CustomHelper
Inherits From: Helper
Defined in tensorflow/contrib/seq2seq/python/ops/helper.py
.
See the guide: Seq2seq Library (contrib) > Dynamic Decoding
Base abstract class that allows the user to customize sampling.
batch_size
Batch size of tensor returned by sample
.
Returns a scalar int32 tensor.
sample_ids_dtype
DType of tensor returned by sample
.
Returns a DType.
sample_ids_shape
Shape of tensor returned by sample
, excluding the batch dimension.
Returns a TensorShape
.
__init__
__init__( initialize_fn, sample_fn, next_inputs_fn, sample_ids_shape=None, sample_ids_dtype=None )
Initializer.
initialize_fn
: callable that returns (finished, next_inputs)
for the first iteration.sample_fn
: callable that takes (time, outputs, state)
and emits tensor sample_ids
.next_inputs_fn
: callable that takes (time, outputs, state, sample_ids)
and emits (finished, next_inputs, next_state)
.sample_ids_shape
: Either a list of integers, or a 1-D Tensor of type int32
, the shape of each value in the sample_ids
batch. Defaults to a scalar.sample_ids_dtype
: The dtype of the sample_ids
tensor. Defaults to int32.initialize
initialize(name=None)
Returns (initial_finished, initial_inputs)
.
next_inputs
next_inputs( time, outputs, state, sample_ids, name=None )
Returns (finished, next_inputs, next_state)
.
sample
sample( time, outputs, state, name=None )
Returns sample_ids
.
© 2018 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/api_docs/python/tf/contrib/seq2seq/CustomHelper