title: Getting lots of warnings and errors in keras.sequential
body: <p>I have the following function that used to work, but now when I run it, after upgrading to Tensorflow 2.3, I am getting lots of warnings and dtypes confusing notices.  I am not sure how to repair my function to properly run the keras sequential code to generate a proper prediction.</p>
  <p>Here is my implementation:</p>
  <pre><code>feature_columns = []
  
  for col in numericColumns:
    col = feature_column.numeric_column(col)
    feature_columns.append(col)
  
  for col in categoricalColumns:
    col = feature_column.indicator_column(feature_column.categorical_column_with_vocabulary_list(col,df_train[col].unique()))
    feature_columns.append(col)
  
  feature_layer = tf.keras.layers.DenseFeatures(feature_columns)
  
  
  from tensorflow.keras import optimizers
  
  def build_model():
    
    model = keras.Sequential([
      feature_layer,
      layers.Dense(10, activation='relu'),
      layers.Dense(10, activation='relu'),
      layers.Dense(1)
    ])
  
    optimizer = tf.optimizers.RMSprop(learning_rate=lr_schedule)
    model.compile(loss='mse',  optimizer=optimizer, metrics=['mse'])
    return model
  
  model = build_model()
  </code></pre>
  <p>This is how I am calling the function:</p>
  <pre><code># train the model
  history = model.fit(train_ds, validation_data=val_ds, epochs=30)
  </code></pre>
  <p>This is the messy returns that I am getting that I am looking for some help to figure out how to repair or rewrite:</p>
  <pre><code>Epoch 1/30
  WARNING:tensorflow:Layers in a Sequential model should only have a single input tensor, but we receive a &lt;class 'dict'&gt; input: {'MSSubClass': &lt;tf.Tensor 'ExpandDims_49:0' shape=(None, 1) dtype=float64&gt;, 'MSZoning': &lt;tf.Tensor 'ExpandDims_50:0' shape=(None, 1) dtype=int32&gt;, 'LotFrontage': &lt;tf.Tensor 'ExpandDims_46:0' shape=(None, 1) dtype=float64&gt;, 'LotArea': &lt;tf.Tensor 'ExpandDims_44:0' shape=(None, 1) dtype=float64&gt;, 'Street': &lt;tf.Tensor 'ExpandDims_66:0' shape=(None, 1) dtype=int32&gt;, 'LotShape': &lt;tf.Tensor 'ExpandDims_47:0' shape=(None, 1) dtype=float64&gt;, 'LandContour': &lt;tf.Tensor 'ExpandDims_42:0' shape=(None, 1) dtype=float64&gt;, 'Utilities': &lt;tf.Tensor 'ExpandDims_69:0' shape=(None, 1) dtype=float64&gt;, 'LotConfig': &lt;tf.Tensor 'ExpandDims_45:0' shape=(None, 1) dtype=int32&gt;, 'LandSlope': &lt;tf.Tensor 'ExpandDims_43:0' shape=(None, 1) dtype=float64&gt;, 'Neighborhood': &lt;tf.Tensor 'ExpandDims_55:0' shape=(None, 1) dtype=int32&gt;, 'Condition1': &lt;tf.Tensor 'ExpandDims_16:0' shape=(None, 1) dtype=int32&gt;, 'Condition2': &lt;tf.Tensor 'ExpandDims_17:0' shape=(None, 1) dtype=int32&gt;, 'BldgType': &lt;tf.Tensor 'ExpandDims_4:0' shape=(None, 1) dtype=int32&gt;, 'HouseStyle': &lt;tf.Tensor 'ExpandDims_39:0' shape=(None, 1) dtype=int32&gt;, 'OverallQual': &lt;tf.Tensor 'ExpandDims_58:0' shape=(None, 1) dtype=float64&gt;, 'OverallCond': &lt;tf.Tensor 'ExpandDims_57:0' shape=(None, 1) dtype=float64&gt;, 'YearBuilt': &lt;tf.Tensor 'ExpandDims_71:0' shape=(None, 1) dtype=float64&gt;, 'YearRemodAdd': &lt;tf.Tensor 'ExpandDims_72:0' shape=(None, 1) dtype=float64&gt;, 'RoofStyle': &lt;tf.Tensor 'ExpandDims_62:0' shape=(None, 1) dtype=int32&gt;, 'RoofMatl': &lt;tf.Tensor 'ExpandDims_61:0' shape=(None, 1) dtype=int32&gt;, 'Exterior1st': &lt;tf.Tensor 'ExpandDims_22:0' shape=(None, 1) dtype=int32&gt;, 'Exterior2nd': &lt;tf.Tensor 'ExpandDims_23:0' shape=(None, 1) dtype=int32&gt;, 'MasVnrType': &lt;tf.Tensor 'ExpandDims_52:0' shape=(None, 1) dtype=int32&gt;, 'MasVnrArea': &lt;tf.Tensor 'ExpandDims_51:0' shape=(None, 1) dtype=float64&gt;, 'ExterQual': &lt;tf.Tensor 'ExpandDims_21:0' shape=(None, 1) dtype=float64&gt;, 'ExterCond': &lt;tf.Tensor 'ExpandDims_20:0' shape=(None, 1) dtype=float64&gt;, 'Foundation': &lt;tf.Tensor 'ExpandDims_25:0' shape=(None, 1) dtype=int32&gt;, 'BsmtQual': &lt;tf.Tensor 'ExpandDims_13:0' shape=(None, 1) dtype=float64&gt;, 'BsmtCond': &lt;tf.Tensor 'ExpandDims_5:0' shape=(None, 1) dtype=int64&gt;, 'BsmtExposure': &lt;tf.Tensor 'ExpandDims_6:0' shape=(None, 1) dtype=float64&gt;, 'BsmtFinType1': &lt;tf.Tensor 'ExpandDims_9:0' shape=(None, 1) dtype=float64&gt;, 'BsmtFinSF1': &lt;tf.Tensor 'ExpandDims_7:0' shape=(None, 1) dtype=float64&gt;, 'BsmtFinType2': &lt;tf.Tensor 'ExpandDims_10:0' shape=(None, 1) dtype=float64&gt;, 'BsmtFinSF2': &lt;tf.Tensor 'ExpandDims_8:0' shape=(None, 1) dtype=float64&gt;, 'BsmtUnfSF': &lt;tf.Tensor 'ExpandDims_14:0' shape=(None, 1) dtype=float64&gt;, 'TotalBsmtSF': &lt;tf.Tensor 'ExpandDims_68:0' shape=(None, 1) dtype=float64&gt;, 'Heating': &lt;tf.Tensor 'ExpandDims_37:0' shape=(None, 1) dtype=int32&gt;, 'HeatingQC': &lt;tf.Tensor 'ExpandDims_38:0' shape=(None, 1) dtype=float64&gt;, 'CentralAir': &lt;tf.Tensor 'ExpandDims_15:0' shape=(None, 1) dtype=int32&gt;, 'Electrical': &lt;tf.Tensor 'ExpandDims_18:0' shape=(None, 1) dtype=float64&gt;, '1stFlrSF': &lt;tf.Tensor 'ExpandDims:0' shape=(None, 1) dtype=float64&gt;, '2ndFlrSF': &lt;tf.Tensor 'ExpandDims_1:0' shape=(None, 1) dtype=float64&gt;, 'LowQualFinSF': &lt;tf.Tensor 'ExpandDims_48:0' shape=(None, 1) dtype=float64&gt;, 'GrLivArea': &lt;tf.Tensor 'ExpandDims_35:0' shape=(None, 1) dtype=float64&gt;, 'BsmtFullBath': &lt;tf.Tensor 'ExpandDims_11:0' shape=(None, 1) dtype=float64&gt;, 'BsmtHalfBath': &lt;tf.Tensor 'ExpandDims_12:0' shape=(None, 1) dtype=float64&gt;, 'FullBath': &lt;tf.Tensor 'ExpandDims_26:0' shape=(None, 1) dtype=float64&gt;, 'HalfBath': &lt;tf.Tensor 'ExpandDims_36:0' shape=(None, 1) dtype=float64&gt;, 'BedroomAbvGr': &lt;tf.Tensor 'ExpandDims_3:0' shape=(None, 1) dtype=float64&gt;, 'KitchenAbvGr': &lt;tf.Tensor 'ExpandDims_40:0' shape=(None, 1) dtype=float64&gt;, 'KitchenQual': &lt;tf.Tensor 'ExpandDims_41:0' shape=(None, 1) dtype=float64&gt;, 'TotRmsAbvGrd': &lt;tf.Tensor 'ExpandDims_67:0' shape=(None, 1) dtype=float64&gt;, 'Functional': &lt;tf.Tensor 'ExpandDims_27:0' shape=(None, 1) dtype=float64&gt;, 'Fireplaces': &lt;tf.Tensor 'ExpandDims_24:0' shape=(None, 1) dtype=float64&gt;, 'GarageType': &lt;tf.Tensor 'ExpandDims_33:0' shape=(None, 1) dtype=int32&gt;, 'GarageYrBlt': &lt;tf.Tensor 'ExpandDims_34:0' shape=(None, 1) dtype=float64&gt;, 'GarageFinish': &lt;tf.Tensor 'ExpandDims_31:0' shape=(None, 1) dtype=float64&gt;, 'GarageCars': &lt;tf.Tensor 'ExpandDims_29:0' shape=(None, 1) dtype=float64&gt;, 'GarageArea': &lt;tf.Tensor 'ExpandDims_28:0' shape=(None, 1) dtype=float64&gt;, 'GarageQual': &lt;tf.Tensor 'ExpandDims_32:0' shape=(None, 1) dtype=float64&gt;, 'GarageCond': &lt;tf.Tensor 'ExpandDims_30:0' shape=(None, 1) dtype=float64&gt;, 'PavedDrive': &lt;tf.Tensor 'ExpandDims_59:0' shape=(None, 1) dtype=float64&gt;, 'WoodDeckSF': &lt;tf.Tensor 'ExpandDims_70:0' shape=(None, 1) dtype=float64&gt;, 'OpenPorchSF': &lt;tf.Tensor 'ExpandDims_56:0' shape=(None, 1) dtype=float64&gt;, 'EnclosedPorch': &lt;tf.Tensor 'ExpandDims_19:0' shape=(None, 1) dtype=float64&gt;, '3SsnPorch': &lt;tf.Tensor 'ExpandDims_2:0' shape=(None, 1) dtype=float64&gt;, 'ScreenPorch': &lt;tf.Tensor 'ExpandDims_65:0' shape=(None, 1) dtype=float64&gt;, 'PoolArea': &lt;tf.Tensor 'ExpandDims_60:0' shape=(None, 1) dtype=float64&gt;, 'MiscVal': &lt;tf.Tensor 'ExpandDims_53:0' shape=(None, 1) dtype=float64&gt;, 'MoSold': &lt;tf.Tensor 'ExpandDims_54:0' shape=(None, 1) dtype=float64&gt;, 'YrSold': &lt;tf.Tensor 'ExpandDims_73:0' shape=(None, 1) dtype=float64&gt;, 'SaleType': &lt;tf.Tensor 'ExpandDims_64:0' shape=(None, 1) dtype=int32&gt;, 'SaleCondition': &lt;tf.Tensor 'ExpandDims_63:0' shape=(None, 1) dtype=int32&gt;}
  Consider rewriting this model with the Functional API.
  WARNING:tensorflow:Layers in a Sequential model should only have a single input tensor, but we receive a &lt;class 'dict'&gt; input: {'MSSubClass': &lt;tf.Tensor 'ExpandDims_49:0' shape=(None, 1) dtype=float64&gt;, 'MSZoning': &lt;tf.Tensor 'ExpandDims_50:0' shape=(None, 1) dtype=int32&gt;, 'LotFrontage': &lt;tf.Tensor 'ExpandDims_46:0' shape=(None, 1) dtype=float64&gt;, 'LotArea': &lt;tf.Tensor 'ExpandDims_44:0' shape=(None, 1) dtype=float64&gt;, 'Street': &lt;tf.Tensor 'ExpandDims_66:0' shape=(None, 1) dtype=int32&gt;, 'LotShape': &lt;tf.Tensor 'ExpandDims_47:0' shape=(None, 1) dtype=float64&gt;, 'LandContour': &lt;tf.Tensor 'ExpandDims_42:0' shape=(None, 1) dtype=float64&gt;, 'Utilities': &lt;tf.Tensor 'ExpandDims_69:0' shape=(None, 1) dtype=float64&gt;, 'LotConfig': &lt;tf.Tensor 'ExpandDims_45:0' shape=(None, 1) dtype=int32&gt;, 'LandSlope': &lt;tf.Tensor 'ExpandDims_43:0' shape=(None, 1) dtype=float64&gt;, 'Neighborhood': &lt;tf.Tensor 'ExpandDims_55:0' shape=(None, 1) dtype=int32&gt;, 'Condition1': &lt;tf.Tensor 'ExpandDims_16:0' shape=(None, 1) dtype=int32&gt;, 'Condition2': &lt;tf.Tensor 'ExpandDims_17:0' shape=(None, 1) dtype=int32&gt;, 'BldgType': &lt;tf.Tensor 'ExpandDims_4:0' shape=(None, 1) dtype=int32&gt;, 'HouseStyle': &lt;tf.Tensor 'ExpandDims_39:0' shape=(None, 1) dtype=int32&gt;, 'OverallQual': &lt;tf.Tensor 'ExpandDims_58:0' shape=(None, 1) dtype=float64&gt;, 'OverallCond': &lt;tf.Tensor 'ExpandDims_57:0' shape=(None, 1) dtype=float64&gt;, 'YearBuilt': &lt;tf.Tensor 'ExpandDims_71:0' shape=(None, 1) dtype=float64&gt;, 'YearRemodAdd': &lt;tf.Tensor 'ExpandDims_72:0' shape=(None, 1) dtype=float64&gt;, 'RoofStyle': &lt;tf.Tensor 'ExpandDims_62:0' shape=(None, 1) dtype=int32&gt;, 'RoofMatl': &lt;tf.Tensor 'ExpandDims_61:0' shape=(None, 1) dtype=int32&gt;, 'Exterior1st': &lt;tf.Tensor 'ExpandDims_22:0' shape=(None, 1) dtype=int32&gt;, 'Exterior2nd': &lt;tf.Tensor 'ExpandDims_23:0' shape=(None, 1) dtype=int32&gt;, 'MasVnrType': &lt;tf.Tensor 'ExpandDims_52:0' shape=(None, 1) dtype=int32&gt;, 'MasVnrArea': &lt;tf.Tensor 'ExpandDims_51:0' shape=(None, 1) dtype=float64&gt;, 'ExterQual': &lt;tf.Tensor 'ExpandDims_21:0' shape=(None, 1) dtype=float64&gt;, 'ExterCond': &lt;tf.Tensor 'ExpandDims_20:0' shape=(None, 1) dtype=float64&gt;, 'Foundation': &lt;tf.Tensor 'ExpandDims_25:0' shape=(None, 1) dtype=int32&gt;, 'BsmtQual': &lt;tf.Tensor 'ExpandDims_13:0' shape=(None, 1) dtype=float64&gt;, 'BsmtCond': &lt;tf.Tensor 'ExpandDims_5:0' shape=(None, 1) dtype=int64&gt;, 'BsmtExposure': &lt;tf.Tensor 'ExpandDims_6:0' shape=(None, 1) dtype=float64&gt;, 'BsmtFinType1': &lt;tf.Tensor 'ExpandDims_9:0' shape=(None, 1) dtype=float64&gt;, 'BsmtFinSF1': &lt;tf.Tensor 'ExpandDims_7:0' shape=(None, 1) dtype=float64&gt;, 'BsmtFinType2': &lt;tf.Tensor 'ExpandDims_10:0' shape=(None, 1) dtype=float64&gt;, 'BsmtFinSF2': &lt;tf.Tensor 'ExpandDims_8:0' shape=(None, 1) dtype=float64&gt;, 'BsmtUnfSF': &lt;tf.Tensor 'ExpandDims_14:0' shape=(None, 1) dtype=float64&gt;, 'TotalBsmtSF': &lt;tf.Tensor 'ExpandDims_68:0' shape=(None, 1) dtype=float64&gt;, 'Heating': &lt;tf.Tensor 'ExpandDims_37:0' shape=(None, 1) dtype=int32&gt;, 'HeatingQC': &lt;tf.Tensor 'ExpandDims_38:0' shape=(None, 1) dtype=float64&gt;, 'CentralAir': &lt;tf.Tensor 'ExpandDims_15:0' shape=(None, 1) dtype=int32&gt;, 'Electrical': &lt;tf.Tensor 'ExpandDims_18:0' shape=(None, 1) dtype=float64&gt;, '1stFlrSF': &lt;tf.Tensor 'ExpandDims:0' shape=(None, 1) dtype=float64&gt;, '2ndFlrSF': &lt;tf.Tensor 'ExpandDims_1:0' shape=(None, 1) dtype=float64&gt;, 'LowQualFinSF': &lt;tf.Tensor 'ExpandDims_48:0' shape=(None, 1) dtype=float64&gt;, 'GrLivArea': &lt;tf.Tensor 'ExpandDims_35:0' shape=(None, 1) dtype=float64&gt;, 'BsmtFullBath': &lt;tf.Tensor 'ExpandDims_11:0' shape=(None, 1) dtype=float64&gt;, 'BsmtHalfBath': &lt;tf.Tensor 'ExpandDims_12:0' shape=(None, 1) dtype=float64&gt;, 'FullBath': &lt;tf.Tensor 'ExpandDims_26:0' shape=(None, 1) dtype=float64&gt;, 'HalfBath': &lt;tf.Tensor 'ExpandDims_36:0' shape=(None, 1) dtype=float64&gt;, 'BedroomAbvGr': &lt;tf.Tensor 'ExpandDims_3:0' shape=(None, 1) dtype=float64&gt;, 'KitchenAbvGr': &lt;tf.Tensor 'ExpandDims_40:0' shape=(None, 1) dtype=float64&gt;, 'KitchenQual': &lt;tf.Tensor 'ExpandDims_41:0' shape=(None, 1) dtype=float64&gt;, 'TotRmsAbvGrd': &lt;tf.Tensor 'ExpandDims_67:0' shape=(None, 1) dtype=float64&gt;, 'Functional': &lt;tf.Tensor 'ExpandDims_27:0' shape=(None, 1) dtype=float64&gt;, 'Fireplaces': &lt;tf.Tensor 'ExpandDims_24:0' shape=(None, 1) dtype=float64&gt;, 'GarageType': &lt;tf.Tensor 'ExpandDims_33:0' shape=(None, 1) dtype=int32&gt;, 'GarageYrBlt': &lt;tf.Tensor 'ExpandDims_34:0' shape=(None, 1) dtype=float64&gt;, 'GarageFinish': &lt;tf.Tensor 'ExpandDims_31:0' shape=(None, 1) dtype=float64&gt;, 'GarageCars': &lt;tf.Tensor 'ExpandDims_29:0' shape=(None, 1) dtype=float64&gt;, 'GarageArea': &lt;tf.Tensor 'ExpandDims_28:0' shape=(None, 1) dtype=float64&gt;, 'GarageQual': &lt;tf.Tensor 'ExpandDims_32:0' shape=(None, 1) dtype=float64&gt;, 'GarageCond': &lt;tf.Tensor 'ExpandDims_30:0' shape=(None, 1) dtype=float64&gt;, 'PavedDrive': &lt;tf.Tensor 'ExpandDims_59:0' shape=(None, 1) dtype=float64&gt;, 'WoodDeckSF': &lt;tf.Tensor 'ExpandDims_70:0' shape=(None, 1) dtype=float64&gt;, 'OpenPorchSF': &lt;tf.Tensor 'ExpandDims_56:0' shape=(None, 1) dtype=float64&gt;, 'EnclosedPorch': &lt;tf.Tensor 'ExpandDims_19:0' shape=(None, 1) dtype=float64&gt;, '3SsnPorch': &lt;tf.Tensor 'ExpandDims_2:0' shape=(None, 1) dtype=float64&gt;, 'ScreenPorch': &lt;tf.Tensor 'ExpandDims_65:0' shape=(None, 1) dtype=float64&gt;, 'PoolArea': &lt;tf.Tensor 'ExpandDims_60:0' shape=(None, 1) dtype=float64&gt;, 'MiscVal': &lt;tf.Tensor 'ExpandDims_53:0' shape=(None, 1) dtype=float64&gt;, 'MoSold': &lt;tf.Tensor 'ExpandDims_54:0' shape=(None, 1) dtype=float64&gt;, 'YrSold': &lt;tf.Tensor 'ExpandDims_73:0' shape=(None, 1) dtype=float64&gt;, 'SaleType': &lt;tf.Tensor 'ExpandDims_64:0' shape=(None, 1) dtype=int32&gt;, 'SaleCondition': &lt;tf.Tensor 'ExpandDims_63:0' shape=(None, 1) dtype=int32&gt;}
  Consider rewriting this model with the Functional API.
  35/37 [===========================&gt;..] - ETA: 0s - loss: 120.7742 - mse: 120.7742WARNING:tensorflow:Layers in a Sequential model should only have a single input tensor, but we receive a &lt;class 'dict'&gt; input: {'MSSubClass': &lt;tf.Tensor 'ExpandDims_49:0' shape=(None, 1) dtype=float64&gt;, 'MSZoning': &lt;tf.Tensor 'ExpandDims_50:0' shape=(None, 1) dtype=int32&gt;, 'LotFrontage': &lt;tf.Tensor 'ExpandDims_46:0' shape=(None, 1) dtype=float64&gt;, 'LotArea': &lt;tf.Tensor 'ExpandDims_44:0' shape=(None, 1) dtype=float64&gt;, 'Street': &lt;tf.Tensor 'ExpandDims_66:0' shape=(None, 1) dtype=int32&gt;, 'LotShape': &lt;tf.Tensor 'ExpandDims_47:0' shape=(None, 1) dtype=float64&gt;, 'LandContour': &lt;tf.Tensor 'ExpandDims_42:0' shape=(None, 1) dtype=float64&gt;, 'Utilities': &lt;tf.Tensor 'ExpandDims_69:0' shape=(None, 1) dtype=float64&gt;, 'LotConfig': &lt;tf.Tensor 'ExpandDims_45:0' shape=(None, 1) dtype=int32&gt;, 'LandSlope': &lt;tf.Tensor 'ExpandDims_43:0' shape=(None, 1) dtype=float64&gt;, 'Neighborhood': &lt;tf.Tensor 'ExpandDims_55:0' shape=(None, 1) dtype=int32&gt;, 'Condition1': &lt;tf.Tensor 'ExpandDims_16:0' shape=(None, 1) dtype=int32&gt;, 'Condition2': &lt;tf.Tensor 'ExpandDims_17:0' shape=(None, 1) dtype=int32&gt;, 'BldgType': &lt;tf.Tensor 'ExpandDims_4:0' shape=(None, 1) dtype=int32&gt;, 'HouseStyle': &lt;tf.Tensor 'ExpandDims_39:0' shape=(None, 1) dtype=int32&gt;, 'OverallQual': &lt;tf.Tensor 'ExpandDims_58:0' shape=(None, 1) dtype=float64&gt;, 'OverallCond': &lt;tf.Tensor 'ExpandDims_57:0' shape=(None, 1) dtype=float64&gt;, 'YearBuilt': &lt;tf.Tensor 'ExpandDims_71:0' shape=(None, 1) dtype=float64&gt;, 'YearRemodAdd': &lt;tf.Tensor 'ExpandDims_72:0' shape=(None, 1) dtype=float64&gt;, 'RoofStyle': &lt;tf.Tensor 'ExpandDims_62:0' shape=(None, 1) dtype=int32&gt;, 'RoofMatl': &lt;tf.Tensor 'ExpandDims_61:0' shape=(None, 1) dtype=int32&gt;, 'Exterior1st': &lt;tf.Tensor 'ExpandDims_22:0' shape=(None, 1) dtype=int32&gt;, 'Exterior2nd': &lt;tf.Tensor 'ExpandDims_23:0' shape=(None, 1) dtype=int32&gt;, 'MasVnrType': &lt;tf.Tensor 'ExpandDims_52:0' shape=(None, 1) dtype=int32&gt;, 'MasVnrArea': &lt;tf.Tensor 'ExpandDims_51:0' shape=(None, 1) dtype=float64&gt;, 'ExterQual': &lt;tf.Tensor 'ExpandDims_21:0' shape=(None, 1) dtype=float64&gt;, 'ExterCond': &lt;tf.Tensor 'ExpandDims_20:0' shape=(None, 1) dtype=float64&gt;, 'Foundation': &lt;tf.Tensor 'ExpandDims_25:0' shape=(None, 1) dtype=int32&gt;, 'BsmtQual': &lt;tf.Tensor 'ExpandDims_13:0' shape=(None, 1) dtype=float64&gt;, 'BsmtCond': &lt;tf.Tensor 'ExpandDims_5:0' shape=(None, 1) dtype=int64&gt;, 'BsmtExposure': &lt;tf.Tensor 'ExpandDims_6:0' shape=(None, 1) dtype=float64&gt;, 'BsmtFinType1': &lt;tf.Tensor 'ExpandDims_9:0' shape=(None, 1) dtype=float64&gt;, 'BsmtFinSF1': &lt;tf.Tensor 'ExpandDims_7:0' shape=(None, 1) dtype=float64&gt;, 'BsmtFinType2': &lt;tf.Tensor 'ExpandDims_10:0' shape=(None, 1) dtype=float64&gt;, 'BsmtFinSF2': &lt;tf.Tensor 'ExpandDims_8:0' shape=(None, 1) dtype=float64&gt;, 'BsmtUnfSF': &lt;tf.Tensor 'ExpandDims_14:0' shape=(None, 1) dtype=float64&gt;, 'TotalBsmtSF': &lt;tf.Tensor 'ExpandDims_68:0' shape=(None, 1) dtype=float64&gt;, 'Heating': &lt;tf.Tensor 'ExpandDims_37:0' shape=(None, 1) dtype=int32&gt;, 'HeatingQC': &lt;tf.Tensor 'ExpandDims_38:0' shape=(None, 1) dtype=float64&gt;, 'CentralAir': &lt;tf.Tensor 'ExpandDims_15:0' shape=(None, 1) dtype=int32&gt;, 'Electrical': &lt;tf.Tensor 'ExpandDims_18:0' shape=(None, 1) dtype=float64&gt;, '1stFlrSF': &lt;tf.Tensor 'ExpandDims:0' shape=(None, 1) dtype=float64&gt;, '2ndFlrSF': &lt;tf.Tensor 'ExpandDims_1:0' shape=(None, 1) dtype=float64&gt;, 'LowQualFinSF': &lt;tf.Tensor 'ExpandDims_48:0' shape=(None, 1) dtype=float64&gt;, 'GrLivArea': &lt;tf.Tensor 'ExpandDims_35:0' shape=(None, 1) dtype=float64&gt;, 'BsmtFullBath': &lt;tf.Tensor 'ExpandDims_11:0' shape=(None, 1) dtype=float64&gt;, 'BsmtHalfBath': &lt;tf.Tensor 'ExpandDims_12:0' shape=(None, 1) dtype=float64&gt;, 'FullBath': &lt;tf.Tensor 'ExpandDims_26:0' shape=(None, 1) dtype=float64&gt;, 'HalfBath': &lt;tf.Tensor 'ExpandDims_36:0' shape=(None, 1) dtype=float64&gt;, 'BedroomAbvGr': &lt;tf.Tensor 'ExpandDims_3:0' shape=(None, 1) dtype=float64&gt;, 'KitchenAbvGr': &lt;tf.Tensor 'ExpandDims_40:0' shape=(None, 1) dtype=float64&gt;, 'KitchenQual': &lt;tf.Tensor 'ExpandDims_41:0' shape=(None, 1) dtype=float64&gt;, 'TotRmsAbvGrd': &lt;tf.Tensor 'ExpandDims_67:0' shape=(None, 1) dtype=float64&gt;, 'Functional': &lt;tf.Tensor 'ExpandDims_27:0' shape=(None, 1) dtype=float64&gt;, 'Fireplaces': &lt;tf.Tensor 'ExpandDims_24:0' shape=(None, 1) dtype=float64&gt;, 'GarageType': &lt;tf.Tensor 'ExpandDims_33:0' shape=(None, 1) dtype=int32&gt;, 'GarageYrBlt': &lt;tf.Tensor 'ExpandDims_34:0' shape=(None, 1) dtype=float64&gt;, 'GarageFinish': &lt;tf.Tensor 'ExpandDims_31:0' shape=(None, 1) dtype=float64&gt;, 'GarageCars': &lt;tf.Tensor 'ExpandDims_29:0' shape=(None, 1) dtype=float64&gt;, 'GarageArea': &lt;tf.Tensor 'ExpandDims_28:0' shape=(None, 1) dtype=float64&gt;, 'GarageQual': &lt;tf.Tensor 'ExpandDims_32:0' shape=(None, 1) dtype=float64&gt;, 'GarageCond': &lt;tf.Tensor 'ExpandDims_30:0' shape=(None, 1) dtype=float64&gt;, 'PavedDrive': &lt;tf.Tensor 'ExpandDims_59:0' shape=(None, 1) dtype=float64&gt;, 'WoodDeckSF': &lt;tf.Tensor 'ExpandDims_70:0' shape=(None, 1) dtype=float64&gt;, 'OpenPorchSF': &lt;tf.Tensor 'ExpandDims_56:0' shape=(None, 1) dtype=float64&gt;, 'EnclosedPorch': &lt;tf.Tensor 'ExpandDims_19:0' shape=(None, 1) dtype=float64&gt;, '3SsnPorch': &lt;tf.Tensor 'ExpandDims_2:0' shape=(None, 1) dtype=float64&gt;, 'ScreenPorch': &lt;tf.Tensor 'ExpandDims_65:0' shape=(None, 1) dtype=float64&gt;, 'PoolArea': &lt;tf.Tensor 'ExpandDims_60:0' shape=(None, 1) dtype=float64&gt;, 'MiscVal': &lt;tf.Tensor 'ExpandDims_53:0' shape=(None, 1) dtype=float64&gt;, 'MoSold': &lt;tf.Tensor 'ExpandDims_54:0' shape=(None, 1) dtype=float64&gt;, 'YrSold': &lt;tf.Tensor 'ExpandDims_73:0' shape=(None, 1) dtype=float64&gt;, 'SaleType': &lt;tf.Tensor 'ExpandDims_64:0' shape=(None, 1) dtype=int32&gt;, 'SaleCondition': &lt;tf.Tensor 'ExpandDims_63:0' shape=(None, 1) dtype=int32&gt;}
  Consider rewriting this model with the Functional API.
  </code></pre>