{"record":{"id":"4964de90af6c70fa","repo":"keras-team/keras","slug":"use-cudnn-true-was-specified-but-cudnn-is-not-sup-4964de","errorCode":null,"errorMessage":"use_cudnn=True was specified, but cuDNN is not supported for this layer configuration with this backend. Pass use_cudnn='auto' to fallback to a non-cuDNN implementation.","messagePattern":"use_cudnn=True was specified, but cuDNN is not supported for this layer configuration with this backend\\. Pass use_cudnn='auto' to fallback to a non-cuDNN implementation\\.","errorType":"exception","errorClass":"ValueError","httpStatus":null,"severity":"error","filePath":"keras/src/layers/rnn/lstm.py","lineNumber":572,"sourceCode":"                        mask,\n                        kernel=self.cell.kernel,\n                        recurrent_kernel=self.cell.recurrent_kernel,\n                        bias=self.cell.bias,\n                        activation=self.cell.activation,\n                        recurrent_activation=self.cell.recurrent_activation,\n                        return_sequences=self.return_sequences,\n                        go_backwards=self.go_backwards,\n                        unroll=self.unroll,\n                    )\n                    # We disable jit_compile for the model in this case,\n                    # since cuDNN ops aren't XLA compatible.\n                    if backend.backend() == \"tensorflow\":\n                        self.supports_jit = False\n                    return out\n                except NotImplementedError:\n                    pass\n        if self.use_cudnn is True:\n            raise ValueError(\n                \"use_cudnn=True was specified, \"\n                \"but cuDNN is not supported for this layer configuration \"\n                \"with this backend. Pass use_cudnn='auto' to fallback \"\n                \"to a non-cuDNN implementation.\"\n            )\n        return super().inner_loop(\n            sequences, initial_state, mask=mask, training=training\n        )\n\n    def call(self, sequences, initial_state=None, mask=None, training=False):\n        return super().call(\n            sequences, mask=mask, training=training, initial_state=initial_state\n        )\n\n    @property\n    def units(self):\n        return self.cell.units\n","sourceCodeStart":554,"sourceCodeEnd":590,"githubUrl":"https://github.com/keras-team/keras/blob/7a34a03db60bf60042242d6a556fc3be119046a5/keras/src/layers/rnn/lstm.py#L554-L590","documentation":"Error \"use_cudnn=True was specified, but cuDNN is not supported for this layer configuration with this backend. Pass use_cudnn='auto' to fallback to a non-cuDNN implementation.\" thrown in keras-team/keras.","triggerScenarios":"Thrown at keras/src/layers/rnn/lstm.py:572 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"}