我需要帮助解决以下问题。我试图将我的CSV数据输入到我的第一层，即一维卷积层，但它显示

输入0与层conv1d_Conv1D1不兼容：期望ndim=3，发现ndim=2

这是我的代码

//move the tfjs_binding.node file in build-tmp-napi-v7/Release folder to build-tmp-napi-v7 folder will solve the problem.const dfd = require("danfojs-node");const tf = require("@tensorflow/tfjs-node");var petData;const TIME_STEPS = (24 * 60) / 60;console.log("start");var model = tf.sequential();model.add(  tf.layers.conv1d({    filters: 3,    kernelSize: 3,    inputShape:[1]  }));// model.add(tf.layers.dropout({ rate: 0.2 }));// model.add(//   tf.layers.conv1d({//     filters: 16,//     kernelSize: 7,//     padding: "same",//     strides: 2,//     activation: "relu",//   })// );// model.add(//   tf.layers.conv1d({//     filters: 16,//     kernelSize: 7,//     padding: "same",//     strides: 2,//     activation: "relu",//   })// );// model.add(tf.layers.dropout({ rate: 0.2 }));// model.add(//   tf.layers.conv1d({//     filters: 32,//     kernelSize: 7,//     padding: "same",//     strides: 2,//     activation: "relu",//   })// );// model.add(//   tf.layers.conv1d({//     filters: 1,//     kernelSize: 7,//     padding: "same",//   })// );model.compile({  optimizer: tf.train.adam((learningRate = 0.001)),  loss: tf.losses.meanSquaredError,});model.summary();console.log("model created.");dfd  .read_csv("./petTempData.csv", (chunk = 10000))  .then((df) => {    let encoder = new dfd.LabelEncoder();    let cols = ["Date", "Time"];    cols.forEach((col) => {      encoder.fit(df[col]);      enc_val = encoder.transform(df[col]);      df.addColumn({ column: col, value: enc_val });    });    petData = df.iloc({ columns: [`1`] });    yData = df["Temperature"];    // let scaler = new dfd.MinMaxScaler();    // scaler.fit(petData);    // petData = scaler.transform(petData);    // petData = petData.tensor.expandDims(-1);    // const data = petData.tensor.reshape([24, 2, 1]);    console.log(petData.shape);    model.fit(petData.tensor, yData.tensor, {      epochs: 10,      batchSize: 4,      // validationSplit: 0.01,      callbacks: tf.callbacks.earlyStopping({        monitor: "loss",        patience: "5",        mode: "min",      }),    });  })  .catch((err) => {    console.log(err);  });

这是我的CSV原始文件

Date,Time,Temperature31-12-2020,01:30,36.631-12-2020,02:30,36.731-12-2020,03:30,36.631-12-2020,04:30,36.531-12-2020,05:30,36.831-12-2020,06:30,36.631-12-2020,07:30,36.631-12-2020,08:30,36.531-12-2020,09:30,36.631-12-2020,10:30,36.731-12-2020,11:30,36.631-12-2020,12:30,36.731-12-2020,13:30,36.731-12-2020,14:30,36.831-12-2020,15:30,36.931-12-2020,16:30,36.631-12-2020,17:30,36.731-12-2020,18:30,36.831-12-2020,19:30,36.731-12-2020,20:30,36.631-12-2020,21:30,36.631-12-2020,22:30,36.531-12-2020,23:30,36.5,,

我已经尝试重塑我的输入，并扩展维度，但这些方法都不起作用。任何解决方案都将不胜感激！

回答：

conv1d层期望输入形状的维度为2，因此，输入形状需要是[a, b]（a, b为正整数）。

model = tf.sequential();model.add(  tf.layers.conv1d({    filters: 3,    kernelSize: 1,    inputShape:[1, 3]  }));model.predict(tf.ones([1, 1, 3])).print()