# tf.contrib.layers.real_valued_column

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| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/contrib/layers/python/layers/feature_column.py#L1922-L2034) |

Creates a `_RealValuedColumn` for dense numeric data.

    tf.contrib.layers.real_valued_column(
        column_name, dimension=1, default_value=None, dtype=tf.dtypes.float32,
        normalizer=None
    )

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| ## Args ||
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| `column_name` | A string defining real valued column name. |
| `dimension` | An integer specifying dimension of the real valued column. The default is 1. |
| `default_value` | A single value compatible with dtype or a list of values compatible with dtype which the column takes on during tf.Example parsing if data is missing. When dimension is not None, a default value of None will cause tf.io.parse_example to fail if an example does not contain this column. If a single value is provided, the same value will be applied as the default value for every dimension. If a list of values is provided, the length of the list should be equal to the value of `dimension`. Only scalar default value is supported in case dimension is not specified. |
| `dtype` | defines the type of values. Default value is tf.float32. Must be a non-quantized, real integer or floating point type. |
| `normalizer` | If not None, a function that can be used to normalize the value of the real valued column after default_value is applied for parsing. Normalizer function takes the input tensor as its argument, and returns the output tensor. (e.g. lambda x: (x - 3.0) / 4.2). Note that for variable length columns, the normalizer should expect an input_tensor of type `SparseTensor`. |

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| ## Returns ||
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| A _RealValuedColumn. ||

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| ## Raises ||
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| `TypeError` | if dimension is not an int |
| `ValueError` | if dimension is not a positive integer |
| `TypeError` | if default_value is a list but its length is not equal to the value of `dimension`. |
| `TypeError` | if default_value is not compatible with dtype. |
| `ValueError` | if dtype is not convertible to tf.float32. |

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