{
  "id": "tensorflow/ragged-tensor-batch-size-mismatch",
  "signature": "InvalidArgumentError: Cannot batch ragged tensors with different number of rows",
  "signature_zh": "InvalidArgumentError: 无法批处理具有不同行数的不规则张量",
  "regex": "InvalidArgumentError: Cannot batch ragged tensors with different number of rows",
  "domain": "tensorflow",
  "category": "data_error",
  "subcategory": null,
  "root_cause": "Attempting to batch multiple RaggedTensors that have different row lengths (first dimension) in a way that requires uniform batch size, e.g., using tf.data.Dataset.batch() without padding.",
  "root_cause_type": "generic",
  "root_cause_zh": "尝试批处理多个具有不同行长度（第一维）的 RaggedTensor，但使用了需要统一批量大小的方式，例如未填充的 tf.data.Dataset.batch()。",
  "versions": [
    {
      "version": "tensorflow 2.9",
      "introduced": null,
      "deprecated": null,
      "removed": null,
      "behavior_change": null,
      "status": "active"
    },
    {
      "version": "tensorflow 2.10",
      "introduced": null,
      "deprecated": null,
      "removed": null,
      "behavior_change": null,
      "status": "active"
    },
    {
      "version": "tensorflow 2.11",
      "introduced": null,
      "deprecated": null,
      "removed": null,
      "behavior_change": null,
      "status": "active"
    }
  ],
  "os_specific": {},
  "dead_ends": [
    {
      "action": "",
      "why_fails": "drop_remainder only controls whether the last incomplete batch is dropped, but the error occurs within a batch where rows are already unequal.",
      "fail_rate": 0.9,
      "condition": "",
      "sources": []
    },
    {
      "action": "",
      "why_fails": "While it resolves the batching error, it can cause OOM if ragged dimensions are large; also it changes semantics.",
      "fail_rate": 0.75,
      "condition": "",
      "sources": []
    }
  ],
  "workarounds": [
    {
      "action": "Use padded_batch() instead of batch() on the dataset: dataset = dataset.padded_batch(batch_size, padded_shapes=[None, None])",
      "success_rate": 0.9,
      "how": "Use padded_batch() instead of batch() on the dataset: dataset = dataset.padded_batch(batch_size, padded_shapes=[None, None])",
      "condition": "",
      "sources": []
    },
    {
      "action": "Pad RaggedTensors manually before batching using ragged_tensor.to_tensor(default_value=0, shape=[None, max_len]) then use regular batch().",
      "success_rate": 0.85,
      "how": "Pad RaggedTensors manually before batching using ragged_tensor.to_tensor(default_value=0, shape=[None, max_len]) then use regular batch().",
      "condition": "",
      "sources": []
    }
  ],
  "workarounds_zh": [
    "在数据集上使用 padded_batch() 代替 batch()：dataset = dataset.padded_batch(batch_size, padded_shapes=[None, None])",
    "在批处理之前手动填充 RaggedTensor：使用 ragged_tensor.to_tensor(default_value=0, shape=[None, max_len])，然后使用常规 batch()。"
  ],
  "transition_graph": {
    "leads_to": [],
    "preceded_by": [],
    "frequently_confused_with": []
  },
  "official_doc_url": "https://www.tensorflow.org/guide/ragged_tensor#batching_ragged_tensors",
  "official_doc_section": null,
  "error_code": null,
  "verification_tier": "ai_generated",
  "confidence": 0.84,
  "fix_success_rate": 0.85,
  "resolvable": "true",
  "first_seen": "2023-06-05",
  "last_confirmed": "2024-06-01",
  "last_updated": "2024-06-01",
  "evidence_count": 1,
  "tags": [],
  "locale": "en",
  "aliases": []
}