# tf.contrib.learn.read_batch_examples

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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/learn/python/learn/learn_io/graph_io.py#L48-L113) |

Adds operations to read, queue, batch `Example` protos. (deprecated)

    tf.contrib.learn.read_batch_examples(
        file_pattern, batch_size, reader, randomize_input=True, num_epochs=None,
        queue_capacity=10000, num_threads=1, read_batch_size=1, parse_fn=None,
        name=None, seed=None
    )

> [!WARNING]
> **Warning:** THIS FUNCTION IS DEPRECATED. It will be removed in a future version. Instructions for updating: Use tf.data.

Given file pattern (or list of files), will setup a queue for file names,
read `Example` proto using provided `reader`, use batch queue to create
batches of examples of size `batch_size`.

All queue runners are added to the queue runners collection, and may be
started via `start_queue_runners`.

All ops are added to the default graph.

Use `parse_fn` if you need to do parsing / processing on single examples.

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| ## Args ||
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| `file_pattern` | List of files or patterns of file paths containing `Example` records. See [`tf.io.gfile.glob`](https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/io/gfile/glob) for pattern rules. |
| `batch_size` | An int or scalar `Tensor` specifying the batch size to use. |
| `reader` | A function or class that returns an object with `read` method, (filename tensor) -\> (example tensor). |
| `randomize_input` | Whether the input should be randomized. |
| `num_epochs` | Integer specifying the number of times to read through the dataset. If `None`, cycles through the dataset forever. NOTE - If specified, creates a variable that must be initialized, so call [`tf.compat.v1.local_variables_initializer()`](https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/initializers/local_variables) and run the op in a session. |
| `queue_capacity` | Capacity for input queue. |
| `num_threads` | The number of threads enqueuing examples. In order to have predictable and repeatable order of reading and enqueueing, such as in prediction and evaluation mode, `num_threads` should be 1. |
| `read_batch_size` | An int or scalar `Tensor` specifying the number of records to read at once. |
| `parse_fn` | Parsing function, takes `Example` Tensor returns parsed representation. If `None`, no parsing is done. |
| `name` | Name of resulting op. |
| `seed` | An integer (optional). Seed used if randomize_input == True. |

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| ## Returns ||
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| String `Tensor` of batched `Example` proto. ||

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| ## Raises ||
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| `ValueError` | for invalid inputs. |

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