{"record":{"id":"f2df43582b5b02f8","repo":"keras-team/keras","slug":"a-ndim-dimensional-array-given-array-must-be-tw","errorCode":null,"errorMessage":"{a.ndim}-dimensional array given. Array must be two-dimensional","messagePattern":"(.+?)-dimensional array given\\. Array must be two-dimensional","errorType":"exception","errorClass":"TypeError","httpStatus":null,"severity":"error","filePath":"keras/src/backend/tensorflow/linalg.py","lineNumber":218,"sourceCode":"def svd(x, full_matrices=True, compute_uv=True):\n    if compute_uv is False:\n        return tf.linalg.svd(x, full_matrices=full_matrices, compute_uv=False)\n    s, u, v = tf.linalg.svd(\n        x, full_matrices=full_matrices, compute_uv=compute_uv\n    )\n    return u, s, tf.linalg.adjoint(v)\n\n\ndef lstsq(a, b, rcond=None):\n    a = convert_to_tensor(a)\n    b = convert_to_tensor(b)\n    if a.shape[0] != b.shape[0]:\n        raise ValueError(\"Leading dimensions of input arrays must match\")\n    b_orig_ndim = b.ndim\n    if b_orig_ndim == 1:\n        b = b[:, None]\n    if a.ndim != 2:\n        raise TypeError(\n            f\"{a.ndim}-dimensional array given. Array must be two-dimensional\"\n        )\n    if b.ndim != 2:\n        raise TypeError(\n            f\"{b.ndim}-dimensional array given. \"\n            \"Array must be one or two-dimensional\"\n        )\n    m, n = a.shape\n    dtype = a.dtype\n    eps = tf.experimental.numpy.finfo(dtype).eps\n    if a.shape == ():\n        s = tf.zeros(0, dtype=a.dtype)\n        x = tf.zeros((n, *b.shape[1:]), dtype=a.dtype)\n    else:\n        if rcond is None:\n            rcond = eps * max(n, m)\n        else:\n            rcond = tf.where(rcond < 0, eps, rcond)","sourceCodeStart":200,"sourceCodeEnd":236,"githubUrl":"https://github.com/keras-team/keras/blob/7a34a03db60bf60042242d6a556fc3be119046a5/keras/src/backend/tensorflow/linalg.py#L200-L236","documentation":"Error \"{a.ndim}-dimensional array given. Array must be two-dimensional\" thrown in keras-team/keras.","triggerScenarios":"Thrown at keras/src/backend/tensorflow/linalg.py:218 when the library encounters an invalid state.","commonSituations":"See trigger scenarios.","solutions":[],"exampleFix":null,"handlingStrategy":null,"validationCode":null,"typeGuard":null,"tryCatchPattern":null,"preventionTips":[],"tags":[],"backgroundTag":null,"analyzedSha":"7a34a03db60bf60042242d6a556fc3be119046a5","analyzedAt":"2026-08-25T21:25:25.994Z","schemaVersion":2},"datasetVersion":"2026-08-26T02:17:13.382Z"}