# tf.compat.v1.train.slice_input_producer

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| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.13.1/tensorflow/python/training/input.py#L319-L374) |

Produces a slice of each `Tensor` in `tensor_list`. (deprecated)

    tf.compat.v1.train.slice_input_producer(
        tensor_list,
        num_epochs=None,
        shuffle=True,
        seed=None,
        capacity=32,
        shared_name=None,
        name=None
    )

> [!WARNING]
> **Deprecated:** THIS FUNCTION IS DEPRECATED. It will be removed in a future version. Instructions for updating: Queue-based input pipelines have been replaced by [`tf.data`](https://www.tensorflow.org/versions/r2.13/api_docs/python/tf/data). Use `tf.data.Dataset.from_tensor_slices(tuple(tensor_list)).shuffle(tf.shape(input_tensor, out_type=tf.int64)[0]).repeat(num_epochs)`. If `shuffle=False`, omit the `.shuffle(...)`.

Implemented using a Queue -- a `QueueRunner` for the Queue
is added to the current `Graph`'s `QUEUE_RUNNER` collection.

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| ## Args ||
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| `tensor_list` | A list of `Tensor` objects. Every `Tensor` in `tensor_list` must have the same size in the first dimension. |
| `num_epochs` | An integer (optional). If specified, `slice_input_producer` produces each slice `num_epochs` times before generating an `OutOfRange` error. If not specified, `slice_input_producer` can cycle through the slices an unlimited number of times. |
| `shuffle` | Boolean. If true, the integers are randomly shuffled within each epoch. |
| `seed` | An integer (optional). Seed used if shuffle == True. |
| `capacity` | An integer. Sets the queue capacity. |
| `shared_name` | (optional). If set, this queue will be shared under the given name across multiple sessions. |
| `name` | A name for the operations (optional). |

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| ## Returns ||
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| A list of tensors, one for each element of `tensor_list`. If the tensor in `tensor_list` has shape `[N, a, b, .., z]`, then the corresponding output tensor will have shape `[a, b, ..., z]`. ||

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| ## Raises ||
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| `ValueError` | if `slice_input_producer` produces nothing from `tensor_list`. |

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## eager compatibility

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Input pipelines based on Queues are not supported when eager execution is
enabled. Please use the [`tf.data`](https://www.tensorflow.org/versions/r2.13/api_docs/python/tf/data) API to ingest data under eager execution.

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