tf.compat.v1.ReaderBase
Base class for different Reader types, that produce a record every step.
tf.compat.v1.ReaderBase(
    reader_ref, supports_serialize=False
)
  Conceptually, Readers convert string 'work units' into records (key, value pairs). Typically the 'work units' are filenames and the records are extracted from the contents of those files. We want a single record produced per step, but a work unit can correspond to many records.
Therefore we introduce some decoupling using a queue. The queue contains the work units and the Reader dequeues from the queue when it is asked to produce a record (via Read()) but it has finished the last work unit.
| Args | |
|---|---|
 reader_ref  |  The operation that implements the reader. | 
 supports_serialize  |  True if the reader implementation can serialize its state. | 
| Raises | |
|---|---|
 RuntimeError  |  If eager execution is enabled. | 
Eager Compatibility
Readers are not compatible with eager execution. Instead, please use tf.data to get data into your model.
| Attributes | |
|---|---|
 reader_ref  |  Op that implements the reader. | 
 supports_serialize  |  Whether the Reader implementation can serialize its state. | 
Methods
num_records_produced
  
num_records_produced(
    name=None
)
 Returns the number of records this reader has produced.
This is the same as the number of Read executions that have succeeded.
| Args | |
|---|---|
 name  |  A name for the operation (optional). | 
| Returns | |
|---|---|
| An int64 Tensor. | 
num_work_units_completed
  
num_work_units_completed(
    name=None
)
 Returns the number of work units this reader has finished processing.
| Args | |
|---|---|
 name  |  A name for the operation (optional). | 
| Returns | |
|---|---|
| An int64 Tensor. | 
read
  
read(
    queue, name=None
)
 Returns the next record (key, value) pair produced by a reader.
Will dequeue a work unit from queue if necessary (e.g. when the Reader needs to start reading from a new file since it has finished with the previous file).
| Args | |
|---|---|
 queue  |  A Queue or a mutable string Tensor representing a handle to a Queue, with string work items. | 
 name  |  A name for the operation (optional). | 
| Returns | |
|---|---|
| A tuple of Tensors (key, value). | |
 key  |  A string scalar Tensor. | 
 value  |  A string scalar Tensor. | 
read_up_to
  
read_up_to(
    queue, num_records, name=None
)
 Returns up to num_records (key, value) pairs produced by a reader.
Will dequeue a work unit from queue if necessary (e.g., when the Reader needs to start reading from a new file since it has finished with the previous file). It may return less than num_records even before the last batch.
| Args | |
|---|---|
 queue  |  A Queue or a mutable string Tensor representing a handle to a Queue, with string work items. | 
 num_records  |  Number of records to read. | 
 name  |  A name for the operation (optional). | 
| Returns | |
|---|---|
| A tuple of Tensors (keys, values). | |
 keys  |  A 1-D string Tensor. | 
 values  |  A 1-D string Tensor. | 
reset
  
reset(
    name=None
)
 Restore a reader to its initial clean state.
| Args | |
|---|---|
 name  |  A name for the operation (optional). | 
| Returns | |
|---|---|
| The created Operation. | 
restore_state
  
restore_state(
    state, name=None
)
 Restore a reader to a previously saved state.
Not all Readers support being restored, so this can produce an Unimplemented error.
| Args | |
|---|---|
 state  |  A string Tensor. Result of a SerializeState of a Reader with matching type. | 
 name  |  A name for the operation (optional). | 
| Returns | |
|---|---|
| The created Operation. | 
serialize_state
  
serialize_state(
    name=None
)
 Produce a string tensor that encodes the state of a reader.
Not all Readers support being serialized, so this can produce an Unimplemented error.
| Args | |
|---|---|
 name  |  A name for the operation (optional). | 
| Returns | |
|---|---|
| A string Tensor. | 
    © 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
    https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/compat/v1/ReaderBase