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.

Attributes:

reader_ref: Op that implements the reader.
supports_serialize: Whether 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.

Methods

`num_records_produced`

View source

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`

View source

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`

View source

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`

View source

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`

View source

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`

View source

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`

View source

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.