TypeError: sparse matrix length is ambiguous； use getnnz() or shape[0]
文章目錄 問題 原因 解決 問題 在跑Keras版GCN源碼解析的時候，發現以下問題：TypeError: sparse matrix length is ambiguous; use getnnz() or shape[0] 原因 在model.fit時，輸入了特徵矩陣，和鄰接矩陣，但鄰接矩陣A是<class ‘scipy.sparse.csr.csr_matrix’>。可能是fit函數接受不了
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相關文章
- 1. sparse matrix format
- 2. 311. Sparse Matrix Multiplication
- 3. Uncaught TypeError: Cannot use 'in' operator to search for 'length'
- 4. ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any()
- 5. 解決TypeError: Tensor is unhashable if Tensor equality is enabled. Instead, use tensor.experimental_re
- 6. TypeError: can't concat str to bytes OR TypeError: cannot use a string pattern on a bytes-like obj
- 7. Column length too big for column 'PARAM_VALUE'(max=21845); use BLOB or Text instead
- 8. [LeetCode] Sparse Matrix Multiplication 稀疏矩陣相乘
- 9. TypeError: The numpy boolean negative, the `-` operator, is not supported, use the `~`
- 10. GroovyScript：Reference to one class is ambiguous