Merge branch 'main' into main

Former-commit-id: 7be442f37d53a0c6324728fa1fa8e2c84d7f0fa5

src/llamafactory/data/processors/supervised.py

@@ -1,14 +1,27 @@
+# Copyright 2024 the LlamaFactory team.
+#
+# 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
+#
+#     http://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 collections import defaultdict
 from typing import TYPE_CHECKING, Any, Dict, List, Optional, Sequence, Tuple
 
 from ...extras.constants import IGNORE_INDEX
 from ...extras.logging import get_logger
-from .processor_utils import get_paligemma_token_type_ids, get_pixel_values, greedy_knapsack
+from .processor_utils import get_paligemma_token_type_ids, get_pixel_values, greedy_knapsack, infer_seqlen
 
 
 if TYPE_CHECKING:
-    from transformers import ProcessorMixin
-    from transformers.tokenization_utils import PreTrainedTokenizer
+    from transformers import PreTrainedTokenizer, ProcessorMixin
 
     from ...hparams import DataArguments
     from ..template import Template
@@ -38,10 +51,17 @@ def _encode_supervised_example(
         input_ids += [image_token_id] * getattr(processor, "image_seq_length")
         labels += [IGNORE_INDEX] * getattr(processor, "image_seq_length")
 
-    encoded_pairs = template.encode_multiturn(
-        tokenizer, messages, system, tools, data_args.cutoff_len, data_args.reserved_label_len
-    )
+    encoded_pairs = template.encode_multiturn(tokenizer, messages, system, tools)
+    total_length = 1 if template.efficient_eos else 0
     for turn_idx, (source_ids, target_ids) in enumerate(encoded_pairs):
+        if total_length >= data_args.cutoff_len:
+            break
+
+        source_len, target_len = infer_seqlen(len(source_ids), len(target_ids), data_args.cutoff_len - total_length)
+        source_ids = source_ids[:source_len]
+        target_ids = target_ids[:target_len]
+        total_length += source_len + target_len
+
         if data_args.train_on_prompt:
             source_mask = source_ids
         elif turn_idx != 0 and template.efficient_eos: