Property 'SR_B1' of feature 'LC08_164038_20220112' is missing

Question

I write the following code for random forest classification, but I received error "Property 'SR_B1' of feature 'LC08_164038_20220112' is missing."

var table = ee.FeatureCollection("users/srs/et")
var landsat = ee.ImageCollection("LANDSAT/LC08/C02/T1_L2")
.filterBounds(geometry)
.filterDate('2022-01-01', '2024-01-01')
.filter(ee.Filter.lessThan('CLOUD_COVER',10))


var fc = ee.FeatureCollection(table,'ET')
var withRandom = fc.randomColumn('ET');
//print('withRandom', withRandom)


var split = 0.7; 
var trainingPartition = withRandom.filter(ee.Filter.lt('ET', split));
var testingPartition = withRandom.filter(ee.Filter.gte('ET', split));
var bands = ['SR_B1', 'SR_B2', 'SR_B3', 'SR_B4', 'SR_B5', 'SR_B6', 'SR_B7', 'ST_B10']

var ClassProperty = 'ET'
//Training the classifer and applying it with the filtered training collection.
var fc_classifier = ee.Classifier.smileRandomForest(10).train({
  features: trainingPartition,
  classProperty: ClassProperty,
  inputProperties: ['SR_B1', 'SR_B2', 'SR_B3', 'SR_B4', 'SR_B5', 'SR_B6', 'SR_B7', 'ST_B10']
  
})
var test = testingPartition.classify(fc_classifier, 'fc_classifier')
print('fc_test', test);

var trainAccuracy = fc_classifier.confusionMatrix();
print('Training error matrix', trainAccuracy);
print('Training overall accuracy', trainAccuracy.accuracy());

var validationSample = testingPartition.classify(fc_classifier, 'fc_classifier');
var validationAccuracy = validationSample.errorMatrix('ET', 'classification');
print('Validation error matrix', validationAccuracy);
print('Validation accuracy', validationAccuracy.accuracy());

Please help me that I solve this problem.