Remove dead code

keras_nlp/src/models/albert/albert_masked_lm_preprocessor.py

@@ -15,11 +15,11 @@
 from absl import logging
 
 from keras_nlp.src.api_export import keras_nlp_export
+from keras_nlp.src.backend import keras
 from keras_nlp.src.layers.preprocessing.masked_lm_mask_generator import (
     MaskedLMMaskGenerator,
 )
 from keras_nlp.src.models.albert.albert_preprocessor import AlbertPreprocessor
-from keras_nlp.src.utils.keras_utils import pack_x_y_sample_weight
 
 
 @keras_nlp_export("keras_nlp.models.AlbertMaskedLMPreprocessor")
@@ -191,4 +191,4 @@ def call(self, x, y=None, sample_weight=None):
         }
         y = masker_outputs["mask_ids"]
         sample_weight = masker_outputs["mask_weights"]
-        return pack_x_y_sample_weight(x, y, sample_weight)
+        return keras.utils.pack_x_y_sample_weight(x, y, sample_weight)

keras_nlp/src/models/albert/albert_preprocessor.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 from keras_nlp.src.api_export import keras_nlp_export
+from keras_nlp.src.backend import keras
 from keras_nlp.src.layers.preprocessing.multi_segment_packer import (
     MultiSegmentPacker,
 )
@@ -21,7 +22,6 @@
 from keras_nlp.src.utils.keras_utils import (
     convert_inputs_to_list_of_tensor_segments,
 )
-from keras_nlp.src.utils.keras_utils import pack_x_y_sample_weight
 
 
 @keras_nlp_export("keras_nlp.models.AlbertPreprocessor")
@@ -191,7 +191,7 @@ def call(self, x, y=None, sample_weight=None):
             "segment_ids": segment_ids,
             "padding_mask": token_ids != self.tokenizer.pad_token_id,
         }
-        return pack_x_y_sample_weight(x, y, sample_weight)
+        return keras.utils.pack_x_y_sample_weight(x, y, sample_weight)
 
     @property
     def sequence_length(self):

keras_nlp/src/models/bart/bart_preprocessor.py

@@ -14,13 +14,13 @@
 
 
 from keras_nlp.src.api_export import keras_nlp_export
+from keras_nlp.src.backend import keras
 from keras_nlp.src.layers.preprocessing.start_end_packer import StartEndPacker
 from keras_nlp.src.models.bart.bart_tokenizer import BartTokenizer
 from keras_nlp.src.models.preprocessor import Preprocessor
 from keras_nlp.src.utils.keras_utils import (
     convert_inputs_to_list_of_tensor_segments,
 )
-from keras_nlp.src.utils.keras_utils import pack_x_y_sample_weight
 
 
 @keras_nlp_export("keras_nlp.models.BartPreprocessor")
@@ -231,7 +231,7 @@ def call(
             "decoder_padding_mask": decoder_padding_mask,
         }
 
-        return pack_x_y_sample_weight(x, y, sample_weight)
+        return keras.utils.pack_x_y_sample_weight(x, y, sample_weight)
 
     def get_config(self):
         config = super().get_config()

keras_nlp/src/models/bart/bart_seq_2_seq_lm_preprocessor.py

@@ -23,12 +23,12 @@
 from absl import logging
 
 from keras_nlp.src.api_export import keras_nlp_export
+from keras_nlp.src.backend import keras
 from keras_nlp.src.backend import ops
 from keras_nlp.src.models.bart.bart_preprocessor import BartPreprocessor
 from keras_nlp.src.utils.keras_utils import (
     convert_inputs_to_list_of_tensor_segments,
 )
-from keras_nlp.src.utils.keras_utils import pack_x_y_sample_weight
 
 
 @keras_nlp_export("keras_nlp.models.BartSeq2SeqLMPreprocessor")
@@ -170,7 +170,7 @@ def call(
         # left (i.e., the next token).
         y = decoder_token_ids[..., 1:]
         sample_weight = decoder_padding_mask[..., 1:]
-        return pack_x_y_sample_weight(x, y, sample_weight)
+        return keras.utils.pack_x_y_sample_weight(x, y, sample_weight)
 
     def generate_preprocess(
         self,

keras_nlp/src/models/bert/bert_masked_lm_preprocessor.py

@@ -15,11 +15,11 @@
 from absl import logging
 
 from keras_nlp.src.api_export import keras_nlp_export
+from keras_nlp.src.backend import keras
 from keras_nlp.src.layers.preprocessing.masked_lm_mask_generator import (
     MaskedLMMaskGenerator,
 )
 from keras_nlp.src.models.bert.bert_preprocessor import BertPreprocessor
-from keras_nlp.src.utils.keras_utils import pack_x_y_sample_weight
 
 
 @keras_nlp_export("keras_nlp.models.BertMaskedLMPreprocessor")
@@ -183,7 +183,7 @@ def call(self, x, y=None, sample_weight=None):
         }
         y = masker_outputs["mask_ids"]
         sample_weight = masker_outputs["mask_weights"]
-        return pack_x_y_sample_weight(x, y, sample_weight)
+        return keras.utils.pack_x_y_sample_weight(x, y, sample_weight)
 
     def get_config(self):
         config = super().get_config()

keras_nlp/src/models/bert/bert_preprocessor.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 from keras_nlp.src.api_export import keras_nlp_export
+from keras_nlp.src.backend import keras
 from keras_nlp.src.layers.preprocessing.multi_segment_packer import (
     MultiSegmentPacker,
 )
@@ -21,7 +22,6 @@
 from keras_nlp.src.utils.keras_utils import (
     convert_inputs_to_list_of_tensor_segments,
 )
-from keras_nlp.src.utils.keras_utils import pack_x_y_sample_weight
 
 
 @keras_nlp_export("keras_nlp.models.BertPreprocessor")
@@ -159,7 +159,7 @@ def call(self, x, y=None, sample_weight=None):
             "segment_ids": segment_ids,
             "padding_mask": token_ids != self.tokenizer.pad_token_id,
         }
-        return pack_x_y_sample_weight(x, y, sample_weight)
+        return keras.utils.pack_x_y_sample_weight(x, y, sample_weight)
 
     def get_config(self):
         config = super().get_config()

keras_nlp/src/models/bloom/bloom_causal_lm_preprocessor.py

@@ -22,12 +22,12 @@
 from absl import logging
 
 from keras_nlp.src.api_export import keras_nlp_export
+from keras_nlp.src.backend import keras
 from keras_nlp.src.backend import ops
 from keras_nlp.src.models.bloom.bloom_preprocessor import BloomPreprocessor
 from keras_nlp.src.utils.keras_utils import (
     convert_inputs_to_list_of_tensor_segments,
 )
-from keras_nlp.src.utils.keras_utils import pack_x_y_sample_weight
 
 
 @keras_nlp_export("keras_nlp.models.BloomCausalLMPreprocessor")
@@ -130,7 +130,7 @@ def call(
         }
         # Target `y` will be the next token.
         y, sample_weight = token_ids[..., 1:], padding_mask[..., 1:]
-        return pack_x_y_sample_weight(x, y, sample_weight)
+        return keras.utils.pack_x_y_sample_weight(x, y, sample_weight)
 
     def generate_preprocess(
         self,

keras_nlp/src/models/bloom/bloom_preprocessor.py

@@ -14,13 +14,13 @@
 
 
 from keras_nlp.src.api_export import keras_nlp_export
+from keras_nlp.src.backend import keras
 from keras_nlp.src.layers.preprocessing.start_end_packer import StartEndPacker
 from keras_nlp.src.models.bloom.bloom_tokenizer import BloomTokenizer
 from keras_nlp.src.models.preprocessor import Preprocessor
 from keras_nlp.src.utils.keras_utils import (
     convert_inputs_to_list_of_tensor_segments,
 )
-from keras_nlp.src.utils.keras_utils import pack_x_y_sample_weight
 
 
 @keras_nlp_export("keras_nlp.models.BloomPreprocessor")
@@ -159,7 +159,7 @@ def call(
             "token_ids": token_ids,
             "padding_mask": padding_mask,
         }
-        return pack_x_y_sample_weight(x, y, sample_weight)
+        return keras.utils.pack_x_y_sample_weight(x, y, sample_weight)
 
     def get_config(self):
         config = super().get_config()

keras_nlp/src/models/deberta_v3/deberta_v3_masked_lm_preprocessor.py

@@ -15,13 +15,13 @@
 from absl import logging
 
 from keras_nlp.src.api_export import keras_nlp_export
+from keras_nlp.src.backend import keras
 from keras_nlp.src.layers.preprocessing.masked_lm_mask_generator import (
     MaskedLMMaskGenerator,
 )
 from keras_nlp.src.models.deberta_v3.deberta_v3_preprocessor import (
     DebertaV3Preprocessor,
 )
-from keras_nlp.src.utils.keras_utils import pack_x_y_sample_weight
 
 
 @keras_nlp_export("keras_nlp.models.DebertaV3MaskedLMPreprocessor")
@@ -188,4 +188,4 @@ def call(self, x, y=None, sample_weight=None):
         }
         y = masker_outputs["mask_ids"]
         sample_weight = masker_outputs["mask_weights"]
-        return pack_x_y_sample_weight(x, y, sample_weight)
+        return keras.utils.pack_x_y_sample_weight(x, y, sample_weight)

keras_nlp/src/models/deberta_v3/deberta_v3_preprocessor.py

@@ -14,6 +14,7 @@
 
 
 from keras_nlp.src.api_export import keras_nlp_export
+from keras_nlp.src.backend import keras
 from keras_nlp.src.layers.preprocessing.multi_segment_packer import (
     MultiSegmentPacker,
 )
@@ -24,7 +25,6 @@
 from keras_nlp.src.utils.keras_utils import (
     convert_inputs_to_list_of_tensor_segments,
 )
-from keras_nlp.src.utils.keras_utils import pack_x_y_sample_weight
 
 
 @keras_nlp_export("keras_nlp.models.DebertaV3Preprocessor")
@@ -191,7 +191,7 @@ def call(self, x, y=None, sample_weight=None):
             "token_ids": token_ids,
             "padding_mask": token_ids != self.tokenizer.pad_token_id,
         }
-        return pack_x_y_sample_weight(x, y, sample_weight)
+        return keras.utils.pack_x_y_sample_weight(x, y, sample_weight)
 
     @property
     def sequence_length(self):

keras_nlp/src/models/distil_bert/distil_bert_masked_lm_preprocessor.py

@@ -15,13 +15,13 @@
 from absl import logging
 
 from keras_nlp.src.api_export import keras_nlp_export
+from keras_nlp.src.backend import keras
 from keras_nlp.src.layers.preprocessing.masked_lm_mask_generator import (
     MaskedLMMaskGenerator,
 )
 from keras_nlp.src.models.distil_bert.distil_bert_preprocessor import (
     DistilBertPreprocessor,
 )
-from keras_nlp.src.utils.keras_utils import pack_x_y_sample_weight
 
 
 @keras_nlp_export("keras_nlp.models.DistilBertMaskedLMPreprocessor")
@@ -179,7 +179,7 @@ def call(self, x, y=None, sample_weight=None):
         }
         y = masker_outputs["mask_ids"]
         sample_weight = masker_outputs["mask_weights"]
-        return pack_x_y_sample_weight(x, y, sample_weight)
+        return keras.utils.pack_x_y_sample_weight(x, y, sample_weight)
 
     def get_config(self):
         config = super().get_config()

keras_nlp/src/models/distil_bert/distil_bert_preprocessor.py

@@ -14,6 +14,7 @@
 
 
 from keras_nlp.src.api_export import keras_nlp_export
+from keras_nlp.src.backend import keras
 from keras_nlp.src.layers.preprocessing.multi_segment_packer import (
     MultiSegmentPacker,
 )
@@ -24,7 +25,6 @@
 from keras_nlp.src.utils.keras_utils import (
     convert_inputs_to_list_of_tensor_segments,
 )
-from keras_nlp.src.utils.keras_utils import pack_x_y_sample_weight
 
 
 @keras_nlp_export("keras_nlp.models.DistilBertPreprocessor")
@@ -150,7 +150,7 @@ def call(self, x, y=None, sample_weight=None):
             "token_ids": token_ids,
             "padding_mask": token_ids != self.tokenizer.pad_token_id,
         }
-        return pack_x_y_sample_weight(x, y, sample_weight)
+        return keras.utils.pack_x_y_sample_weight(x, y, sample_weight)
 
     def get_config(self):
         config = super().get_config()

keras_nlp/src/models/electra/electra_preprocessor.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 from keras_nlp.src.api_export import keras_nlp_export
+from keras_nlp.src.backend import keras
 from keras_nlp.src.layers.preprocessing.multi_segment_packer import (
     MultiSegmentPacker,
 )
@@ -21,7 +22,6 @@
 from keras_nlp.src.utils.keras_utils import (
     convert_inputs_to_list_of_tensor_segments,
 )
-from keras_nlp.src.utils.keras_utils import pack_x_y_sample_weight
 
 
 @keras_nlp_export("keras_nlp.models.ElectraPreprocessor")
@@ -150,4 +150,4 @@ def call(self, x, y=None, sample_weight=None):
             "segment_ids": segment_ids,
             "padding_mask": token_ids != self.tokenizer.pad_token_id,
         }
-        return pack_x_y_sample_weight(x, y, sample_weight)
+        return keras.utils.pack_x_y_sample_weight(x, y, sample_weight)

keras_nlp/src/models/f_net/f_net_masked_lm_preprocessor.py

@@ -15,11 +15,11 @@
 from absl import logging
 
 from keras_nlp.src.api_export import keras_nlp_export
+from keras_nlp.src.backend import keras
 from keras_nlp.src.layers.preprocessing.masked_lm_mask_generator import (
     MaskedLMMaskGenerator,
 )
 from keras_nlp.src.models.f_net.f_net_preprocessor import FNetPreprocessor
-from keras_nlp.src.utils.keras_utils import pack_x_y_sample_weight
 
 
 @keras_nlp_export("keras_nlp.models.FNetMaskedLMPreprocessor")
@@ -193,4 +193,4 @@ def call(self, x, y=None, sample_weight=None):
         }
         y = masker_outputs["mask_ids"]
         sample_weight = masker_outputs["mask_weights"]
-        return pack_x_y_sample_weight(x, y, sample_weight)
+        return keras.utils.pack_x_y_sample_weight(x, y, sample_weight)

keras_nlp/src/models/f_net/f_net_preprocessor.py

@@ -14,6 +14,7 @@
 
 
 from keras_nlp.src.api_export import keras_nlp_export
+from keras_nlp.src.backend import keras
 from keras_nlp.src.layers.preprocessing.multi_segment_packer import (
     MultiSegmentPacker,
 )
@@ -22,7 +23,6 @@
 from keras_nlp.src.utils.keras_utils import (
     convert_inputs_to_list_of_tensor_segments,
 )
-from keras_nlp.src.utils.keras_utils import pack_x_y_sample_weight
 
 
 @keras_nlp_export("keras_nlp.models.FNetPreprocessor")
@@ -162,7 +162,7 @@ def call(self, x, y=None, sample_weight=None):
             "token_ids": token_ids,
             "segment_ids": segment_ids,
         }
-        return pack_x_y_sample_weight(x, y, sample_weight)
+        return keras.utils.pack_x_y_sample_weight(x, y, sample_weight)
 
     @property
     def sequence_length(self):

keras_nlp/src/models/falcon/falcon_causal_lm_preprocessor.py

@@ -22,12 +22,12 @@
 from absl import logging
 
 from keras_nlp.src.api_export import keras_nlp_export
+from keras_nlp.src.backend import keras
 from keras_nlp.src.backend import ops
 from keras_nlp.src.models.falcon.falcon_preprocessor import FalconPreprocessor
 from keras_nlp.src.utils.keras_utils import (
     convert_inputs_to_list_of_tensor_segments,
 )
-from keras_nlp.src.utils.keras_utils import pack_x_y_sample_weight
 
 
 @keras_nlp_export("keras_nlp.models.FalconCausalLMPreprocessor")
@@ -130,7 +130,7 @@ def call(
         }
         # Target `y` will be the next token.
         y, sample_weight = token_ids[..., 1:], padding_mask[..., 1:]
-        return pack_x_y_sample_weight(x, y, sample_weight)
+        return keras.utils.pack_x_y_sample_weight(x, y, sample_weight)
 
     def generate_preprocess(
         self,

keras_nlp/src/models/falcon/falcon_preprocessor.py

@@ -14,13 +14,13 @@
 
 
 from keras_nlp.src.api_export import keras_nlp_export
+from keras_nlp.src.backend import keras
 from keras_nlp.src.layers.preprocessing.start_end_packer import StartEndPacker
 from keras_nlp.src.models.falcon.falcon_tokenizer import FalconTokenizer
 from keras_nlp.src.models.preprocessor import Preprocessor
 from keras_nlp.src.utils.keras_utils import (
     convert_inputs_to_list_of_tensor_segments,
 )
-from keras_nlp.src.utils.keras_utils import pack_x_y_sample_weight
 
 
 @keras_nlp_export("keras_nlp.models.FalconPreprocessor")
@@ -161,7 +161,7 @@ def call(
             "token_ids": token_ids,
             "padding_mask": padding_mask,
         }
-        return pack_x_y_sample_weight(x, y, sample_weight)
+        return keras.utils.pack_x_y_sample_weight(x, y, sample_weight)
 
     def get_config(self):
         config = super().get_config()