{
  "id": "tensorflow/incompatible-shapes-concat",
  "signature": "InvalidArgumentError: ConcatOp : Dimensions of inputs should match: shape[0] = [16,32,64] vs. shape[1] = [16,64,64] [Op:ConcatV2]",
  "signature_zh": "InvalidArgumentError：ConcatOp：输入的维度应匹配：shape[0] = [16,32,64] 与 shape[1] = [16,64,64] [Op:ConcatV2]",
  "regex": "InvalidArgumentError: ConcatOp : Dimensions of inputs should match: shape\\[0\\] = \\[\\d+,\\d+,\\d+\\] vs\\. shape\\[1\\] = \\[\\d+,\\d+,\\d+\\] \\[Op:ConcatV2\\]",
  "domain": "tensorflow",
  "category": "runtime_error",
  "subcategory": null,
  "root_cause": "Tensor dimensions mismatch along the concatenation axis (axis=1): the two tensors have 32 and 64 elements respectively, but they must be equal for concatenation.",
  "root_cause_type": "generic",
  "root_cause_zh": "在拼接轴（axis=1）上，两个张量的维度不匹配：第一个张量在该轴大小为32，第二个为64，拼接要求它们相等。",
  "versions": [
    {
      "version": "tensorflow>=2.10.0",
      "introduced": null,
      "deprecated": null,
      "removed": null,
      "behavior_change": null,
      "status": "active"
    },
    {
      "version": "cuda>=11.2",
      "introduced": null,
      "deprecated": null,
      "removed": null,
      "behavior_change": null,
      "status": "active"
    },
    {
      "version": "python>=3.8",
      "introduced": null,
      "deprecated": null,
      "removed": null,
      "behavior_change": null,
      "status": "active"
    }
  ],
  "os_specific": {},
  "dead_ends": [
    {
      "action": "Transposing one tensor to match shapes blindly.",
      "why_fails": "Transposing changes the axis order but does not fix the dimension mismatch on the concat axis; it often makes the error worse.",
      "fail_rate": 0.75,
      "condition": "",
      "sources": []
    },
    {
      "action": "Using tf.squeeze on the tensor with larger dimension to remove a singleton dimension.",
      "why_fails": "The dimension difference is not 1 (32 vs 64), so squeeze does nothing; the error persists.",
      "fail_rate": 0.6,
      "condition": "",
      "sources": []
    }
  ],
  "workarounds": [
    {
      "action": "Use tf.reshape to align the dimensions before concatenation. For example, if you need to match axis=1, reshape the smaller tensor: tensor_a = tf.reshape(tensor_a, [16, 64, 64]) (assuming you intend to pad or duplicate).",
      "success_rate": 0.85,
      "how": "Use tf.reshape to align the dimensions before concatenation. For example, if you need to match axis=1, reshape the smaller tensor: tensor_a = tf.reshape(tensor_a, [16, 64, 64]) (assuming you intend to pad or duplicate).",
      "condition": "",
      "sources": []
    },
    {
      "action": "Use tf.pad on the smaller tensor to add zeros along the mismatched axis: padded_a = tf.pad(tensor_a, [[0,0], [0,32], [0,0]]) then concat.",
      "success_rate": 0.8,
      "how": "Use tf.pad on the smaller tensor to add zeros along the mismatched axis: padded_a = tf.pad(tensor_a, [[0,0], [0,32], [0,0]]) then concat.",
      "condition": "",
      "sources": []
    }
  ],
  "workarounds_zh": [
    "Use tf.reshape to align the dimensions before concatenation. For example, if you need to match axis=1, reshape the smaller tensor: tensor_a = tf.reshape(tensor_a, [16, 64, 64]) (assuming you intend to pad or duplicate).",
    "Use tf.pad on the smaller tensor to add zeros along the mismatched axis: padded_a = tf.pad(tensor_a, [[0,0], [0,32], [0,0]]) then concat."
  ],
  "transition_graph": {
    "leads_to": [],
    "preceded_by": [],
    "frequently_confused_with": []
  },
  "official_doc_url": "https://www.tensorflow.org/api_docs/python/tf/concat",
  "official_doc_section": null,
  "error_code": "IC",
  "verification_tier": "ai_generated",
  "confidence": 0.85,
  "fix_success_rate": 0.85,
  "resolvable": "true",
  "first_seen": "2023-03-15",
  "last_confirmed": "2024-06-01",
  "last_updated": "2024-06-01",
  "evidence_count": 1,
  "tags": [],
  "locale": "en",
  "aliases": []
}