An integer (optional). If specified, string_input_producer
produces each string from string_tensornum_epochs times before
generating an OutOfRange error. If not specified,
string_input_producer can cycle through the strings in string_tensor
an unlimited number of times.
shuffle
Boolean. If true, the strings 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. All sessions open to the device which has
this queue will be able to access it via the shared_name. Using this in
a distributed setting means each name will only be seen by one of the
sessions which has access to this operation.
name
A name for the operations (optional).
cancel_op
Cancel op for the queue (optional).
Returns
A queue with the output strings. A QueueRunner for the Queue
is added to the current Graph's QUEUE_RUNNER collection.
Raises
ValueError
If the string_tensor is a null Python list. At runtime,
will fail with an assertion if string_tensor becomes a null tensor.
eager compatibility
Input pipelines based on Queues are not supported when eager execution is
enabled. Please use the tf.data API to ingest data under eager execution.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-04-26 UTC."],[],[],null,["# tf.compat.v1.train.string_input_producer\n\n\u003cbr /\u003e\n\n|------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.16.1/tensorflow/python/training/input.py#L203-L275) |\n\nOutput strings (e.g. filenames) to a queue for an input pipeline. (deprecated) \n\n tf.compat.v1.train.string_input_producer(\n string_tensor,\n num_epochs=None,\n shuffle=True,\n seed=None,\n capacity=32,\n shared_name=None,\n name=None,\n cancel_op=None\n )\n\n| **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`](../../../../tf/data). Use `tf.data.Dataset.from_tensor_slices(string_tensor).shuffle(tf.shape(input_tensor, out_type=tf.int64)[0]).repeat(num_epochs)`. If `shuffle=False`, omit the `.shuffle(...)`.\n| **Note:** if `num_epochs` is not `None`, this function creates local counter `epochs`. Use `local_variables_initializer()` to initialize local variables.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `string_tensor` | A 1-D string tensor with the strings to produce. |\n| `num_epochs` | An integer (optional). If specified, `string_input_producer` produces each string from `string_tensor` `num_epochs` times before generating an `OutOfRange` error. If not specified, `string_input_producer` can cycle through the strings in `string_tensor` an unlimited number of times. |\n| `shuffle` | Boolean. If true, the strings are randomly shuffled within each epoch. |\n| `seed` | An integer (optional). Seed used if shuffle == True. |\n| `capacity` | An integer. Sets the queue capacity. |\n| `shared_name` | (optional). If set, this queue will be shared under the given name across multiple sessions. All sessions open to the device which has this queue will be able to access it via the shared_name. Using this in a distributed setting means each name will only be seen by one of the sessions which has access to this operation. |\n| `name` | A name for the operations (optional). |\n| `cancel_op` | Cancel op for the queue (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A queue with the output strings. A `QueueRunner` for the Queue is added to the current `Graph`'s `QUEUE_RUNNER` collection. ||\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Raises ------ ||\n|--------------|-----------------------------------------------------------------------------------------------------------------------------|\n| `ValueError` | If the string_tensor is a null Python list. At runtime, will fail with an assertion if string_tensor becomes a null tensor. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\neager compatibility\n-------------------\n\n\u003cbr /\u003e\n\nInput pipelines based on Queues are not supported when eager execution is\nenabled. Please use the [`tf.data`](../../../../tf/data) API to ingest data under eager execution.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e"]]