(
-                    (
-                        pathlib.Path(__file__).parent.parent.parent
-                        / "tests"
-                        / "test_data"
-                        / "f_net_sentencepiece.proto"
-                    ).absolute()
+                    pathlib.Path(__file__).parent.parent.parent
+                    / "tests"
+                    / "test_data"
+                    / "f_net_sentencepiece.proto"
                 )
             ),
             sequence_length=5,
diff --git a/keras_nlp/models/f_net/f_net_masked_lm_preprocessor_test.py b/keras_nlp/models/f_net/f_net_masked_lm_preprocessor_test.py
index 80e8d51704..9e816f369d 100644
--- a/keras_nlp/models/f_net/f_net_masked_lm_preprocessor_test.py
+++ b/keras_nlp/models/f_net/f_net_masked_lm_preprocessor_test.py
@@ -27,12 +27,10 @@ class FNetMaskedLMPreprocessorTest(TestCase):
     def setUp(self):
         self.tokenizer = FNetTokenizer(
             proto=str(
-                (
-                    pathlib.Path(__file__).parent.parent.parent
-                    / "tests"
-                    / "test_data"
-                    / "f_net_sentencepiece.proto"
-                ).absolute()
+                pathlib.Path(__file__).parent.parent.parent
+                / "tests"
+                / "test_data"
+                / "f_net_sentencepiece.proto"
             )
         )
         self.init_kwargs = {
diff --git a/keras_nlp/models/f_net/f_net_masked_lm_test.py b/keras_nlp/models/f_net/f_net_masked_lm_test.py
index 5ea72ae44b..4992b65d47 100644
--- a/keras_nlp/models/f_net/f_net_masked_lm_test.py
+++ b/keras_nlp/models/f_net/f_net_masked_lm_test.py
@@ -31,12 +31,10 @@ def setUp(self):
         self.preprocessor = FNetMaskedLMPreprocessor(
             FNetTokenizer(
                 proto=str(
-                    (
-                        pathlib.Path(__file__).parent.parent.parent
-                        / "tests"
-                        / "test_data"
-                        / "f_net_sentencepiece.proto"
-                    ).absolute()
+                    pathlib.Path(__file__).parent.parent.parent
+                    / "tests"
+                    / "test_data"
+                    / "f_net_sentencepiece.proto"
                 )
             ),
             # Simplify our testing by masking every available token.
diff --git a/keras_nlp/models/f_net/f_net_preprocessor_test.py b/keras_nlp/models/f_net/f_net_preprocessor_test.py
index 9625e4474c..7e5aee579e 100644
--- a/keras_nlp/models/f_net/f_net_preprocessor_test.py
+++ b/keras_nlp/models/f_net/f_net_preprocessor_test.py
@@ -25,12 +25,10 @@ class FNetPreprocessorTest(TestCase):
     def setUp(self):
         self.tokenizer = FNetTokenizer(
             proto=str(
-                (
-                    pathlib.Path(__file__).parent.parent.parent
-                    / "tests"
-                    / "test_data"
-                    / "f_net_sentencepiece.proto"
-                ).absolute()
+                pathlib.Path(__file__).parent.parent.parent
+                / "tests"
+                / "test_data"
+                / "f_net_sentencepiece.proto"
             )
         )
         self.init_kwargs = {
diff --git a/keras_nlp/models/f_net/f_net_tokenizer_test.py b/keras_nlp/models/f_net/f_net_tokenizer_test.py
index 0a43fd5e40..327b8bd2ee 100644
--- a/keras_nlp/models/f_net/f_net_tokenizer_test.py
+++ b/keras_nlp/models/f_net/f_net_tokenizer_test.py
@@ -24,12 +24,10 @@ class FNetTokenizerTest(TestCase):
     def setUp(self):
         self.init_kwargs = {
             "proto": str(
-                (
-                    pathlib.Path(__file__).parent.parent.parent
-                    / "tests"
-                    / "test_data"
-                    / "f_net_sentencepiece.proto"
-                ).absolute()
+                pathlib.Path(__file__).parent.parent.parent
+                / "tests"
+                / "test_data"
+                / "f_net_sentencepiece.proto"
             )
         }
         self.input_data = ["the quick brown fox.", "the earth is round."]
@@ -46,12 +44,10 @@ def test_errors_missing_special_tokens(self):
         with self.assertRaises(ValueError):
             FNetTokenizer(
                 proto=str(
-                    (
-                        pathlib.Path(__file__).parent.parent.parent
-                        / "tests"
-                        / "test_data"
-                        / "f_net_sentencepiece_bad.proto"
-                    ).absolute()
+                    pathlib.Path(__file__).parent.parent.parent
+                    / "tests"
+                    / "test_data"
+                    / "f_net_sentencepiece_bad.proto"
                 )
             )
 
diff --git a/keras_nlp/models/xlm_roberta/xlm_roberta_classifier_test.py b/keras_nlp/models/xlm_roberta/xlm_roberta_classifier_test.py
index f578afdd4d..3eab55c4c1 100644
--- a/keras_nlp/models/xlm_roberta/xlm_roberta_classifier_test.py
+++ b/keras_nlp/models/xlm_roberta/xlm_roberta_classifier_test.py
@@ -35,12 +35,10 @@ def setUp(self):
         self.preprocessor = XLMRobertaPreprocessor(
             XLMRobertaTokenizer(
                 proto=str(
-                    (
-                        pathlib.Path(__file__).parent.parent.parent
-                        / "tests"
-                        / "test_data"
-                        / "xlm_roberta_classifier_sentencepiece.proto"
-                    ).absolute()
+                    pathlib.Path(__file__).parent.parent.parent
+                    / "tests"
+                    / "test_data"
+                    / "xlm_roberta_classifier_sentencepiece.proto"
                 )
             ),
             sequence_length=5,
diff --git a/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_preprocessor_test.py b/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_preprocessor_test.py
index 09e9e3f531..b1db15620b 100644
--- a/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_preprocessor_test.py
+++ b/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_preprocessor_test.py
@@ -29,12 +29,10 @@ class XLMRobertaMaskedLMPreprocessorTest(TestCase):
     def setUp(self):
         self.tokenizer = XLMRobertaTokenizer(
             proto=str(
-                (
-                    pathlib.Path(__file__).parent.parent.parent
-                    / "tests"
-                    / "test_data"
-                    / "xlm_roberta_sentencepiece.proto"
-                ).absolute()
+                pathlib.Path(__file__).parent.parent.parent
+                / "tests"
+                / "test_data"
+                / "xlm_roberta_sentencepiece.proto"
             )
         )
         self.init_kwargs = {
diff --git a/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_test.py b/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_test.py
index cb0089e47a..b694fe0fb4 100644
--- a/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_test.py
+++ b/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_test.py
@@ -35,12 +35,10 @@ def setUp(self):
         self.preprocessor = XLMRobertaMaskedLMPreprocessor(
             XLMRobertaTokenizer(
                 proto=str(
-                    (
-                        pathlib.Path(__file__).parent.parent.parent
-                        / "tests"
-                        / "test_data"
-                        / "xlm_roberta_sentencepiece.proto"
-                    ).absolute()
+                    pathlib.Path(__file__).parent.parent.parent
+                    / "tests"
+                    / "test_data"
+                    / "xlm_roberta_sentencepiece.proto"
                 )
             ),
             # Simplify our testing by masking every available token.
diff --git a/keras_nlp/models/xlm_roberta/xlm_roberta_tokenizer_test.py b/keras_nlp/models/xlm_roberta/xlm_roberta_tokenizer_test.py
index 6ccdbd3788..a85543355d 100644
--- a/keras_nlp/models/xlm_roberta/xlm_roberta_tokenizer_test.py
+++ b/keras_nlp/models/xlm_roberta/xlm_roberta_tokenizer_test.py
@@ -26,12 +26,10 @@ class XLMRobertaTokenizerTest(TestCase):
     def setUp(self):
         self.init_kwargs = {
             "proto": str(
-                (
-                    pathlib.Path(__file__).parent.parent.parent
-                    / "tests"
-                    / "test_data"
-                    / "xlm_roberta_sentencepiece.proto"
-                ).absolute()
+                pathlib.Path(__file__).parent.parent.parent
+                / "tests"
+                / "test_data"
+                / "xlm_roberta_sentencepiece.proto"
             )
         }
         self.input_data = ["the quick brown fox.", "the earth is round."]

From 4aa6347d01676ed1f5dcc0e8f49183ec745fd8a2 Mon Sep 17 00:00:00 2001
From: Tirth Patel <tirthasheshpatel@gmail.com>
Date: Fri, 20 Oct 2023 22:52:29 +0000
Subject: [PATCH 07/14] Make the bad sentencepiece proto common between all the
 tests

---
 .../models/albert/albert_tokenizer_test.py    |   2 +-
 .../deberta_v3/deberta_v3_tokenizer_test.py   |   2 +-
 .../models/f_net/f_net_tokenizer_test.py      |   2 +-
 keras_nlp/models/t5/t5_tokenizer_test.py      |   2 +-
 .../deberta_v3_sentencepiece_bad.proto        | Bin 237677 -> 0 bytes
 .../test_data/f_net_sentencepiece_bad.proto   | Bin 237677 -> 0 bytes
 ...iece_bad.proto => sentencepiece_bad.proto} | Bin
 .../test_data/t5_sentencepiece_bad.proto      | Bin 237677 -> 0 bytes
 .../create_albert_test_proto.py               |   9 -----
 .../sentencepiece_testing/create_bad_proto.py |  31 ++++++++++++++++++
 .../create_deberta_v3_test_proto.py           |   9 -----
 .../create_f_net_test_proto.py                |   9 -----
 .../create_t5_test_proto.py                   |   9 -----
 13 files changed, 35 insertions(+), 40 deletions(-)
 delete mode 100644 keras_nlp/tests/test_data/deberta_v3_sentencepiece_bad.proto
 delete mode 100644 keras_nlp/tests/test_data/f_net_sentencepiece_bad.proto
 rename keras_nlp/tests/test_data/{albert_sentencepiece_bad.proto => sentencepiece_bad.proto} (100%)
 delete mode 100644 keras_nlp/tests/test_data/t5_sentencepiece_bad.proto
 create mode 100644 tools/sentencepiece_testing/create_bad_proto.py

diff --git a/keras_nlp/models/albert/albert_tokenizer_test.py b/keras_nlp/models/albert/albert_tokenizer_test.py
index d5bd15f135..f3b1ed7b4d 100644
--- a/keras_nlp/models/albert/albert_tokenizer_test.py
+++ b/keras_nlp/models/albert/albert_tokenizer_test.py
@@ -47,7 +47,7 @@ def test_errors_missing_special_tokens(self):
                     pathlib.Path(__file__).parent.parent.parent
                     / "tests"
                     / "test_data"
-                    / "albert_sentencepiece_bad.proto"
+                    / "sentencepiece_bad.proto"
                 )
             )
 
diff --git a/keras_nlp/models/deberta_v3/deberta_v3_tokenizer_test.py b/keras_nlp/models/deberta_v3/deberta_v3_tokenizer_test.py
index 342492a5a8..0e1545a4ef 100644
--- a/keras_nlp/models/deberta_v3/deberta_v3_tokenizer_test.py
+++ b/keras_nlp/models/deberta_v3/deberta_v3_tokenizer_test.py
@@ -47,7 +47,7 @@ def test_errors_missing_special_tokens(self):
                     pathlib.Path(__file__).parent.parent.parent
                     / "tests"
                     / "test_data"
-                    / "deberta_v3_sentencepiece_bad.proto"
+                    / "sentencepiece_bad.proto"
                 )
             )
 
diff --git a/keras_nlp/models/f_net/f_net_tokenizer_test.py b/keras_nlp/models/f_net/f_net_tokenizer_test.py
index 327b8bd2ee..9b8f5388da 100644
--- a/keras_nlp/models/f_net/f_net_tokenizer_test.py
+++ b/keras_nlp/models/f_net/f_net_tokenizer_test.py
@@ -47,7 +47,7 @@ def test_errors_missing_special_tokens(self):
                     pathlib.Path(__file__).parent.parent.parent
                     / "tests"
                     / "test_data"
-                    / "f_net_sentencepiece_bad.proto"
+                    / "sentencepiece_bad.proto"
                 )
             )
 
diff --git a/keras_nlp/models/t5/t5_tokenizer_test.py b/keras_nlp/models/t5/t5_tokenizer_test.py
index 32b3d05860..7ce335cc1b 100644
--- a/keras_nlp/models/t5/t5_tokenizer_test.py
+++ b/keras_nlp/models/t5/t5_tokenizer_test.py
@@ -48,7 +48,7 @@ def test_errors_missing_special_tokens(self):
                         pathlib.Path(__file__).parent.parent.parent
                         / "tests"
                         / "test_data"
-                        / "t5_sentencepiece_bad.proto"
+                        / "sentencepiece_bad.proto"
                     )
                 )
             )
diff --git a/keras_nlp/tests/test_data/deberta_v3_sentencepiece_bad.proto b/keras_nlp/tests/test_data/deberta_v3_sentencepiece_bad.proto
deleted file mode 100644
index 582613aba70500f85977fac17732e99a2391d252..0000000000000000000000000000000000000000
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diff --git a/keras_nlp/tests/test_data/f_net_sentencepiece_bad.proto b/keras_nlp/tests/test_data/f_net_sentencepiece_bad.proto
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diff --git a/keras_nlp/tests/test_data/albert_sentencepiece_bad.proto b/keras_nlp/tests/test_data/sentencepiece_bad.proto
similarity index 100%
rename from keras_nlp/tests/test_data/albert_sentencepiece_bad.proto
rename to keras_nlp/tests/test_data/sentencepiece_bad.proto
diff --git a/keras_nlp/tests/test_data/t5_sentencepiece_bad.proto b/keras_nlp/tests/test_data/t5_sentencepiece_bad.proto
deleted file mode 100644
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diff --git a/tools/sentencepiece_testing/create_albert_test_proto.py b/tools/sentencepiece_testing/create_albert_test_proto.py
index 8774a395f7..8f78e9c58b 100644
--- a/tools/sentencepiece_testing/create_albert_test_proto.py
+++ b/tools/sentencepiece_testing/create_albert_test_proto.py
@@ -33,15 +33,6 @@ def main():
     )
     _save(bytes_io, "albert_sentencepiece.proto")
 
-    bytes_io = _train_sentencepiece(
-        ["abc"],
-        vocab_size=5,
-        pad_id=-1,
-        eos_id=-1,
-        bos_id=-1,
-    )
-    _save(bytes_io, "albert_sentencepiece_bad.proto")
-
 
 if __name__ == "__main__":
     main()
diff --git a/tools/sentencepiece_testing/create_bad_proto.py b/tools/sentencepiece_testing/create_bad_proto.py
new file mode 100644
index 0000000000..9a093b87c1
--- /dev/null
+++ b/tools/sentencepiece_testing/create_bad_proto.py
@@ -0,0 +1,31 @@
+# Copyright 2023 The KerasNLP Authors
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from tools.sentencepiece_testing.utils import _save
+from tools.sentencepiece_testing.utils import _train_sentencepiece
+
+
+def main():
+    bytes_io = _train_sentencepiece(
+        ["abc"],
+        vocab_size=5,
+        pad_id=-1,
+        eos_id=-1,
+        bos_id=-1,
+    )
+    _save(bytes_io, "sentencepiece_bad.proto")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tools/sentencepiece_testing/create_deberta_v3_test_proto.py b/tools/sentencepiece_testing/create_deberta_v3_test_proto.py
index b0317ada10..2ee61f2db2 100644
--- a/tools/sentencepiece_testing/create_deberta_v3_test_proto.py
+++ b/tools/sentencepiece_testing/create_deberta_v3_test_proto.py
@@ -48,15 +48,6 @@ def main():
     )
     _save(bytes_io, "deberta_v3_tokenizer_sentencepiece.proto")
 
-    bytes_io = _train_sentencepiece(
-        ["abc"],
-        vocab_size=5,
-        pad_id=-1,
-        eos_id=-1,
-        bos_id=-1,
-    )
-    _save(bytes_io, "deberta_v3_sentencepiece_bad.proto")
-
 
 if __name__ == "__main__":
     main()
diff --git a/tools/sentencepiece_testing/create_f_net_test_proto.py b/tools/sentencepiece_testing/create_f_net_test_proto.py
index 7294b19043..824c7a124f 100644
--- a/tools/sentencepiece_testing/create_f_net_test_proto.py
+++ b/tools/sentencepiece_testing/create_f_net_test_proto.py
@@ -33,15 +33,6 @@ def main():
     )
     _save(bytes_io, "f_net_sentencepiece.proto")
 
-    bytes_io = _train_sentencepiece(
-        ["abc"],
-        vocab_size=5,
-        pad_id=-1,
-        eos_id=-1,
-        bos_id=-1,
-    )
-    _save(bytes_io, "f_net_sentencepiece_bad.proto")
-
 
 if __name__ == "__main__":
     main()
diff --git a/tools/sentencepiece_testing/create_t5_test_proto.py b/tools/sentencepiece_testing/create_t5_test_proto.py
index a51b7c6048..c613cc42ad 100644
--- a/tools/sentencepiece_testing/create_t5_test_proto.py
+++ b/tools/sentencepiece_testing/create_t5_test_proto.py
@@ -32,15 +32,6 @@ def main():
     )
     _save(bytes_io, "t5_sentencepiece.proto")
 
-    bytes_io = _train_sentencepiece(
-        ["abc"],
-        vocab_size=5,
-        pad_id=-1,
-        eos_id=-1,
-        bos_id=-1,
-    )
-    _save(bytes_io, "t5_sentencepiece_bad.proto")
-
 
 if __name__ == "__main__":
     main()

From 01347994f0f87c932766cbb33314384e95f957d9 Mon Sep 17 00:00:00 2001
From: Tirth Patel <tirthasheshpatel@gmail.com>
Date: Fri, 20 Oct 2023 23:24:48 +0000
Subject: [PATCH 08/14] Factor missing instances out.

---
 .../xlm_roberta_preprocessor_test.py          |  27 +++++----------
 ...ntence_piece_tokenizer_sentencepiece.proto | Bin 0 -> 237695 bytes
 .../sentence_piece_tokenizer_test.py          |  31 +++++++-----------
 .../create_sentence_piece_tokenizer_proto.py  |  29 ++++++++++++++++
 4 files changed, 48 insertions(+), 39 deletions(-)
 create mode 100644 keras_nlp/tests/test_data/sentence_piece_tokenizer_sentencepiece.proto
 create mode 100644 tools/sentencepiece_testing/create_sentence_piece_tokenizer_proto.py

diff --git a/keras_nlp/models/xlm_roberta/xlm_roberta_preprocessor_test.py b/keras_nlp/models/xlm_roberta/xlm_roberta_preprocessor_test.py
index 38eb4882f3..12ccfb4fd7 100644
--- a/keras_nlp/models/xlm_roberta/xlm_roberta_preprocessor_test.py
+++ b/keras_nlp/models/xlm_roberta/xlm_roberta_preprocessor_test.py
@@ -12,10 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import io
+import pathlib
 
 import pytest
-import sentencepiece
 
 from keras_nlp.models.xlm_roberta.xlm_roberta_preprocessor import (
     XLMRobertaPreprocessor,
@@ -28,24 +27,14 @@
 
 class XLMRobertaPreprocessorTest(TestCase):
     def setUp(self):
-        vocab_data = ["the quick brown fox", "the earth is round"]
-        bytes_io = io.BytesIO()
-        sentencepiece.SentencePieceTrainer.train(
-            sentence_iterator=iter(vocab_data),
-            model_writer=bytes_io,
-            vocab_size=12,
-            model_type="WORD",
-            pad_id=0,
-            unk_id=1,
-            bos_id=2,
-            eos_id=3,
-            pad_piece="<pad>",
-            unk_piece="<unk>",
-            bos_piece="[CLS]",
-            eos_piece="[SEP]",
-            user_defined_symbols="[MASK]",
+        self.tokenizer = XLMRobertaTokenizer(
+            proto=str(
+                pathlib.Path(__file__).parent.parent.parent
+                / "tests"
+                / "test_data"
+                / "xlm_roberta_sentencepiece.proto"
+            )
         )
-        self.tokenizer = XLMRobertaTokenizer(proto=bytes_io.getvalue())
         self.init_kwargs = {
             "tokenizer": self.tokenizer,
             "sequence_length": 8,
diff --git a/keras_nlp/tests/test_data/sentence_piece_tokenizer_sentencepiece.proto b/keras_nlp/tests/test_data/sentence_piece_tokenizer_sentencepiece.proto
new file mode 100644
index 0000000000000000000000000000000000000000..ec895a9d67f420ad7c377aadfaa12dca7b56ba97
GIT binary patch
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HcmV?d00001

diff --git a/keras_nlp/tokenizers/sentence_piece_tokenizer_test.py b/keras_nlp/tokenizers/sentence_piece_tokenizer_test.py
index e488f1d0c1..70e70f65b2 100644
--- a/keras_nlp/tokenizers/sentence_piece_tokenizer_test.py
+++ b/keras_nlp/tokenizers/sentence_piece_tokenizer_test.py
@@ -12,10 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import io
-import os
+import pathlib
 
-import sentencepiece
 import tensorflow as tf
 
 from keras_nlp.tests.test_case import TestCase
@@ -25,17 +23,12 @@
 class SentencePieceTokenizerTest(TestCase):
     def setUp(self):
         super().setUp()
-        bytes_io = io.BytesIO()
-        vocab_data = tf.data.Dataset.from_tensor_slices(
-            ["the quick brown fox."]
+        self.proto = str(
+            pathlib.Path(__file__).parent.parent
+            / "tests"
+            / "test_data"
+            / "sentence_piece_tokenizer_sentencepiece.proto"
         )
-        sentencepiece.SentencePieceTrainer.train(
-            sentence_iterator=vocab_data.as_numpy_iterator(),
-            model_writer=bytes_io,
-            vocab_size=7,
-            model_type="WORD",
-        )
-        self.proto = bytes_io.getvalue()
 
     def test_tokenize(self):
         input_data = ["the quick brown fox."]
@@ -112,15 +105,13 @@ def test_error_id_out_of_vocabulary(self):
         with self.assertRaises(ValueError):
             tokenizer.id_to_token(-1)
 
-    def test_from_file(self):
-        filepath = os.path.join(self.get_temp_dir(), "model.txt")
-        input_data = ["the quick brown fox."]
-        with tf.io.gfile.GFile(filepath, "wb") as file:
-            file.write(self.proto)
+    def test_from_bytes(self):
+        with tf.io.gfile.GFile(self.proto, "rb") as file:
+            proto = file.read()
         tokenizer = SentencePieceTokenizer(
-            proto=filepath,
+            proto=proto,
         )
-        output_data = tokenizer(input_data)
+        output_data = tokenizer(["the quick brown fox."])
         self.assertAllEqual(output_data, [[6, 5, 3, 4]])
 
     def test_tokenize_then_batch(self):
diff --git a/tools/sentencepiece_testing/create_sentence_piece_tokenizer_proto.py b/tools/sentencepiece_testing/create_sentence_piece_tokenizer_proto.py
new file mode 100644
index 0000000000..7675eee750
--- /dev/null
+++ b/tools/sentencepiece_testing/create_sentence_piece_tokenizer_proto.py
@@ -0,0 +1,29 @@
+# Copyright 2023 The KerasNLP Authors
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from tools.sentencepiece_testing.utils import _save
+from tools.sentencepiece_testing.utils import _train_sentencepiece
+
+
+def main():
+    bytes_io = _train_sentencepiece(
+        ["the quick brown fox."],
+        vocab_size=7,
+        model_type="WORD",
+    )
+    _save(bytes_io, "sentence_piece_tokenizer_sentencepiece.proto")
+
+
+if __name__ == "__main__":
+    main()

From ec944b8536d2b1af2bb3dfe528434e5308753a9a Mon Sep 17 00:00:00 2001
From: Tirth Patel <tirthasheshpatel@gmail.com>
Date: Wed, 25 Oct 2023 18:14:15 +0000
Subject: [PATCH 09/14] Address review comments

- Use one proto per model; modify tests accordingly
- Add a comment saying where the test proto file was generated from
- Rename the files from `*_sentencepiece.proto` to `*_test_vocab.spm`
- Rename the bad proto file to `no_special_token_vocab.spm`
- Add a method to get the test dir
- Remove the underscores from the sentencepiece util file
- Save the file in `train_sentencepiece` function itself
- Address the XLM Roberta test failure
---
 .../models/albert/albert_classifier_test.py   |  10 ++----
 .../albert_masked_lm_preprocessor_test.py     |  10 ++----
 .../models/albert/albert_masked_lm_test.py    |  10 ++----
 .../models/albert/albert_preprocessor_test.py |  10 ++----
 .../models/albert/albert_tokenizer_test.py    |  16 +++-------
 .../deberta_v3/deberta_v3_classifier_test.py  |   8 ++---
 .../deberta_v3_masked_lm_preprocessor_test.py |  10 ++----
 .../deberta_v3/deberta_v3_masked_lm_test.py   |   8 ++---
 .../deberta_v3_preprocessor_test.py           |  10 ++----
 .../deberta_v3/deberta_v3_tokenizer_test.py   |  26 ++++++---------
 .../models/f_net/f_net_classifier_test.py     |  10 ++----
 .../f_net_masked_lm_preprocessor_test.py      |  10 ++----
 .../models/f_net/f_net_masked_lm_test.py      |  10 ++----
 .../models/f_net/f_net_preprocessor_test.py   |  10 ++----
 .../models/f_net/f_net_tokenizer_test.py      |  16 +++-------
 keras_nlp/models/t5/t5_tokenizer_test.py      |  20 +++---------
 .../xlm_roberta_classifier_test.py            |   8 ++---
 ...xlm_roberta_masked_lm_preprocessor_test.py |  10 ++----
 .../xlm_roberta/xlm_roberta_masked_lm_test.py |   8 ++---
 .../xlm_roberta_preprocessor_test.py          |  12 ++-----
 .../xlm_roberta/xlm_roberta_tokenizer_test.py |   8 ++---
 keras_nlp/tests/test_case.py                  |   4 +++
 ...tencepiece.proto => albert_test_vocab.spm} | Bin
 ...epiece.proto => deberta_v3_test_vocab.spm} | Bin
 ...ntencepiece.proto => f_net_test_vocab.spm} | Bin
 ...e_bad.proto => no_special_token_vocab.spm} | Bin
 ..._sentencepiece.proto => t5_test_vocab.spm} | Bin
 ...cepiece.proto => tokenizer_test_vocab.spm} | Bin
 ...xlm_roberta_classifier_sentencepiece.proto | Bin 237751 -> 0 bytes
 .../test_data/xlm_roberta_sentencepiece.proto | Bin 237777 -> 0 bytes
 ...piece.proto => xlm_roberta_test_vocab.spm} | Bin 237805 -> 237831 bytes
 .../sentence_piece_tokenizer_test.py          |   7 +---
 .../create_albert_test_proto.py               |   7 ++--
 .../sentencepiece_testing/create_bad_proto.py |   7 ++--
 .../create_deberta_v3_test_proto.py           |  22 ++-----------
 .../create_f_net_test_proto.py                |   7 ++--
 .../create_sentence_piece_tokenizer_proto.py  |   7 ++--
 .../create_t5_test_proto.py                   |   7 ++--
 .../create_xlm_roberta_test_proto.py          |  30 +++++++-----------
 tools/sentencepiece_testing/utils.py          |   6 +---
 40 files changed, 92 insertions(+), 252 deletions(-)
 rename keras_nlp/tests/test_data/{albert_sentencepiece.proto => albert_test_vocab.spm} (100%)
 rename keras_nlp/tests/test_data/{deberta_v3_sentencepiece.proto => deberta_v3_test_vocab.spm} (100%)
 rename keras_nlp/tests/test_data/{f_net_sentencepiece.proto => f_net_test_vocab.spm} (100%)
 rename keras_nlp/tests/test_data/{sentencepiece_bad.proto => no_special_token_vocab.spm} (100%)
 rename keras_nlp/tests/test_data/{t5_sentencepiece.proto => t5_test_vocab.spm} (100%)
 rename keras_nlp/tests/test_data/{sentence_piece_tokenizer_sentencepiece.proto => tokenizer_test_vocab.spm} (100%)
 delete mode 100644 keras_nlp/tests/test_data/xlm_roberta_classifier_sentencepiece.proto
 delete mode 100644 keras_nlp/tests/test_data/xlm_roberta_sentencepiece.proto
 rename keras_nlp/tests/test_data/{deberta_v3_tokenizer_sentencepiece.proto => xlm_roberta_test_vocab.spm} (99%)

diff --git a/keras_nlp/models/albert/albert_classifier_test.py b/keras_nlp/models/albert/albert_classifier_test.py
index 7cd105eb72..4e88aa98a0 100644
--- a/keras_nlp/models/albert/albert_classifier_test.py
+++ b/keras_nlp/models/albert/albert_classifier_test.py
@@ -12,8 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import pathlib
-
 import pytest
 
 from keras_nlp.models.albert.albert_backbone import AlbertBackbone
@@ -28,12 +26,8 @@ def setUp(self):
         # Setup model.
         self.preprocessor = AlbertPreprocessor(
             AlbertTokenizer(
-                proto=str(
-                    pathlib.Path(__file__).parent.parent.parent
-                    / "tests"
-                    / "test_data"
-                    / "albert_sentencepiece.proto"
-                ),
+                # Generated using create_albert_test_proto.py
+                proto=str(self.get_test_data_dir() / "albert_test_vocab.spm"),
                 sequence_length=5,
             )
         )
diff --git a/keras_nlp/models/albert/albert_masked_lm_preprocessor_test.py b/keras_nlp/models/albert/albert_masked_lm_preprocessor_test.py
index 9b52a91f06..97b7436f48 100644
--- a/keras_nlp/models/albert/albert_masked_lm_preprocessor_test.py
+++ b/keras_nlp/models/albert/albert_masked_lm_preprocessor_test.py
@@ -12,8 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import pathlib
-
 import pytest
 
 from keras_nlp.models.albert.albert_masked_lm_preprocessor import (
@@ -26,12 +24,8 @@
 class AlbertMaskedLMPreprocessorTest(TestCase):
     def setUp(self):
         self.tokenizer = AlbertTokenizer(
-            proto=str(
-                pathlib.Path(__file__).parent.parent.parent
-                / "tests"
-                / "test_data"
-                / "albert_sentencepiece.proto"
-            )
+            # Generated using create_albert_test_proto.py
+            proto=str(self.get_test_data_dir() / "albert_test_vocab.spm")
         )
         self.init_kwargs = {
             "tokenizer": self.tokenizer,
diff --git a/keras_nlp/models/albert/albert_masked_lm_test.py b/keras_nlp/models/albert/albert_masked_lm_test.py
index 9e0bd1f22e..a9fb4ba4ad 100644
--- a/keras_nlp/models/albert/albert_masked_lm_test.py
+++ b/keras_nlp/models/albert/albert_masked_lm_test.py
@@ -12,8 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import pathlib
-
 import pytest
 
 from keras_nlp.models.albert.albert_backbone import AlbertBackbone
@@ -30,12 +28,8 @@ def setUp(self):
         # Setup model.
         self.preprocessor = AlbertMaskedLMPreprocessor(
             AlbertTokenizer(
-                proto=str(
-                    pathlib.Path(__file__).parent.parent.parent
-                    / "tests"
-                    / "test_data"
-                    / "albert_sentencepiece.proto"
-                ),
+                # Generated using create_albert_test_proto.py
+                proto=str(self.get_test_data_dir() / "albert_test_vocab.spm"),
                 sequence_length=5,
             ),
             # Simplify our testing by masking every available token.
diff --git a/keras_nlp/models/albert/albert_preprocessor_test.py b/keras_nlp/models/albert/albert_preprocessor_test.py
index 2b3983f89f..f5f617e7d2 100644
--- a/keras_nlp/models/albert/albert_preprocessor_test.py
+++ b/keras_nlp/models/albert/albert_preprocessor_test.py
@@ -12,8 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import pathlib
-
 import pytest
 
 from keras_nlp.models.albert.albert_preprocessor import AlbertPreprocessor
@@ -24,12 +22,8 @@
 class AlbertPreprocessorTest(TestCase):
     def setUp(self):
         self.tokenizer = AlbertTokenizer(
-            proto=str(
-                pathlib.Path(__file__).parent.parent.parent
-                / "tests"
-                / "test_data"
-                / "albert_sentencepiece.proto"
-            )
+            # Generated using create_albert_test_proto.py
+            proto=str(self.get_test_data_dir() / "albert_test_vocab.spm")
         )
         self.init_kwargs = {
             "tokenizer": self.tokenizer,
diff --git a/keras_nlp/models/albert/albert_tokenizer_test.py b/keras_nlp/models/albert/albert_tokenizer_test.py
index f3b1ed7b4d..5aae68c870 100644
--- a/keras_nlp/models/albert/albert_tokenizer_test.py
+++ b/keras_nlp/models/albert/albert_tokenizer_test.py
@@ -12,8 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import pathlib
-
 import pytest
 
 from keras_nlp.models.albert.albert_tokenizer import AlbertTokenizer
@@ -23,12 +21,8 @@
 class AlbertTokenizerTest(TestCase):
     def setUp(self):
         self.init_kwargs = {
-            "proto": str(
-                pathlib.Path(__file__).parent.parent.parent
-                / "tests"
-                / "test_data"
-                / "albert_sentencepiece.proto"
-            )
+            # Generated using create_albert_test_proto.py
+            "proto": str(self.get_test_data_dir() / "albert_test_vocab.spm")
         }
         self.input_data = ["the quick brown fox.", "the earth is round."]
 
@@ -43,11 +37,9 @@ def test_tokenizer_basics(self):
     def test_errors_missing_special_tokens(self):
         with self.assertRaises(ValueError):
             AlbertTokenizer(
+                # Generated using create_bad_proto.py
                 proto=str(
-                    pathlib.Path(__file__).parent.parent.parent
-                    / "tests"
-                    / "test_data"
-                    / "sentencepiece_bad.proto"
+                    self.get_test_data_dir() / "no_special_token_vocab.spm"
                 )
             )
 
diff --git a/keras_nlp/models/deberta_v3/deberta_v3_classifier_test.py b/keras_nlp/models/deberta_v3/deberta_v3_classifier_test.py
index 167f84da6e..df43196316 100644
--- a/keras_nlp/models/deberta_v3/deberta_v3_classifier_test.py
+++ b/keras_nlp/models/deberta_v3/deberta_v3_classifier_test.py
@@ -12,8 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import pathlib
-
 import pytest
 
 from keras_nlp.models.deberta_v3.deberta_v3_backbone import DebertaV3Backbone
@@ -32,11 +30,9 @@ def setUp(self):
         # Setup model.
         self.preprocessor = DebertaV3Preprocessor(
             DebertaV3Tokenizer(
+                # Generated using create_deberta_v3_test_proto.py
                 proto=str(
-                    pathlib.Path(__file__).parent.parent.parent
-                    / "tests"
-                    / "test_data"
-                    / "deberta_v3_sentencepiece.proto"
+                    self.get_test_data_dir() / "deberta_v3_test_vocab.spm"
                 )
             ),
             sequence_length=5,
diff --git a/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_preprocessor_test.py b/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_preprocessor_test.py
index 4b7439d1ba..af1d0ac190 100644
--- a/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_preprocessor_test.py
+++ b/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_preprocessor_test.py
@@ -12,8 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import pathlib
-
 import pytest
 
 from keras_nlp.models.deberta_v3.deberta_v3_masked_lm_preprocessor import (
@@ -26,12 +24,8 @@
 class DebertaV3MaskedLMPreprocessorTest(TestCase):
     def setUp(self):
         self.tokenizer = DebertaV3Tokenizer(
-            proto=str(
-                pathlib.Path(__file__).parent.parent.parent
-                / "tests"
-                / "test_data"
-                / "deberta_v3_sentencepiece.proto"
-            )
+            # Generated using create_deberta_v3_test_proto.py
+            proto=str(self.get_test_data_dir() / "deberta_v3_test_vocab.spm")
         )
         self.init_kwargs = {
             "tokenizer": self.tokenizer,
diff --git a/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_test.py b/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_test.py
index 09dc92ae5d..7734e99e4c 100644
--- a/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_test.py
+++ b/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_test.py
@@ -12,8 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import pathlib
-
 import pytest
 
 from keras_nlp.models.deberta_v3.deberta_v3_backbone import DebertaV3Backbone
@@ -30,11 +28,9 @@ def setUp(self):
         # Setup model.
         self.preprocessor = DebertaV3MaskedLMPreprocessor(
             DebertaV3Tokenizer(
+                # Generated using create_deberta_v3_test_proto.py
                 proto=str(
-                    pathlib.Path(__file__).parent.parent.parent
-                    / "tests"
-                    / "test_data"
-                    / "deberta_v3_sentencepiece.proto"
+                    self.get_test_data_dir() / "deberta_v3_test_vocab.spm"
                 )
             ),
             # Simplify our testing by masking every available token.
diff --git a/keras_nlp/models/deberta_v3/deberta_v3_preprocessor_test.py b/keras_nlp/models/deberta_v3/deberta_v3_preprocessor_test.py
index c6719c96d1..8a6fcbf452 100644
--- a/keras_nlp/models/deberta_v3/deberta_v3_preprocessor_test.py
+++ b/keras_nlp/models/deberta_v3/deberta_v3_preprocessor_test.py
@@ -12,8 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import pathlib
-
 import pytest
 
 from keras_nlp.models.deberta_v3.deberta_v3_preprocessor import (
@@ -26,12 +24,8 @@
 class DebertaV3PreprocessorTest(TestCase):
     def setUp(self):
         self.tokenizer = DebertaV3Tokenizer(
-            proto=str(
-                pathlib.Path(__file__).parent.parent.parent
-                / "tests"
-                / "test_data"
-                / "deberta_v3_sentencepiece.proto"
-            )
+            # Generated using create_deberta_v3_test_proto.py
+            proto=str(self.get_test_data_dir() / "deberta_v3_test_vocab.spm")
         )
         self.init_kwargs = {
             "tokenizer": self.tokenizer,
diff --git a/keras_nlp/models/deberta_v3/deberta_v3_tokenizer_test.py b/keras_nlp/models/deberta_v3/deberta_v3_tokenizer_test.py
index 0e1545a4ef..381e4d3165 100644
--- a/keras_nlp/models/deberta_v3/deberta_v3_tokenizer_test.py
+++ b/keras_nlp/models/deberta_v3/deberta_v3_tokenizer_test.py
@@ -12,8 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import pathlib
-
 import pytest
 
 from keras_nlp.models.deberta_v3.deberta_v3_tokenizer import DebertaV3Tokenizer
@@ -22,12 +20,8 @@
 
 class DebertaV3TokenizerTest(TestCase):
     def setUp(self):
-        proto = str(
-            pathlib.Path(__file__).parent.parent.parent
-            / "tests"
-            / "test_data"
-            / "deberta_v3_tokenizer_sentencepiece.proto"
-        )
+        # Generated using create_deberta_v3_test_proto.py
+        proto = str(self.get_test_data_dir() / "deberta_v3_test_vocab.spm")
         self.tokenizer = DebertaV3Tokenizer(proto=proto)
         self.init_kwargs = {"proto": proto}
         self.input_data = ["the quick brown fox.", "the earth is round."]
@@ -37,26 +31,24 @@ def test_tokenizer_basics(self):
             cls=DebertaV3Tokenizer,
             init_kwargs=self.init_kwargs,
             input_data=self.input_data,
-            expected_output=[[4, 9, 5, 3], [4, 6, 8, 3]],
+            expected_output=[[5, 10, 6, 3], [5, 7, 9, 3]],
         )
 
     def test_errors_missing_special_tokens(self):
         with self.assertRaises(ValueError):
             DebertaV3Tokenizer(
+                # Generated using create_bad_proto.py
                 proto=str(
-                    pathlib.Path(__file__).parent.parent.parent
-                    / "tests"
-                    / "test_data"
-                    / "sentencepiece_bad.proto"
+                    self.get_test_data_dir() / "no_special_token_vocab.spm"
                 )
             )
 
     def test_mask_token_handling(self):
         tokenizer = DebertaV3Tokenizer(**self.init_kwargs)
-        self.assertEqual(tokenizer.get_vocabulary()[11], "[MASK]")
-        self.assertEqual(tokenizer.id_to_token(11), "[MASK]")
-        self.assertEqual(tokenizer.token_to_id("[MASK]"), 11)
-        input_data = [[4, 9, 5, 7, self.tokenizer.mask_token_id]]
+        self.assertEqual(tokenizer.get_vocabulary()[4], "[MASK]")
+        self.assertEqual(tokenizer.id_to_token(4), "[MASK]")
+        self.assertEqual(tokenizer.token_to_id("[MASK]"), 4)
+        input_data = [[5, 10, 6, 8, self.tokenizer.mask_token_id]]
         output = tokenizer.detokenize(input_data)
         self.assertEqual(output, ["the quick brown fox"])
 
diff --git a/keras_nlp/models/f_net/f_net_classifier_test.py b/keras_nlp/models/f_net/f_net_classifier_test.py
index 50e3d5abe4..34211c2e5f 100644
--- a/keras_nlp/models/f_net/f_net_classifier_test.py
+++ b/keras_nlp/models/f_net/f_net_classifier_test.py
@@ -12,8 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import pathlib
-
 import pytest
 
 from keras_nlp.models.f_net.f_net_backbone import FNetBackbone
@@ -28,12 +26,8 @@ def setUp(self):
         # Setup model.
         self.preprocessor = FNetPreprocessor(
             FNetTokenizer(
-                proto=str(
-                    pathlib.Path(__file__).parent.parent.parent
-                    / "tests"
-                    / "test_data"
-                    / "f_net_sentencepiece.proto"
-                )
+                # Generated using create_f_net_test_proto.py
+                proto=str(self.get_test_data_dir() / "f_net_test_vocab.spm")
             ),
             sequence_length=5,
         )
diff --git a/keras_nlp/models/f_net/f_net_masked_lm_preprocessor_test.py b/keras_nlp/models/f_net/f_net_masked_lm_preprocessor_test.py
index 9e816f369d..b18c84ff23 100644
--- a/keras_nlp/models/f_net/f_net_masked_lm_preprocessor_test.py
+++ b/keras_nlp/models/f_net/f_net_masked_lm_preprocessor_test.py
@@ -12,8 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import pathlib
-
 import pytest
 
 from keras_nlp.models.f_net.f_net_masked_lm_preprocessor import (
@@ -26,12 +24,8 @@
 class FNetMaskedLMPreprocessorTest(TestCase):
     def setUp(self):
         self.tokenizer = FNetTokenizer(
-            proto=str(
-                pathlib.Path(__file__).parent.parent.parent
-                / "tests"
-                / "test_data"
-                / "f_net_sentencepiece.proto"
-            )
+            # Generated using create_f_net_test_proto.py
+            proto=str(self.get_test_data_dir() / "f_net_test_vocab.spm")
         )
         self.init_kwargs = {
             "tokenizer": self.tokenizer,
diff --git a/keras_nlp/models/f_net/f_net_masked_lm_test.py b/keras_nlp/models/f_net/f_net_masked_lm_test.py
index 4992b65d47..4e2b4f432a 100644
--- a/keras_nlp/models/f_net/f_net_masked_lm_test.py
+++ b/keras_nlp/models/f_net/f_net_masked_lm_test.py
@@ -12,8 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import pathlib
-
 import pytest
 
 from keras_nlp.models.f_net.f_net_backbone import FNetBackbone
@@ -30,12 +28,8 @@ def setUp(self):
         # Setup model.
         self.preprocessor = FNetMaskedLMPreprocessor(
             FNetTokenizer(
-                proto=str(
-                    pathlib.Path(__file__).parent.parent.parent
-                    / "tests"
-                    / "test_data"
-                    / "f_net_sentencepiece.proto"
-                )
+                # Generated using create_f_net_test_proto.py
+                proto=str(self.get_test_data_dir() / "f_net_test_vocab.spm")
             ),
             # Simplify our testing by masking every available token.
             mask_selection_rate=1.0,
diff --git a/keras_nlp/models/f_net/f_net_preprocessor_test.py b/keras_nlp/models/f_net/f_net_preprocessor_test.py
index 7e5aee579e..27156cadfd 100644
--- a/keras_nlp/models/f_net/f_net_preprocessor_test.py
+++ b/keras_nlp/models/f_net/f_net_preprocessor_test.py
@@ -12,8 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import pathlib
-
 import pytest
 
 from keras_nlp.models.f_net.f_net_preprocessor import FNetPreprocessor
@@ -24,12 +22,8 @@
 class FNetPreprocessorTest(TestCase):
     def setUp(self):
         self.tokenizer = FNetTokenizer(
-            proto=str(
-                pathlib.Path(__file__).parent.parent.parent
-                / "tests"
-                / "test_data"
-                / "f_net_sentencepiece.proto"
-            )
+            # Generated using create_f_net_test_proto.py
+            proto=str(self.get_test_data_dir() / "f_net_test_vocab.spm")
         )
         self.init_kwargs = {
             "tokenizer": self.tokenizer,
diff --git a/keras_nlp/models/f_net/f_net_tokenizer_test.py b/keras_nlp/models/f_net/f_net_tokenizer_test.py
index 9b8f5388da..d67392cad1 100644
--- a/keras_nlp/models/f_net/f_net_tokenizer_test.py
+++ b/keras_nlp/models/f_net/f_net_tokenizer_test.py
@@ -12,8 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import pathlib
-
 import pytest
 
 from keras_nlp.models.f_net.f_net_tokenizer import FNetTokenizer
@@ -23,12 +21,8 @@
 class FNetTokenizerTest(TestCase):
     def setUp(self):
         self.init_kwargs = {
-            "proto": str(
-                pathlib.Path(__file__).parent.parent.parent
-                / "tests"
-                / "test_data"
-                / "f_net_sentencepiece.proto"
-            )
+            # Generated using create_f_net_test_proto.py
+            "proto": str(self.get_test_data_dir() / "f_net_test_vocab.spm")
         }
         self.input_data = ["the quick brown fox.", "the earth is round."]
 
@@ -43,11 +37,9 @@ def test_tokenizer_basics(self):
     def test_errors_missing_special_tokens(self):
         with self.assertRaises(ValueError):
             FNetTokenizer(
+                # Generated using create_bad_proto.py
                 proto=str(
-                    pathlib.Path(__file__).parent.parent.parent
-                    / "tests"
-                    / "test_data"
-                    / "sentencepiece_bad.proto"
+                    self.get_test_data_dir() / "no_special_token_vocab.spm"
                 )
             )
 
diff --git a/keras_nlp/models/t5/t5_tokenizer_test.py b/keras_nlp/models/t5/t5_tokenizer_test.py
index 7ce335cc1b..898635cfd7 100644
--- a/keras_nlp/models/t5/t5_tokenizer_test.py
+++ b/keras_nlp/models/t5/t5_tokenizer_test.py
@@ -12,8 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import pathlib
-
 from keras_nlp.models.t5.t5_tokenizer import T5Tokenizer
 from keras_nlp.tests.test_case import TestCase
 
@@ -21,14 +19,8 @@
 class T5TokenizerTest(TestCase):
     def setUp(self):
         self.init_kwargs = {
-            "proto": str(
-                (
-                    pathlib.Path(__file__).parent.parent.parent
-                    / "tests"
-                    / "test_data"
-                    / "t5_sentencepiece.proto"
-                )
-            )
+            # Generated using create_t5_test_proto.py
+            "proto": str((self.get_test_data_dir() / "t5_test_vocab.spm"))
         }
         self.input_data = ["the quick brown fox.", "the earth is round."]
 
@@ -43,12 +35,8 @@ def test_tokenizer_basics(self):
     def test_errors_missing_special_tokens(self):
         with self.assertRaises(ValueError):
             T5Tokenizer(
+                # Generated using create_bad_proto.py
                 proto=str(
-                    (
-                        pathlib.Path(__file__).parent.parent.parent
-                        / "tests"
-                        / "test_data"
-                        / "sentencepiece_bad.proto"
-                    )
+                    (self.get_test_data_dir() / "no_special_token_vocab.spm")
                 )
             )
diff --git a/keras_nlp/models/xlm_roberta/xlm_roberta_classifier_test.py b/keras_nlp/models/xlm_roberta/xlm_roberta_classifier_test.py
index 3eab55c4c1..f60c8c3033 100644
--- a/keras_nlp/models/xlm_roberta/xlm_roberta_classifier_test.py
+++ b/keras_nlp/models/xlm_roberta/xlm_roberta_classifier_test.py
@@ -12,8 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import pathlib
-
 import pytest
 
 from keras_nlp.models.xlm_roberta.xlm_roberta_backbone import XLMRobertaBackbone
@@ -34,11 +32,9 @@ def setUp(self):
         # Setup model.
         self.preprocessor = XLMRobertaPreprocessor(
             XLMRobertaTokenizer(
+                # Generated using create_xlm_roberta_test_proto.py
                 proto=str(
-                    pathlib.Path(__file__).parent.parent.parent
-                    / "tests"
-                    / "test_data"
-                    / "xlm_roberta_classifier_sentencepiece.proto"
+                    self.get_test_data_dir() / "xlm_roberta_test_vocab.spm"
                 )
             ),
             sequence_length=5,
diff --git a/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_preprocessor_test.py b/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_preprocessor_test.py
index b1db15620b..b88e57bc99 100644
--- a/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_preprocessor_test.py
+++ b/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_preprocessor_test.py
@@ -12,8 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import pathlib
-
 import pytest
 
 from keras_nlp.models.xlm_roberta.xlm_roberta_masked_lm_preprocessor import (
@@ -28,12 +26,8 @@
 class XLMRobertaMaskedLMPreprocessorTest(TestCase):
     def setUp(self):
         self.tokenizer = XLMRobertaTokenizer(
-            proto=str(
-                pathlib.Path(__file__).parent.parent.parent
-                / "tests"
-                / "test_data"
-                / "xlm_roberta_sentencepiece.proto"
-            )
+            # Generated using create_xlm_roberta_test_proto.py
+            proto=str(self.get_test_data_dir() / "xlm_roberta_test_vocab.spm")
         )
         self.init_kwargs = {
             "tokenizer": self.tokenizer,
diff --git a/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_test.py b/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_test.py
index b694fe0fb4..a3dd58b1a0 100644
--- a/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_test.py
+++ b/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_test.py
@@ -12,8 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import pathlib
-
 import pytest
 
 from keras_nlp.models.xlm_roberta.xlm_roberta_backbone import XLMRobertaBackbone
@@ -34,11 +32,9 @@ def setUp(self):
         # Setup model.
         self.preprocessor = XLMRobertaMaskedLMPreprocessor(
             XLMRobertaTokenizer(
+                # Generated using create_xlm_roberta_test_proto.py
                 proto=str(
-                    pathlib.Path(__file__).parent.parent.parent
-                    / "tests"
-                    / "test_data"
-                    / "xlm_roberta_sentencepiece.proto"
+                    self.get_test_data_dir() / "xlm_roberta_test_vocab.spm"
                 )
             ),
             # Simplify our testing by masking every available token.
diff --git a/keras_nlp/models/xlm_roberta/xlm_roberta_preprocessor_test.py b/keras_nlp/models/xlm_roberta/xlm_roberta_preprocessor_test.py
index 12ccfb4fd7..48b2140332 100644
--- a/keras_nlp/models/xlm_roberta/xlm_roberta_preprocessor_test.py
+++ b/keras_nlp/models/xlm_roberta/xlm_roberta_preprocessor_test.py
@@ -12,8 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import pathlib
-
 import pytest
 
 from keras_nlp.models.xlm_roberta.xlm_roberta_preprocessor import (
@@ -28,12 +26,8 @@
 class XLMRobertaPreprocessorTest(TestCase):
     def setUp(self):
         self.tokenizer = XLMRobertaTokenizer(
-            proto=str(
-                pathlib.Path(__file__).parent.parent.parent
-                / "tests"
-                / "test_data"
-                / "xlm_roberta_sentencepiece.proto"
-            )
+            # Generated using create_xlm_roberta_test_proto.py
+            proto=str(self.get_test_data_dir() / "xlm_roberta_test_vocab.spm")
         )
         self.init_kwargs = {
             "tokenizer": self.tokenizer,
@@ -52,7 +46,7 @@ def test_preprocessor_basics(self):
             input_data=self.input_data,
             expected_output=(
                 {
-                    "token_ids": [[0, 6, 11, 7, 9, 2, 1, 1]],
+                    "token_ids": [[0, 5, 10, 6, 8, 2, 1, 1]],
                     "padding_mask": [[1, 1, 1, 1, 1, 1, 0, 0]],
                 },
                 [1],  # Pass through labels.
diff --git a/keras_nlp/models/xlm_roberta/xlm_roberta_tokenizer_test.py b/keras_nlp/models/xlm_roberta/xlm_roberta_tokenizer_test.py
index a85543355d..f6dd8d2389 100644
--- a/keras_nlp/models/xlm_roberta/xlm_roberta_tokenizer_test.py
+++ b/keras_nlp/models/xlm_roberta/xlm_roberta_tokenizer_test.py
@@ -12,8 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import pathlib
-
 import pytest
 
 from keras_nlp.models.xlm_roberta.xlm_roberta_tokenizer import (
@@ -25,11 +23,9 @@
 class XLMRobertaTokenizerTest(TestCase):
     def setUp(self):
         self.init_kwargs = {
+            # Generated using create_xlm_roberta_test_proto.py
             "proto": str(
-                pathlib.Path(__file__).parent.parent.parent
-                / "tests"
-                / "test_data"
-                / "xlm_roberta_sentencepiece.proto"
+                self.get_test_data_dir() / "xlm_roberta_test_vocab.spm"
             )
         }
         self.input_data = ["the quick brown fox.", "the earth is round."]
diff --git a/keras_nlp/tests/test_case.py b/keras_nlp/tests/test_case.py
index 2025f3ad13..8dad878328 100644
--- a/keras_nlp/tests/test_case.py
+++ b/keras_nlp/tests/test_case.py
@@ -14,6 +14,7 @@
 
 import json
 import os
+import pathlib
 import re
 
 import tensorflow as tf
@@ -417,3 +418,6 @@ def compare(actual, expected):
                 self.assertAllClose(actual, expected, atol=0.01, rtol=0.01)
 
             tree.map_structure(compare, output, expected_partial_output)
+
+    def get_test_data_dir(self):
+        return pathlib.Path(__file__).parent / "test_data"
diff --git a/keras_nlp/tests/test_data/albert_sentencepiece.proto b/keras_nlp/tests/test_data/albert_test_vocab.spm
similarity index 100%
rename from keras_nlp/tests/test_data/albert_sentencepiece.proto
rename to keras_nlp/tests/test_data/albert_test_vocab.spm
diff --git a/keras_nlp/tests/test_data/deberta_v3_sentencepiece.proto b/keras_nlp/tests/test_data/deberta_v3_test_vocab.spm
similarity index 100%
rename from keras_nlp/tests/test_data/deberta_v3_sentencepiece.proto
rename to keras_nlp/tests/test_data/deberta_v3_test_vocab.spm
diff --git a/keras_nlp/tests/test_data/f_net_sentencepiece.proto b/keras_nlp/tests/test_data/f_net_test_vocab.spm
similarity index 100%
rename from keras_nlp/tests/test_data/f_net_sentencepiece.proto
rename to keras_nlp/tests/test_data/f_net_test_vocab.spm
diff --git a/keras_nlp/tests/test_data/sentencepiece_bad.proto b/keras_nlp/tests/test_data/no_special_token_vocab.spm
similarity index 100%
rename from keras_nlp/tests/test_data/sentencepiece_bad.proto
rename to keras_nlp/tests/test_data/no_special_token_vocab.spm
diff --git a/keras_nlp/tests/test_data/t5_sentencepiece.proto b/keras_nlp/tests/test_data/t5_test_vocab.spm
similarity index 100%
rename from keras_nlp/tests/test_data/t5_sentencepiece.proto
rename to keras_nlp/tests/test_data/t5_test_vocab.spm
diff --git a/keras_nlp/tests/test_data/sentence_piece_tokenizer_sentencepiece.proto b/keras_nlp/tests/test_data/tokenizer_test_vocab.spm
similarity index 100%
rename from keras_nlp/tests/test_data/sentence_piece_tokenizer_sentencepiece.proto
rename to keras_nlp/tests/test_data/tokenizer_test_vocab.spm
diff --git a/keras_nlp/tests/test_data/xlm_roberta_classifier_sentencepiece.proto b/keras_nlp/tests/test_data/xlm_roberta_classifier_sentencepiece.proto
deleted file mode 100644
index 893aedad07cee3216d5ee6fe6044fc6525eb1a98..0000000000000000000000000000000000000000
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diff --git a/keras_nlp/tests/test_data/xlm_roberta_sentencepiece.proto b/keras_nlp/tests/test_data/xlm_roberta_sentencepiece.proto
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diff --git a/keras_nlp/tests/test_data/deberta_v3_tokenizer_sentencepiece.proto b/keras_nlp/tests/test_data/xlm_roberta_test_vocab.spm
similarity index 99%
rename from keras_nlp/tests/test_data/deberta_v3_tokenizer_sentencepiece.proto
rename to keras_nlp/tests/test_data/xlm_roberta_test_vocab.spm
index 11dc7ea7c5125fe85b38bbe9bf2a7c0f1d9ee3a5..8520ca4919b4344d5643f1e99b2c03993b901e80 100644
GIT binary patch
delta 134
zcmaERkgxp^p8^*j7pqM{Vv3z80}x0sgZZU-*-$>yL;*zselE6XU&mnYScn>yi4KKU
zmJ-YgJii#B5(k(VPcSiEU}C<(#PEuV)dpn1CnnZtXP@BMUqCw8H6XT$8Ddf6qt-`^
Nt&f<tK4Rux007o5BOCw#

delta 108
zcmZoa#P{|fp8yvh7i)BYqf4wP0}x0sPgGFk2MLAxc|(PmCI%K78b~lJa35e|KEcFz
ufr;q`6T>Seh?-A8+Sw;K_7{*2b`6MaVul#k_^0&`W9uKLt$&!g7XScdm>t#t

diff --git a/keras_nlp/tokenizers/sentence_piece_tokenizer_test.py b/keras_nlp/tokenizers/sentence_piece_tokenizer_test.py
index 70e70f65b2..9ad4ceb549 100644
--- a/keras_nlp/tokenizers/sentence_piece_tokenizer_test.py
+++ b/keras_nlp/tokenizers/sentence_piece_tokenizer_test.py
@@ -12,8 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import pathlib
-
 import tensorflow as tf
 
 from keras_nlp.tests.test_case import TestCase
@@ -24,10 +22,7 @@ class SentencePieceTokenizerTest(TestCase):
     def setUp(self):
         super().setUp()
         self.proto = str(
-            pathlib.Path(__file__).parent.parent
-            / "tests"
-            / "test_data"
-            / "sentence_piece_tokenizer_sentencepiece.proto"
+            self.get_test_data_dir() / "sentence_piece_tokenizer_test_vocab.spm"
         )
 
     def test_tokenize(self):
diff --git a/tools/sentencepiece_testing/create_albert_test_proto.py b/tools/sentencepiece_testing/create_albert_test_proto.py
index 8f78e9c58b..80e82b3cd1 100644
--- a/tools/sentencepiece_testing/create_albert_test_proto.py
+++ b/tools/sentencepiece_testing/create_albert_test_proto.py
@@ -12,13 +12,13 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from tools.sentencepiece_testing.utils import _save
-from tools.sentencepiece_testing.utils import _train_sentencepiece
+from tools.sentencepiece_testing.utils import train_sentencepiece
 
 
 def main():
-    bytes_io = _train_sentencepiece(
+    train_sentencepiece(
         ["the quick brown fox", "the earth is round"],
+        "albert_test_vocab.spm",
         vocab_size=12,
         model_type="WORD",
         pad_id=0,
@@ -31,7 +31,6 @@ def main():
         eos_piece="[SEP]",
         user_defined_symbols="[MASK]",
     )
-    _save(bytes_io, "albert_sentencepiece.proto")
 
 
 if __name__ == "__main__":
diff --git a/tools/sentencepiece_testing/create_bad_proto.py b/tools/sentencepiece_testing/create_bad_proto.py
index 9a093b87c1..c13ef6e05a 100644
--- a/tools/sentencepiece_testing/create_bad_proto.py
+++ b/tools/sentencepiece_testing/create_bad_proto.py
@@ -12,19 +12,18 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from tools.sentencepiece_testing.utils import _save
-from tools.sentencepiece_testing.utils import _train_sentencepiece
+from tools.sentencepiece_testing.utils import train_sentencepiece
 
 
 def main():
-    bytes_io = _train_sentencepiece(
+    train_sentencepiece(
         ["abc"],
+        "no_special_token_vocab.spm",
         vocab_size=5,
         pad_id=-1,
         eos_id=-1,
         bos_id=-1,
     )
-    _save(bytes_io, "sentencepiece_bad.proto")
 
 
 if __name__ == "__main__":
diff --git a/tools/sentencepiece_testing/create_deberta_v3_test_proto.py b/tools/sentencepiece_testing/create_deberta_v3_test_proto.py
index 2ee61f2db2..c3f98867c5 100644
--- a/tools/sentencepiece_testing/create_deberta_v3_test_proto.py
+++ b/tools/sentencepiece_testing/create_deberta_v3_test_proto.py
@@ -12,13 +12,13 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from tools.sentencepiece_testing.utils import _save
-from tools.sentencepiece_testing.utils import _train_sentencepiece
+from tools.sentencepiece_testing.utils import train_sentencepiece
 
 
 def main():
-    bytes_io = _train_sentencepiece(
+    train_sentencepiece(
         ["the quick brown fox", "the earth is round"],
+        "deberta_v3_test_vocab.spm",
         vocab_size=12,
         model_type="WORD",
         pad_id=0,
@@ -31,22 +31,6 @@ def main():
         unk_piece="[UNK]",
         user_defined_symbols="[MASK]",
     )
-    _save(bytes_io, "deberta_v3_sentencepiece.proto")
-
-    bytes_io = _train_sentencepiece(
-        ["the quick brown fox", "the earth is round"],
-        vocab_size=11,
-        model_type="WORD",
-        pad_id=0,
-        bos_id=1,
-        eos_id=2,
-        unk_id=3,
-        pad_piece="[PAD]",
-        bos_piece="[CLS]",
-        eos_piece="[SEP]",
-        unk_piece="[UNK]",
-    )
-    _save(bytes_io, "deberta_v3_tokenizer_sentencepiece.proto")
 
 
 if __name__ == "__main__":
diff --git a/tools/sentencepiece_testing/create_f_net_test_proto.py b/tools/sentencepiece_testing/create_f_net_test_proto.py
index 824c7a124f..949a5692f9 100644
--- a/tools/sentencepiece_testing/create_f_net_test_proto.py
+++ b/tools/sentencepiece_testing/create_f_net_test_proto.py
@@ -12,13 +12,13 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from tools.sentencepiece_testing.utils import _save
-from tools.sentencepiece_testing.utils import _train_sentencepiece
+from tools.sentencepiece_testing.utils import train_sentencepiece
 
 
 def main():
-    bytes_io = _train_sentencepiece(
+    train_sentencepiece(
         ["the quick brown fox", "the earth is round"],
+        "f_net_test_vocab.spm",
         vocab_size=12,
         model_type="WORD",
         pad_id=0,
@@ -31,7 +31,6 @@ def main():
         eos_piece="[SEP]",
         user_defined_symbols="[MASK]",
     )
-    _save(bytes_io, "f_net_sentencepiece.proto")
 
 
 if __name__ == "__main__":
diff --git a/tools/sentencepiece_testing/create_sentence_piece_tokenizer_proto.py b/tools/sentencepiece_testing/create_sentence_piece_tokenizer_proto.py
index 7675eee750..a40eade848 100644
--- a/tools/sentencepiece_testing/create_sentence_piece_tokenizer_proto.py
+++ b/tools/sentencepiece_testing/create_sentence_piece_tokenizer_proto.py
@@ -12,17 +12,16 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from tools.sentencepiece_testing.utils import _save
-from tools.sentencepiece_testing.utils import _train_sentencepiece
+from tools.sentencepiece_testing.utils import train_sentencepiece
 
 
 def main():
-    bytes_io = _train_sentencepiece(
+    train_sentencepiece(
         ["the quick brown fox."],
+        "tokenizer_test_vocab.spm",
         vocab_size=7,
         model_type="WORD",
     )
-    _save(bytes_io, "sentence_piece_tokenizer_sentencepiece.proto")
 
 
 if __name__ == "__main__":
diff --git a/tools/sentencepiece_testing/create_t5_test_proto.py b/tools/sentencepiece_testing/create_t5_test_proto.py
index c613cc42ad..b7e28160e5 100644
--- a/tools/sentencepiece_testing/create_t5_test_proto.py
+++ b/tools/sentencepiece_testing/create_t5_test_proto.py
@@ -12,13 +12,13 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from tools.sentencepiece_testing.utils import _save
-from tools.sentencepiece_testing.utils import _train_sentencepiece
+from tools.sentencepiece_testing.utils import train_sentencepiece
 
 
 def main():
-    bytes_io = _train_sentencepiece(
+    train_sentencepiece(
         ["the quick brown fox", "the earth is round"],
+        "t5_test_vocab.spm",
         vocab_size=11,
         model_type="WORD",
         bos_id=-1,
@@ -30,7 +30,6 @@ def main():
         unk_piece="<unk>",
         user_defined_symbols="[MASK]",
     )
-    _save(bytes_io, "t5_sentencepiece.proto")
 
 
 if __name__ == "__main__":
diff --git a/tools/sentencepiece_testing/create_xlm_roberta_test_proto.py b/tools/sentencepiece_testing/create_xlm_roberta_test_proto.py
index 5fd5eb74c3..988d161f99 100644
--- a/tools/sentencepiece_testing/create_xlm_roberta_test_proto.py
+++ b/tools/sentencepiece_testing/create_xlm_roberta_test_proto.py
@@ -12,31 +12,25 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from tools.sentencepiece_testing.utils import _save
-from tools.sentencepiece_testing.utils import _train_sentencepiece
+from tools.sentencepiece_testing.utils import train_sentencepiece
 
 
 def main():
-    bytes_io = _train_sentencepiece(
+    train_sentencepiece(
         ["the quick brown fox", "the earth is round"],
-        vocab_size=10,
+        "xlm_roberta_test_vocab.spm",
+        vocab_size=12,
         model_type="WORD",
-        unk_id=0,
-        bos_id=1,
-        eos_id=2,
-    )
-    _save(bytes_io, "xlm_roberta_classifier_sentencepiece.proto")
-
-    bytes_io = _train_sentencepiece(
-        ["the quick brown fox", "the earth is round"],
-        vocab_size=11,
-        model_type="WORD",
-        unk_id=0,
-        bos_id=1,
-        eos_id=2,
+        pad_id=0,
+        unk_id=1,
+        bos_id=2,
+        eos_id=3,
+        pad_piece="<pad>",
+        unk_piece="<unk>",
+        bos_piece="[CLS]",
+        eos_piece="[SEP]",
         user_defined_symbols="[MASK]",
     )
-    _save(bytes_io, "xlm_roberta_sentencepiece.proto")
 
 
 if __name__ == "__main__":
diff --git a/tools/sentencepiece_testing/utils.py b/tools/sentencepiece_testing/utils.py
index e735438656..9deebd9737 100644
--- a/tools/sentencepiece_testing/utils.py
+++ b/tools/sentencepiece_testing/utils.py
@@ -17,15 +17,11 @@
 import sentencepiece
 
 
-def _train_sentencepiece(data, *args, **kwargs):
+def train_sentencepiece(data, filename, *args, **kwargs):
     bytes_io = io.BytesIO()
     sentencepiece.SentencePieceTrainer.train(
         sentence_iterator=iter(data), model_writer=bytes_io, *args, **kwargs
     )
-    return bytes_io
-
-
-def _save(bytes_io, filename):
     with open(
         pathlib.Path(__file__).parent.parent.parent
         / "keras_nlp"

From a76c57764f308684d34d0ac8f673560ce1401141 Mon Sep 17 00:00:00 2001
From: Tirth Patel <tirthasheshpatel@gmail.com>
Date: Wed, 25 Oct 2023 18:31:18 +0000
Subject: [PATCH 10/14] create_bad_proto.py -> create_no_special_token_proto.py

---
 keras_nlp/models/albert/albert_tokenizer_test.py                | 2 +-
 keras_nlp/models/deberta_v3/deberta_v3_tokenizer_test.py        | 2 +-
 keras_nlp/models/f_net/f_net_tokenizer_test.py                  | 2 +-
 keras_nlp/models/t5/t5_tokenizer_test.py                        | 2 +-
 .../{create_bad_proto.py => create_no_special_token_proto.py}   | 0
 5 files changed, 4 insertions(+), 4 deletions(-)
 rename tools/sentencepiece_testing/{create_bad_proto.py => create_no_special_token_proto.py} (100%)

diff --git a/keras_nlp/models/albert/albert_tokenizer_test.py b/keras_nlp/models/albert/albert_tokenizer_test.py
index 5aae68c870..ca6dbab2ba 100644
--- a/keras_nlp/models/albert/albert_tokenizer_test.py
+++ b/keras_nlp/models/albert/albert_tokenizer_test.py
@@ -37,7 +37,7 @@ def test_tokenizer_basics(self):
     def test_errors_missing_special_tokens(self):
         with self.assertRaises(ValueError):
             AlbertTokenizer(
-                # Generated using create_bad_proto.py
+                # Generated using create_no_special_token_proto.py
                 proto=str(
                     self.get_test_data_dir() / "no_special_token_vocab.spm"
                 )
diff --git a/keras_nlp/models/deberta_v3/deberta_v3_tokenizer_test.py b/keras_nlp/models/deberta_v3/deberta_v3_tokenizer_test.py
index 381e4d3165..cc78808b59 100644
--- a/keras_nlp/models/deberta_v3/deberta_v3_tokenizer_test.py
+++ b/keras_nlp/models/deberta_v3/deberta_v3_tokenizer_test.py
@@ -37,7 +37,7 @@ def test_tokenizer_basics(self):
     def test_errors_missing_special_tokens(self):
         with self.assertRaises(ValueError):
             DebertaV3Tokenizer(
-                # Generated using create_bad_proto.py
+                # Generated using create_no_special_token_proto.py
                 proto=str(
                     self.get_test_data_dir() / "no_special_token_vocab.spm"
                 )
diff --git a/keras_nlp/models/f_net/f_net_tokenizer_test.py b/keras_nlp/models/f_net/f_net_tokenizer_test.py
index d67392cad1..4d0a830af1 100644
--- a/keras_nlp/models/f_net/f_net_tokenizer_test.py
+++ b/keras_nlp/models/f_net/f_net_tokenizer_test.py
@@ -37,7 +37,7 @@ def test_tokenizer_basics(self):
     def test_errors_missing_special_tokens(self):
         with self.assertRaises(ValueError):
             FNetTokenizer(
-                # Generated using create_bad_proto.py
+                # Generated using create_no_special_token_proto.py
                 proto=str(
                     self.get_test_data_dir() / "no_special_token_vocab.spm"
                 )
diff --git a/keras_nlp/models/t5/t5_tokenizer_test.py b/keras_nlp/models/t5/t5_tokenizer_test.py
index 898635cfd7..88472650ae 100644
--- a/keras_nlp/models/t5/t5_tokenizer_test.py
+++ b/keras_nlp/models/t5/t5_tokenizer_test.py
@@ -35,7 +35,7 @@ def test_tokenizer_basics(self):
     def test_errors_missing_special_tokens(self):
         with self.assertRaises(ValueError):
             T5Tokenizer(
-                # Generated using create_bad_proto.py
+                # Generated using create_no_special_token_proto.py
                 proto=str(
                     (self.get_test_data_dir() / "no_special_token_vocab.spm")
                 )
diff --git a/tools/sentencepiece_testing/create_bad_proto.py b/tools/sentencepiece_testing/create_no_special_token_proto.py
similarity index 100%
rename from tools/sentencepiece_testing/create_bad_proto.py
rename to tools/sentencepiece_testing/create_no_special_token_proto.py

From a77b362bcac704bb7f4d1abd86109c97b94b7a6c Mon Sep 17 00:00:00 2001
From: Tirth Patel <tirthasheshpatel@gmail.com>
Date: Wed, 25 Oct 2023 18:35:13 +0000
Subject: [PATCH 11/14] Update the SentencePieceTokenizer test proto file

---
 keras_nlp/tokenizers/sentence_piece_tokenizer_test.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/keras_nlp/tokenizers/sentence_piece_tokenizer_test.py b/keras_nlp/tokenizers/sentence_piece_tokenizer_test.py
index 9ad4ceb549..18ca270914 100644
--- a/keras_nlp/tokenizers/sentence_piece_tokenizer_test.py
+++ b/keras_nlp/tokenizers/sentence_piece_tokenizer_test.py
@@ -22,7 +22,7 @@ class SentencePieceTokenizerTest(TestCase):
     def setUp(self):
         super().setUp()
         self.proto = str(
-            self.get_test_data_dir() / "sentence_piece_tokenizer_test_vocab.spm"
+            self.get_test_data_dir() / "tokenizer_test_vocab.spm"
         )
 
     def test_tokenize(self):

From bf0b044170e8ce2927d50701b919a0a5e3e7fb4a Mon Sep 17 00:00:00 2001
From: Tirth Patel <tirthasheshpatel@gmail.com>
Date: Wed, 25 Oct 2023 22:50:20 +0000
Subject: [PATCH 12/14] Use os.path.join and resolve XLMRoberta failures

---
 keras_nlp/models/albert/albert_classifier_test.py    |  6 +++++-
 .../albert/albert_masked_lm_preprocessor_test.py     |  6 +++++-
 keras_nlp/models/albert/albert_masked_lm_test.py     |  6 +++++-
 keras_nlp/models/albert/albert_preprocessor_test.py  |  6 +++++-
 keras_nlp/models/albert/albert_tokenizer_test.py     | 10 +++++++---
 .../models/deberta_v3/deberta_v3_classifier_test.py  |  6 ++++--
 .../deberta_v3_masked_lm_preprocessor_test.py        |  6 +++++-
 .../models/deberta_v3/deberta_v3_masked_lm_test.py   |  6 ++++--
 .../deberta_v3/deberta_v3_preprocessor_test.py       |  6 +++++-
 .../models/deberta_v3/deberta_v3_tokenizer_test.py   | 10 +++++++---
 keras_nlp/models/f_net/f_net_classifier_test.py      |  6 +++++-
 .../f_net/f_net_masked_lm_preprocessor_test.py       |  4 +++-
 keras_nlp/models/f_net/f_net_masked_lm_test.py       |  6 +++++-
 keras_nlp/models/f_net/f_net_preprocessor_test.py    |  4 +++-
 keras_nlp/models/f_net/f_net_tokenizer_test.py       | 10 +++++++---
 keras_nlp/models/t5/t5_tokenizer_test.py             | 10 +++++++---
 .../xlm_roberta/xlm_roberta_classifier_test.py       |  6 ++++--
 .../xlm_roberta_masked_lm_preprocessor_test.py       | 12 ++++++++----
 .../models/xlm_roberta/xlm_roberta_masked_lm_test.py |  8 +++++---
 .../xlm_roberta/xlm_roberta_preprocessor_test.py     |  8 ++++++--
 .../models/xlm_roberta/xlm_roberta_tokenizer_test.py |  8 +++++---
 keras_nlp/tests/test_case.py                         |  2 +-
 .../tokenizers/sentence_piece_tokenizer_test.py      |  6 ++++--
 23 files changed, 115 insertions(+), 43 deletions(-)

diff --git a/keras_nlp/models/albert/albert_classifier_test.py b/keras_nlp/models/albert/albert_classifier_test.py
index 4e88aa98a0..ebf8a630eb 100644
--- a/keras_nlp/models/albert/albert_classifier_test.py
+++ b/keras_nlp/models/albert/albert_classifier_test.py
@@ -12,6 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import os
+
 import pytest
 
 from keras_nlp.models.albert.albert_backbone import AlbertBackbone
@@ -27,7 +29,9 @@ def setUp(self):
         self.preprocessor = AlbertPreprocessor(
             AlbertTokenizer(
                 # Generated using create_albert_test_proto.py
-                proto=str(self.get_test_data_dir() / "albert_test_vocab.spm"),
+                proto=os.path.join(
+                    self.get_test_data_dir(), "albert_test_vocab.spm"
+                ),
                 sequence_length=5,
             )
         )
diff --git a/keras_nlp/models/albert/albert_masked_lm_preprocessor_test.py b/keras_nlp/models/albert/albert_masked_lm_preprocessor_test.py
index 97b7436f48..79d3a36bbb 100644
--- a/keras_nlp/models/albert/albert_masked_lm_preprocessor_test.py
+++ b/keras_nlp/models/albert/albert_masked_lm_preprocessor_test.py
@@ -12,6 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import os
+
 import pytest
 
 from keras_nlp.models.albert.albert_masked_lm_preprocessor import (
@@ -25,7 +27,9 @@ class AlbertMaskedLMPreprocessorTest(TestCase):
     def setUp(self):
         self.tokenizer = AlbertTokenizer(
             # Generated using create_albert_test_proto.py
-            proto=str(self.get_test_data_dir() / "albert_test_vocab.spm")
+            proto=os.path.join(
+                self.get_test_data_dir(), "albert_test_vocab.spm"
+            )
         )
         self.init_kwargs = {
             "tokenizer": self.tokenizer,
diff --git a/keras_nlp/models/albert/albert_masked_lm_test.py b/keras_nlp/models/albert/albert_masked_lm_test.py
index a9fb4ba4ad..f992ed2b37 100644
--- a/keras_nlp/models/albert/albert_masked_lm_test.py
+++ b/keras_nlp/models/albert/albert_masked_lm_test.py
@@ -12,6 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import os
+
 import pytest
 
 from keras_nlp.models.albert.albert_backbone import AlbertBackbone
@@ -29,7 +31,9 @@ def setUp(self):
         self.preprocessor = AlbertMaskedLMPreprocessor(
             AlbertTokenizer(
                 # Generated using create_albert_test_proto.py
-                proto=str(self.get_test_data_dir() / "albert_test_vocab.spm"),
+                proto=os.path.join(
+                    self.get_test_data_dir(), "albert_test_vocab.spm"
+                ),
                 sequence_length=5,
             ),
             # Simplify our testing by masking every available token.
diff --git a/keras_nlp/models/albert/albert_preprocessor_test.py b/keras_nlp/models/albert/albert_preprocessor_test.py
index f5f617e7d2..7d6fb4cfd4 100644
--- a/keras_nlp/models/albert/albert_preprocessor_test.py
+++ b/keras_nlp/models/albert/albert_preprocessor_test.py
@@ -12,6 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import os
+
 import pytest
 
 from keras_nlp.models.albert.albert_preprocessor import AlbertPreprocessor
@@ -23,7 +25,9 @@ class AlbertPreprocessorTest(TestCase):
     def setUp(self):
         self.tokenizer = AlbertTokenizer(
             # Generated using create_albert_test_proto.py
-            proto=str(self.get_test_data_dir() / "albert_test_vocab.spm")
+            proto=os.path.join(
+                self.get_test_data_dir(), "albert_test_vocab.spm"
+            )
         )
         self.init_kwargs = {
             "tokenizer": self.tokenizer,
diff --git a/keras_nlp/models/albert/albert_tokenizer_test.py b/keras_nlp/models/albert/albert_tokenizer_test.py
index ca6dbab2ba..ca80ace281 100644
--- a/keras_nlp/models/albert/albert_tokenizer_test.py
+++ b/keras_nlp/models/albert/albert_tokenizer_test.py
@@ -12,6 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import os
+
 import pytest
 
 from keras_nlp.models.albert.albert_tokenizer import AlbertTokenizer
@@ -22,7 +24,9 @@ class AlbertTokenizerTest(TestCase):
     def setUp(self):
         self.init_kwargs = {
             # Generated using create_albert_test_proto.py
-            "proto": str(self.get_test_data_dir() / "albert_test_vocab.spm")
+            "proto": os.path.join(
+                self.get_test_data_dir(), "albert_test_vocab.spm"
+            )
         }
         self.input_data = ["the quick brown fox.", "the earth is round."]
 
@@ -38,8 +42,8 @@ def test_errors_missing_special_tokens(self):
         with self.assertRaises(ValueError):
             AlbertTokenizer(
                 # Generated using create_no_special_token_proto.py
-                proto=str(
-                    self.get_test_data_dir() / "no_special_token_vocab.spm"
+                proto=os.path.join(
+                    self.get_test_data_dir(), "no_special_token_vocab.spm"
                 )
             )
 
diff --git a/keras_nlp/models/deberta_v3/deberta_v3_classifier_test.py b/keras_nlp/models/deberta_v3/deberta_v3_classifier_test.py
index df43196316..0e0ab7642d 100644
--- a/keras_nlp/models/deberta_v3/deberta_v3_classifier_test.py
+++ b/keras_nlp/models/deberta_v3/deberta_v3_classifier_test.py
@@ -12,6 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import os
+
 import pytest
 
 from keras_nlp.models.deberta_v3.deberta_v3_backbone import DebertaV3Backbone
@@ -31,8 +33,8 @@ def setUp(self):
         self.preprocessor = DebertaV3Preprocessor(
             DebertaV3Tokenizer(
                 # Generated using create_deberta_v3_test_proto.py
-                proto=str(
-                    self.get_test_data_dir() / "deberta_v3_test_vocab.spm"
+                proto=os.path.join(
+                    self.get_test_data_dir(), "deberta_v3_test_vocab.spm"
                 )
             ),
             sequence_length=5,
diff --git a/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_preprocessor_test.py b/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_preprocessor_test.py
index af1d0ac190..217980ea59 100644
--- a/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_preprocessor_test.py
+++ b/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_preprocessor_test.py
@@ -12,6 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import os
+
 import pytest
 
 from keras_nlp.models.deberta_v3.deberta_v3_masked_lm_preprocessor import (
@@ -25,7 +27,9 @@ class DebertaV3MaskedLMPreprocessorTest(TestCase):
     def setUp(self):
         self.tokenizer = DebertaV3Tokenizer(
             # Generated using create_deberta_v3_test_proto.py
-            proto=str(self.get_test_data_dir() / "deberta_v3_test_vocab.spm")
+            proto=os.path.join(
+                self.get_test_data_dir(), "deberta_v3_test_vocab.spm"
+            )
         )
         self.init_kwargs = {
             "tokenizer": self.tokenizer,
diff --git a/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_test.py b/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_test.py
index 7734e99e4c..32bf71de13 100644
--- a/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_test.py
+++ b/keras_nlp/models/deberta_v3/deberta_v3_masked_lm_test.py
@@ -12,6 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import os
+
 import pytest
 
 from keras_nlp.models.deberta_v3.deberta_v3_backbone import DebertaV3Backbone
@@ -29,8 +31,8 @@ def setUp(self):
         self.preprocessor = DebertaV3MaskedLMPreprocessor(
             DebertaV3Tokenizer(
                 # Generated using create_deberta_v3_test_proto.py
-                proto=str(
-                    self.get_test_data_dir() / "deberta_v3_test_vocab.spm"
+                proto=os.path.join(
+                    self.get_test_data_dir(), "deberta_v3_test_vocab.spm"
                 )
             ),
             # Simplify our testing by masking every available token.
diff --git a/keras_nlp/models/deberta_v3/deberta_v3_preprocessor_test.py b/keras_nlp/models/deberta_v3/deberta_v3_preprocessor_test.py
index 8a6fcbf452..a50022f3c7 100644
--- a/keras_nlp/models/deberta_v3/deberta_v3_preprocessor_test.py
+++ b/keras_nlp/models/deberta_v3/deberta_v3_preprocessor_test.py
@@ -12,6 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import os
+
 import pytest
 
 from keras_nlp.models.deberta_v3.deberta_v3_preprocessor import (
@@ -25,7 +27,9 @@ class DebertaV3PreprocessorTest(TestCase):
     def setUp(self):
         self.tokenizer = DebertaV3Tokenizer(
             # Generated using create_deberta_v3_test_proto.py
-            proto=str(self.get_test_data_dir() / "deberta_v3_test_vocab.spm")
+            proto=os.path.join(
+                self.get_test_data_dir(), "deberta_v3_test_vocab.spm"
+            )
         )
         self.init_kwargs = {
             "tokenizer": self.tokenizer,
diff --git a/keras_nlp/models/deberta_v3/deberta_v3_tokenizer_test.py b/keras_nlp/models/deberta_v3/deberta_v3_tokenizer_test.py
index cc78808b59..fcaf637974 100644
--- a/keras_nlp/models/deberta_v3/deberta_v3_tokenizer_test.py
+++ b/keras_nlp/models/deberta_v3/deberta_v3_tokenizer_test.py
@@ -12,6 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import os
+
 import pytest
 
 from keras_nlp.models.deberta_v3.deberta_v3_tokenizer import DebertaV3Tokenizer
@@ -21,7 +23,9 @@
 class DebertaV3TokenizerTest(TestCase):
     def setUp(self):
         # Generated using create_deberta_v3_test_proto.py
-        proto = str(self.get_test_data_dir() / "deberta_v3_test_vocab.spm")
+        proto = os.path.join(
+            self.get_test_data_dir(), "deberta_v3_test_vocab.spm"
+        )
         self.tokenizer = DebertaV3Tokenizer(proto=proto)
         self.init_kwargs = {"proto": proto}
         self.input_data = ["the quick brown fox.", "the earth is round."]
@@ -38,8 +42,8 @@ def test_errors_missing_special_tokens(self):
         with self.assertRaises(ValueError):
             DebertaV3Tokenizer(
                 # Generated using create_no_special_token_proto.py
-                proto=str(
-                    self.get_test_data_dir() / "no_special_token_vocab.spm"
+                proto=os.path.join(
+                    self.get_test_data_dir(), "no_special_token_vocab.spm"
                 )
             )
 
diff --git a/keras_nlp/models/f_net/f_net_classifier_test.py b/keras_nlp/models/f_net/f_net_classifier_test.py
index 34211c2e5f..c871fbcc7b 100644
--- a/keras_nlp/models/f_net/f_net_classifier_test.py
+++ b/keras_nlp/models/f_net/f_net_classifier_test.py
@@ -12,6 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import os
+
 import pytest
 
 from keras_nlp.models.f_net.f_net_backbone import FNetBackbone
@@ -27,7 +29,9 @@ def setUp(self):
         self.preprocessor = FNetPreprocessor(
             FNetTokenizer(
                 # Generated using create_f_net_test_proto.py
-                proto=str(self.get_test_data_dir() / "f_net_test_vocab.spm")
+                proto=os.path.join(
+                    self.get_test_data_dir(), "f_net_test_vocab.spm"
+                )
             ),
             sequence_length=5,
         )
diff --git a/keras_nlp/models/f_net/f_net_masked_lm_preprocessor_test.py b/keras_nlp/models/f_net/f_net_masked_lm_preprocessor_test.py
index b18c84ff23..5f72081a0d 100644
--- a/keras_nlp/models/f_net/f_net_masked_lm_preprocessor_test.py
+++ b/keras_nlp/models/f_net/f_net_masked_lm_preprocessor_test.py
@@ -12,6 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import os
+
 import pytest
 
 from keras_nlp.models.f_net.f_net_masked_lm_preprocessor import (
@@ -25,7 +27,7 @@ class FNetMaskedLMPreprocessorTest(TestCase):
     def setUp(self):
         self.tokenizer = FNetTokenizer(
             # Generated using create_f_net_test_proto.py
-            proto=str(self.get_test_data_dir() / "f_net_test_vocab.spm")
+            proto=os.path.join(self.get_test_data_dir(), "f_net_test_vocab.spm")
         )
         self.init_kwargs = {
             "tokenizer": self.tokenizer,
diff --git a/keras_nlp/models/f_net/f_net_masked_lm_test.py b/keras_nlp/models/f_net/f_net_masked_lm_test.py
index 4e2b4f432a..b4931a76fc 100644
--- a/keras_nlp/models/f_net/f_net_masked_lm_test.py
+++ b/keras_nlp/models/f_net/f_net_masked_lm_test.py
@@ -12,6 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import os
+
 import pytest
 
 from keras_nlp.models.f_net.f_net_backbone import FNetBackbone
@@ -29,7 +31,9 @@ def setUp(self):
         self.preprocessor = FNetMaskedLMPreprocessor(
             FNetTokenizer(
                 # Generated using create_f_net_test_proto.py
-                proto=str(self.get_test_data_dir() / "f_net_test_vocab.spm")
+                proto=os.path.join(
+                    self.get_test_data_dir(), "f_net_test_vocab.spm"
+                )
             ),
             # Simplify our testing by masking every available token.
             mask_selection_rate=1.0,
diff --git a/keras_nlp/models/f_net/f_net_preprocessor_test.py b/keras_nlp/models/f_net/f_net_preprocessor_test.py
index 27156cadfd..f67737c828 100644
--- a/keras_nlp/models/f_net/f_net_preprocessor_test.py
+++ b/keras_nlp/models/f_net/f_net_preprocessor_test.py
@@ -12,6 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import os
+
 import pytest
 
 from keras_nlp.models.f_net.f_net_preprocessor import FNetPreprocessor
@@ -23,7 +25,7 @@ class FNetPreprocessorTest(TestCase):
     def setUp(self):
         self.tokenizer = FNetTokenizer(
             # Generated using create_f_net_test_proto.py
-            proto=str(self.get_test_data_dir() / "f_net_test_vocab.spm")
+            proto=os.path.join(self.get_test_data_dir(), "f_net_test_vocab.spm")
         )
         self.init_kwargs = {
             "tokenizer": self.tokenizer,
diff --git a/keras_nlp/models/f_net/f_net_tokenizer_test.py b/keras_nlp/models/f_net/f_net_tokenizer_test.py
index 4d0a830af1..8d3511dee7 100644
--- a/keras_nlp/models/f_net/f_net_tokenizer_test.py
+++ b/keras_nlp/models/f_net/f_net_tokenizer_test.py
@@ -12,6 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import os
+
 import pytest
 
 from keras_nlp.models.f_net.f_net_tokenizer import FNetTokenizer
@@ -22,7 +24,9 @@ class FNetTokenizerTest(TestCase):
     def setUp(self):
         self.init_kwargs = {
             # Generated using create_f_net_test_proto.py
-            "proto": str(self.get_test_data_dir() / "f_net_test_vocab.spm")
+            "proto": os.path.join(
+                self.get_test_data_dir(), "f_net_test_vocab.spm"
+            )
         }
         self.input_data = ["the quick brown fox.", "the earth is round."]
 
@@ -38,8 +42,8 @@ def test_errors_missing_special_tokens(self):
         with self.assertRaises(ValueError):
             FNetTokenizer(
                 # Generated using create_no_special_token_proto.py
-                proto=str(
-                    self.get_test_data_dir() / "no_special_token_vocab.spm"
+                proto=os.path.join(
+                    self.get_test_data_dir(), "no_special_token_vocab.spm"
                 )
             )
 
diff --git a/keras_nlp/models/t5/t5_tokenizer_test.py b/keras_nlp/models/t5/t5_tokenizer_test.py
index 88472650ae..e56195a462 100644
--- a/keras_nlp/models/t5/t5_tokenizer_test.py
+++ b/keras_nlp/models/t5/t5_tokenizer_test.py
@@ -12,6 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import os
+
 from keras_nlp.models.t5.t5_tokenizer import T5Tokenizer
 from keras_nlp.tests.test_case import TestCase
 
@@ -20,7 +22,9 @@ class T5TokenizerTest(TestCase):
     def setUp(self):
         self.init_kwargs = {
             # Generated using create_t5_test_proto.py
-            "proto": str((self.get_test_data_dir() / "t5_test_vocab.spm"))
+            "proto": os.path.join(
+                (self.get_test_data_dir(), "t5_test_vocab.spm")
+            )
         }
         self.input_data = ["the quick brown fox.", "the earth is round."]
 
@@ -36,7 +40,7 @@ def test_errors_missing_special_tokens(self):
         with self.assertRaises(ValueError):
             T5Tokenizer(
                 # Generated using create_no_special_token_proto.py
-                proto=str(
-                    (self.get_test_data_dir() / "no_special_token_vocab.spm")
+                proto=os.path.join(
+                    (self.get_test_data_dir(), "no_special_token_vocab.spm")
                 )
             )
diff --git a/keras_nlp/models/xlm_roberta/xlm_roberta_classifier_test.py b/keras_nlp/models/xlm_roberta/xlm_roberta_classifier_test.py
index f60c8c3033..8255a40cf5 100644
--- a/keras_nlp/models/xlm_roberta/xlm_roberta_classifier_test.py
+++ b/keras_nlp/models/xlm_roberta/xlm_roberta_classifier_test.py
@@ -12,6 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import os
+
 import pytest
 
 from keras_nlp.models.xlm_roberta.xlm_roberta_backbone import XLMRobertaBackbone
@@ -33,8 +35,8 @@ def setUp(self):
         self.preprocessor = XLMRobertaPreprocessor(
             XLMRobertaTokenizer(
                 # Generated using create_xlm_roberta_test_proto.py
-                proto=str(
-                    self.get_test_data_dir() / "xlm_roberta_test_vocab.spm"
+                proto=os.path.join(
+                    self.get_test_data_dir(), "xlm_roberta_test_vocab.spm"
                 )
             ),
             sequence_length=5,
diff --git a/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_preprocessor_test.py b/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_preprocessor_test.py
index b88e57bc99..c1bfc7242a 100644
--- a/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_preprocessor_test.py
+++ b/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_preprocessor_test.py
@@ -12,6 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import os
+
 import pytest
 
 from keras_nlp.models.xlm_roberta.xlm_roberta_masked_lm_preprocessor import (
@@ -27,7 +29,9 @@ class XLMRobertaMaskedLMPreprocessorTest(TestCase):
     def setUp(self):
         self.tokenizer = XLMRobertaTokenizer(
             # Generated using create_xlm_roberta_test_proto.py
-            proto=str(self.get_test_data_dir() / "xlm_roberta_test_vocab.spm")
+            proto=os.path.join(
+                self.get_test_data_dir(), "xlm_roberta_test_vocab.spm"
+            )
         )
         self.init_kwargs = {
             "tokenizer": self.tokenizer,
@@ -47,11 +51,11 @@ def test_preprocessor_basics(self):
             input_data=self.input_data,
             expected_output=(
                 {
-                    "token_ids": [[0, 12, 12, 12, 12, 2, 1, 1, 1, 1, 1, 1]],
+                    "token_ids": [[0, 13, 13, 13, 13, 2, 1, 1, 1, 1, 1, 1]],
                     "padding_mask": [[1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0]],
                     "mask_positions": [[1, 2, 3, 4]],
                 },
-                [[5, 10, 6, 8]],
+                [[6, 11, 7, 9]],
                 [[1.0, 1.0, 1.0, 1.0]],
             ),
         )
@@ -68,7 +72,7 @@ def test_no_masking_zero_rate(self):
             no_mask_preprocessor(input_data),
             (
                 {
-                    "token_ids": [[0, 5, 10, 6, 8, 2, 1, 1, 1, 1, 1, 1]],
+                    "token_ids": [[0, 6, 11, 7, 9, 2, 1, 1, 1, 1, 1, 1]],
                     "padding_mask": [[1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0]],
                     "mask_positions": [[0, 0, 0, 0]],
                 },
diff --git a/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_test.py b/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_test.py
index a3dd58b1a0..bcbafe4ad9 100644
--- a/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_test.py
+++ b/keras_nlp/models/xlm_roberta/xlm_roberta_masked_lm_test.py
@@ -12,6 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import os
+
 import pytest
 
 from keras_nlp.models.xlm_roberta.xlm_roberta_backbone import XLMRobertaBackbone
@@ -33,8 +35,8 @@ def setUp(self):
         self.preprocessor = XLMRobertaMaskedLMPreprocessor(
             XLMRobertaTokenizer(
                 # Generated using create_xlm_roberta_test_proto.py
-                proto=str(
-                    self.get_test_data_dir() / "xlm_roberta_test_vocab.spm"
+                proto=os.path.join(
+                    self.get_test_data_dir(), "xlm_roberta_test_vocab.spm"
                 )
             ),
             # Simplify our testing by masking every available token.
@@ -66,7 +68,7 @@ def test_masked_lm_basics(self):
             cls=XLMRobertaMaskedLM,
             init_kwargs=self.init_kwargs,
             train_data=self.train_data,
-            expected_output_shape=(2, 5, 13),
+            expected_output_shape=(2, 5, 14),
         )
 
     @pytest.mark.large
diff --git a/keras_nlp/models/xlm_roberta/xlm_roberta_preprocessor_test.py b/keras_nlp/models/xlm_roberta/xlm_roberta_preprocessor_test.py
index 48b2140332..3c3bbf2612 100644
--- a/keras_nlp/models/xlm_roberta/xlm_roberta_preprocessor_test.py
+++ b/keras_nlp/models/xlm_roberta/xlm_roberta_preprocessor_test.py
@@ -12,6 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import os
+
 import pytest
 
 from keras_nlp.models.xlm_roberta.xlm_roberta_preprocessor import (
@@ -27,7 +29,9 @@ class XLMRobertaPreprocessorTest(TestCase):
     def setUp(self):
         self.tokenizer = XLMRobertaTokenizer(
             # Generated using create_xlm_roberta_test_proto.py
-            proto=str(self.get_test_data_dir() / "xlm_roberta_test_vocab.spm")
+            proto=os.path.join(
+                self.get_test_data_dir(), "xlm_roberta_test_vocab.spm"
+            )
         )
         self.init_kwargs = {
             "tokenizer": self.tokenizer,
@@ -46,7 +50,7 @@ def test_preprocessor_basics(self):
             input_data=self.input_data,
             expected_output=(
                 {
-                    "token_ids": [[0, 5, 10, 6, 8, 2, 1, 1]],
+                    "token_ids": [[0, 6, 11, 7, 9, 2, 1, 1]],
                     "padding_mask": [[1, 1, 1, 1, 1, 1, 0, 0]],
                 },
                 [1],  # Pass through labels.
diff --git a/keras_nlp/models/xlm_roberta/xlm_roberta_tokenizer_test.py b/keras_nlp/models/xlm_roberta/xlm_roberta_tokenizer_test.py
index f6dd8d2389..9ec205c725 100644
--- a/keras_nlp/models/xlm_roberta/xlm_roberta_tokenizer_test.py
+++ b/keras_nlp/models/xlm_roberta/xlm_roberta_tokenizer_test.py
@@ -12,6 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import os
+
 import pytest
 
 from keras_nlp.models.xlm_roberta.xlm_roberta_tokenizer import (
@@ -24,8 +26,8 @@ class XLMRobertaTokenizerTest(TestCase):
     def setUp(self):
         self.init_kwargs = {
             # Generated using create_xlm_roberta_test_proto.py
-            "proto": str(
-                self.get_test_data_dir() / "xlm_roberta_test_vocab.spm"
+            "proto": os.path.join(
+                self.get_test_data_dir(), "xlm_roberta_test_vocab.spm"
             )
         }
         self.input_data = ["the quick brown fox.", "the earth is round."]
@@ -35,7 +37,7 @@ def test_tokenizer_basics(self):
             cls=XLMRobertaTokenizer,
             init_kwargs=self.init_kwargs,
             input_data=self.input_data,
-            expected_output=[[5, 10, 6, 3], [5, 7, 9, 3]],
+            expected_output=[[6, 11, 7, 2], [6, 8, 10, 2]],
         )
 
     @pytest.mark.large
diff --git a/keras_nlp/tests/test_case.py b/keras_nlp/tests/test_case.py
index 8dad878328..ec29b2add6 100644
--- a/keras_nlp/tests/test_case.py
+++ b/keras_nlp/tests/test_case.py
@@ -420,4 +420,4 @@ def compare(actual, expected):
             tree.map_structure(compare, output, expected_partial_output)
 
     def get_test_data_dir(self):
-        return pathlib.Path(__file__).parent / "test_data"
+        return str(pathlib.Path(__file__).parent / "test_data")
diff --git a/keras_nlp/tokenizers/sentence_piece_tokenizer_test.py b/keras_nlp/tokenizers/sentence_piece_tokenizer_test.py
index 18ca270914..f3b39711bd 100644
--- a/keras_nlp/tokenizers/sentence_piece_tokenizer_test.py
+++ b/keras_nlp/tokenizers/sentence_piece_tokenizer_test.py
@@ -12,6 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import os
+
 import tensorflow as tf
 
 from keras_nlp.tests.test_case import TestCase
@@ -21,8 +23,8 @@
 class SentencePieceTokenizerTest(TestCase):
     def setUp(self):
         super().setUp()
-        self.proto = str(
-            self.get_test_data_dir() / "tokenizer_test_vocab.spm"
+        self.proto = os.path.join(
+            self.get_test_data_dir(), "tokenizer_test_vocab.spm"
         )
 
     def test_tokenize(self):

From 234b90869f5ef5f4ddf71d356e09373e4aa3c6b2 Mon Sep 17 00:00:00 2001
From: Tirth Patel <tirthasheshpatel@gmail.com>
Date: Thu, 26 Oct 2023 00:37:30 +0000
Subject: [PATCH 13/14] Fix T5 Tokenizer test failures

---
 keras_nlp/models/t5/t5_tokenizer_test.py | 6 ++----
 1 file changed, 2 insertions(+), 4 deletions(-)

diff --git a/keras_nlp/models/t5/t5_tokenizer_test.py b/keras_nlp/models/t5/t5_tokenizer_test.py
index f7d076b434..4d19f96140 100644
--- a/keras_nlp/models/t5/t5_tokenizer_test.py
+++ b/keras_nlp/models/t5/t5_tokenizer_test.py
@@ -24,9 +24,7 @@ class T5TokenizerTest(TestCase):
     def setUp(self):
         self.init_kwargs = {
             # Generated using create_t5_test_proto.py
-            "proto": os.path.join(
-                (self.get_test_data_dir(), "t5_test_vocab.spm")
-            )
+            "proto": os.path.join(self.get_test_data_dir(), "t5_test_vocab.spm")
         }
         self.input_data = ["the quick brown fox.", "the earth is round."]
 
@@ -43,7 +41,7 @@ def test_errors_missing_special_tokens(self):
             T5Tokenizer(
                 # Generated using create_no_special_token_proto.py
                 proto=os.path.join(
-                    (self.get_test_data_dir(), "no_special_token_vocab.spm")
+                    self.get_test_data_dir(), "no_special_token_vocab.spm"
                 )
             )
 

From 75ead27a83a110c2a9f70cf82242f31cfdad72d4 Mon Sep 17 00:00:00 2001
From: Tirth Patel <tirthasheshpatel@gmail.com>
Date: Thu, 26 Oct 2023 00:42:32 +0000
Subject: [PATCH 14/14] Fix a merge artifact

---
 keras_nlp/models/t5/t5_tokenizer_test.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/keras_nlp/models/t5/t5_tokenizer_test.py b/keras_nlp/models/t5/t5_tokenizer_test.py
index 4d19f96140..be07b486e4 100644
--- a/keras_nlp/models/t5/t5_tokenizer_test.py
+++ b/keras_nlp/models/t5/t5_tokenizer_test.py
@@ -50,6 +50,7 @@ def test_smallest_preset(self):
         for preset in T5Tokenizer.presets:
             self.run_preset_test(
                 cls=T5Tokenizer,
+                preset=preset,
                 input_data=["The quick brown fox."],
                 expected_output=[[1996, 4248, 2829, 4419, 1012]],
             )