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我刚从 Tensorflow 开始，当我打电话时m.fit(input_fn=lambda: self.input_fn(train_data), steps=train_steps)，我收到以下错误。

File "/Library/Python/2.7/site-packages/tensorflow/contrib/layers/python/layers/feature_column_ops.py", line 161, in _input_from_feature_columns
    transformed_tensor = transformer.transform(column)
File "/Library/Python/2.7/site-packages/tensorflow/contrib/layers/python/layers/feature_column_ops.py", line 882, in transform
    feature_column.insert_transformed_feature(self._columns_to_tensors)
File "/Library/Python/2.7/site-packages/tensorflow/contrib/layers/python/layers/feature_column.py", line 991, in insert_transformed_feature
    self.sparse_id_column.insert_transformed_feature(columns_to_tensors)
File "/Library/Python/2.7/site-packages/tensorflow/contrib/layers/python/layers/feature_column.py", line 572, in insert_transformed_feature
    name="lookup")
File "/Library/Python/2.7/site-packages/tensorflow/contrib/lookup/lookup_ops.py", line 1018, in index_table_from_tensor
    "integer" if dtype.is_integer else "non-integer", keys.dtype))
ValueError: Expected non-integer, got <dtype: 'int32'>.

在我传递给的特征列中fit()，只有int32and int64，但这不应该是问题，不是吗？

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1 回答 1

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我认为您可能会使用分类特征，tf.SparseTensor但您的特征列包含int32.

在这种情况下，只需将整数列转换为字符串，例如：

# using Pandas
for f in categorical_features:
    df_train[f] = df_train[f].astype(str)   
    df_test[f] = df_test[f].astype(str)
于 2017-06-01T15:15:45.940 回答