[Ready] align sft formats & new ops

configs/config_all.yaml

@@ -61,30 +61,26 @@ process:
   - clean_links_mapper:                                     # remove web links from text.
   - clean_copyright_mapper:                                 # remove copyright comments.
   - expand_macro_mapper:                                    # expand macro definitions in Latex text.
-  - extract_qa_mapper:                                      # mapper to extract question and answer pair from text.
-      hf_model: 'alibaba-pai/pai-qwen1_5-7b-doc2qa'           # model name on huggingface to extract question and answer pair.
-      pattern: null                                           # regular expression pattern to search for within text.
-      qa_format: 'chatml'                                     # Output format of question and answer pair.
-      enable_vllm: true                                       # Whether to use vllm for inference acceleration.
-      tensor_parallel_size: null                              # It is only valid when enable_vllm is True. The number of GPUs to use for distributed execution with tensor parallelism.
-      max_model_len: null                                     # It is only valid when enable_vllm is True. Model context length. If unspecified, will be automatically derived from the model config.
-      max_num_seqs: 256                                       # It is only valid when enable_vllm is True. Maximum number of sequences to be processed in a single iteration.
-      sampling_params: {}                                     # Sampling parameters for text generation. e.g {'temperature': 0.9, 'top_p': 0.95}
   - fix_unicode_mapper:                                     # fix unicode errors in text.
-  - generate_instruction_mapper:                            # generate new instruction text data.
-      hf_model: 'Qwen/Qwen-7B-Chat'                           # model name on huggingface to generate instruction.
-      seed_file: 'demos/data/demo-dataset-chatml.jsonl'       # Seed file as instruction samples to generate new instructions, chatml format.
-      instruct_num: 3                                         # the number of generated samples.
-      similarity_threshold: 0.7                               # the similarity score threshold between the generated samples and the seed samples.Range from 0 to 1. Samples with similarity score less than this threshold will be kept.
-      prompt_template: null                                   # Prompt template for generate samples. Please make sure the template contains "{augmented_data}", which corresponds to the augmented samples.
-      qa_pair_template: null                                  # Prompt template for generate question and answer pair description. Please make sure the template contains two "{}" to format question and answer. Default: '【问题】\n{}\n【回答】\n{}\n'.
-      example_template: null                                  # Prompt template for generate examples. Please make sure the template contains "{qa_pairs}", which corresponds to the question and answer pair description generated by param `qa_pair_template`.
-      qa_extraction_pattern: null                             # Regular expression pattern for parsing question and answer from model response.
-      enable_vllm: true                                       # Whether to use vllm for inference acceleration.
-      tensor_parallel_size: null                              # It is only valid when enable_vllm is True. The number of GPUs to use for distributed execution with tensor parallelism.
-      max_model_len: null                                     # It is only valid when enable_vllm is True. Model context length. If unspecified, will be automatically derived from the model config.
-      max_num_seqs: 256                                       # It is only valid when enable_vllm is True. Maximum number of sequences to be processed in a single iteration.
+  - generate_qa_from_examples_mapper:                       # mapper to generate question and answer pairs from examples.
+      hf_model: 'Qwen/Qwen2.5-7B-Instruct'                    # Model name on huggingface to generate question and answer pairs.
+      seed_file: 'demos/data/demo-dataset-chatml.jsonl'       # Path to the seed file in chatml format.
+      instruct_num: 3                                         # The number of randomly selected seed examples.
+      similarity_threshold: 0.7                               # the similarity score threshold between the generated samples and the seed examples. Range from 0 to 1. Samples with similarity score less than this threshold will be kept.
+      system_prompt: null                                     # System prompt for guiding the generation task.
+      input_template: null                                    # Template for building the input prompt.
+      example_template: null                                  # Template for formatting each QA example.
+      qa_pair_template: null                                  # Template for formatting a single QA pair within each example.
+      output_pattern: null                                    # Regular expression pattern to extract questions and answers from model response.
+      enable_vllm: false                                      # Whether to use vllm for inference acceleration.
+      model_params: null                                      # Parameters for initializing the model.
       sampling_params: {}                                     # Sampling parameters for text generation. e.g {'temperature': 0.9, 'top_p': 0.95}
+  - generate_qa_from_text_mapper:                           # mapper to generate question and answer pairs from text.
+      hf_model: 'alibaba-pai/pai-qwen1_5-7b-doc2qa'           # Model name on huggingface to generate question and answer pairs.
+      output_pattern: null                                    # Regular expression pattern to extract questions and answers from model response.
+      enable_vllm: false                                      # Whether to use vllm for inference acceleration.
+      model_params: null                                      # Parameters for initializing the model.
+      sampling_params: null                                   # Sampling parameters for text generation. e.g {'temperature': 0.9, 'top_p': 0.95}
   - image_blur_mapper:                                      # mapper to blur images.
       p: 0.2                                                  # probability of the image being blured
       blur_type: 'gaussian'                                   # type of blur kernel, including ['mean', 'box', 'gaussian']
@@ -146,13 +142,17 @@ process:
       delete_random_char: false                               # whether to open the augmentation method of deleting random characters from the original texts. e.g. "这里一共有5种不同的数据增强方法" --> "这里一共有5种不同的数据增强"
       swap_random_char: false                                 # whether to open the augmentation method of swapping random contiguous characters in the original texts. e.g. "这里一共有5种不同的数据增强方法" --> "这里一共有5种不同的数据强增方法"
       replace_equivalent_num: false                           # whether to open the augmentation method of replacing random numbers with their equivalent representations in the original texts. **Notice**: Only for numbers for now. e.g. "这里一共有5种不同的数据增强方法" --> "这里一共有伍种不同的数据增强方法"
-  - optimize_instruction_mapper:                            # optimize instruction.
-      hf_model: 'alibaba-pai/Qwen2-7B-Instruct-Refine'        # model name on huggingface to optimize instruction
-      enable_vllm: true                                       # whether to use vllm for inference acceleration.
-      tensor_parallel_size: null                              # It is only valid when enable_vllm is True. The number of GPUs to use for distributed execution with tensor parallelism.
-      max_model_len: null                                     # It is only valid when enable_vllm is True. Model context length. If unspecified, will be automatically derived from the model config.
-      max_num_seqs: 256                                       # It is only valid when enable_vllm is True. Maximum number of sequences to be processed in a single iteration.
-      sampling_params: {}                                     # Sampling parameters for text generation. e.g {'temperature': 0.9, 'top_p': 0.95}
+  - optimize_qa_mapper:                                     # optimize question-answer pairs.
+      hf_model: 'Qwen/Qwen2.5-7B-Instruct'                    # model name on huggingface.
+      system_prompt: null                                     # System prompt for guiding the optimization task.
+      input_template: null                                    # Template for building the input for the model.
+      qa_pair_template: null                                  # Template for formatting the question and answer pair.
+      output_pattern: null                                    # Regular expression pattern to extract question and answer from model response.
+      enable_vllm: false                                      # whether to use vllm for inference acceleration.
+      model_params: null                                      # Parameters for initializing the model.
+      sampling_params: null                                   # Sampling parameters for text generation. e.g {'temperature': 0.9, 'top_p': 0.95}
+  - optimize_query_mapper:                                  # optimize query in question-answer pairs.
+  - optimize_response_mapper:                               # optimize response in question-answer pairs.
   - punctuation_normalization_mapper:                       # normalize unicode punctuations to English punctuations.
   - remove_bibliography_mapper:                             # remove bibliography from Latex text.
   - remove_comments_mapper:                                 # remove comments from Latex text, code, etc.

data_juicer/core/data.py

@@ -246,16 +246,23 @@ def map(self, *args, **kargs):
 
         if inspect.ismethod(called_func):
             # batched is required for fault-tolerant or batched OP
-            if not called_func.__self__.turbo or hasattr(
+            if callable(getattr(
                     called_func.__self__,
-                    'is_batched_op') and called_func.__self__.is_batched_op():
+                    'is_batched_op')) and called_func.__self__.is_batched_op(
+                    ) or not called_func.__self__.turbo:
                 kargs['batched'] = True
                 kargs['batch_size'] = kargs.pop('batch_size', 1) if hasattr(
                     called_func.__self__, 'is_batched_op'
                 ) and called_func.__self__.is_batched_op() else 1
             else:
                 kargs['batched'] = False
 
+            # rank is required for cuda model loading
+            if callable(
+                    getattr(called_func.__self__,
+                            'use_cuda')) and called_func.__self__.use_cuda():
+                kargs['with_rank'] = True
+
         if 'new_fingerprint' not in kargs or kargs['new_fingerprint'] is None:
             new_fingerprint = generate_fingerprint(self, *args, **kargs)
             kargs['new_fingerprint'] = new_fingerprint
@@ -300,10 +307,12 @@ def filter(self, *args, **kargs):
             called_func = called_func.__wrapped__
 
         # Batched is always required for fault tolerance
-        if inspect.ismethod(
-                called_func) and called_func.__self__.is_batched_op():
-            kargs['batched'] = True
-            kargs['batch_size'] = kargs.pop('batch_size', 1)
+        if inspect.ismethod(called_func):
+            if callable(getattr(
+                    called_func.__self__,
+                    'is_batched_op')) and called_func.__self__.is_batched_op():
+                kargs['batched'] = True
+                kargs['batch_size'] = kargs.pop('batch_size', 1)
 
         if 'new_fingerprint' not in kargs or kargs['new_fingerprint'] is None:
             new_fingerprint = generate_fingerprint(self, *args, **kargs)

data_juicer/ops/base_op.py

@@ -2,6 +2,7 @@
 import traceback
 from functools import wraps
 
+import numpy as np
 import pyarrow as pa
 from loguru import logger
 
@@ -133,6 +134,11 @@ def __init__(self, *args, **kwargs):
         self.image_key = kwargs.get('image_key', 'images')
         self.audio_key = kwargs.get('audio_key', 'audios')
         self.video_key = kwargs.get('video_key', 'videos')
+
+        self.query_key = kwargs.get('query_key', 'query')
+        self.response_key = kwargs.get('response_key', 'response')
+        self.history_key = kwargs.get('history_key', 'history')
+
         self.batch_size = kwargs.get('batch_size', 1000)
 
         # whether the model can be accelerated using cuda
@@ -210,6 +216,9 @@ def run(self, dataset):
             dataset = NestedDataset(dataset)
         return dataset
 
+    def empty_history(self):
+        return np.empty((0, 0), dtype=str)
+
 
 class Mapper(OP):
 

data_juicer/ops/common/__init__.py

@@ -5,12 +5,7 @@
 from .special_characters import SPECIAL_CHARACTERS
 
 __all__ = [
-    'get_sentences_from_document',
-    'get_words_from_document',
-    'merge_on_whitespace_tab_newline',
-    'split_on_newline_tab_whitespace',
-    'split_on_whitespace',
-    'strip',
-    'words_augmentation',
-    'words_refinement',
+    'get_sentences_from_document', 'get_words_from_document',
+    'merge_on_whitespace_tab_newline', 'split_on_newline_tab_whitespace',
+    'split_on_whitespace', 'strip', 'words_augmentation', 'words_refinement'
 ]

data_juicer/ops/deduplicator/__init__.py

@@ -9,7 +9,8 @@
 from .video_deduplicator import VideoDeduplicator
 
 __all__ = [
-    'VideoDeduplicator', 'RayBasicDeduplicator', 'DocumentMinhashDeduplicator',
-    'RayImageDeduplicator', 'RayDocumentDeduplicator', 'DocumentDeduplicator',
-    'ImageDeduplicator', 'DocumentSimhashDeduplicator', 'RayVideoDeduplicator'
+    'DocumentDeduplicator', 'DocumentMinhashDeduplicator',
+    'DocumentSimhashDeduplicator', 'ImageDeduplicator', 'RayBasicDeduplicator',
+    'RayDocumentDeduplicator', 'RayImageDeduplicator', 'RayVideoDeduplicator',
+    'VideoDeduplicator'
 ]

data_juicer/ops/filter/__init__.py

@@ -44,21 +44,20 @@
 from .words_num_filter import WordsNumFilter
 
 __all__ = [
-    'ImageTextSimilarityFilter', 'VideoAspectRatioFilter',
-    'ImageTextMatchingFilter', 'ImageNSFWFilter', 'TokenNumFilter',
-    'TextLengthFilter', 'SpecifiedNumericFieldFilter', 'AudioNMFSNRFilter',
-    'VideoAestheticsFilter', 'PerplexityFilter', 'PhraseGroundingRecallFilter',
-    'MaximumLineLengthFilter', 'AverageLineLengthFilter',
-    'SpecifiedFieldFilter', 'VideoTaggingFromFramesFilter',
-    'TextEntityDependencyFilter', 'VideoResolutionFilter',
-    'AlphanumericFilter', 'ImageWatermarkFilter', 'ImageAestheticsFilter',
-    'AudioSizeFilter', 'StopWordsFilter', 'CharacterRepetitionFilter',
-    'ImageShapeFilter', 'VideoDurationFilter', 'TextActionFilter',
-    'VideoOcrAreaRatioFilter', 'VideoNSFWFilter', 'SpecialCharactersFilter',
-    'VideoFramesTextSimilarityFilter', 'ImageAspectRatioFilter',
-    'AudioDurationFilter', 'LanguageIDScoreFilter', 'SuffixFilter',
-    'ImageSizeFilter', 'VideoWatermarkFilter', 'WordsNumFilter',
-    'ImageFaceCountFilter', 'ImageFaceRatioFilter', 'FlaggedWordFilter',
-    'WordRepetitionFilter', 'VideoMotionScoreFilter',
-    'ImagePairSimilarityFilter'
+    'AlphanumericFilter', 'AudioDurationFilter', 'AudioNMFSNRFilter',
+    'AudioSizeFilter', 'AverageLineLengthFilter', 'CharacterRepetitionFilter',
+    'FlaggedWordFilter', 'ImageAestheticsFilter', 'ImageAspectRatioFilter',
+    'ImageFaceCountFilter', 'ImageFaceRatioFilter', 'ImageNSFWFilter',
+    'ImagePairSimilarityFilter', 'ImageShapeFilter', 'ImageSizeFilter',
+    'ImageTextMatchingFilter', 'ImageTextSimilarityFilter',
+    'ImageWatermarkFilter', 'LanguageIDScoreFilter', 'MaximumLineLengthFilter',
+    'PerplexityFilter', 'PhraseGroundingRecallFilter',
+    'SpecialCharactersFilter', 'SpecifiedFieldFilter',
+    'SpecifiedNumericFieldFilter', 'StopWordsFilter', 'SuffixFilter',
+    'TextActionFilter', 'TextEntityDependencyFilter', 'TextLengthFilter',
+    'TokenNumFilter', 'VideoAestheticsFilter', 'VideoAspectRatioFilter',
+    'VideoDurationFilter', 'VideoFramesTextSimilarityFilter',
+    'VideoMotionScoreFilter', 'VideoNSFWFilter', 'VideoOcrAreaRatioFilter',
+    'VideoResolutionFilter', 'VideoTaggingFromFramesFilter',
+    'VideoWatermarkFilter', 'WordRepetitionFilter', 'WordsNumFilter'
 ]