# Copyright 2018 The Texar Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
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"""
Base class for connectors that transform inputs into specified output shape.
"""
from texar.tf.module_base import ModuleBase
__all__ = [
"ConnectorBase"
]
[docs]class ConnectorBase(ModuleBase):
"""Base class inherited by all connector classes. A connector is to
transform inputs into outputs with any specified structure and shape.
For example, tranforming the final state of an encoder to the initial
state of a decoder, and performing stochastic sampling in between as
in Variational Autoencoders (VAEs).
Args:
output_size: Size of output **excluding** the batch dimension. For
example, set `output_size` to `dim` to generate output of
shape `[batch_size, dim]`.
Can be an `int`, a tuple of `int`, a Tensorshape, or a tuple of
TensorShapes.
For example, to transform inputs to have decoder state size, set
`output_size=decoder.state_size`.
hparams (dict, optional): Hyperparameters. Missing
hyperparamerter will be set to default values. See
:meth:`default_hparams` for the hyperparameter sturcture and
default values.
"""
def __init__(self, output_size, hparams=None):
ModuleBase.__init__(self, hparams)
self._output_size = output_size
[docs] @staticmethod
def default_hparams():
"""Returns a dictionary of hyperparameters with default values.
"""
return {
"name": "connector"
}
def _build(self, *args, **kwargs):
"""Transforms inputs to outputs with specified shape.
"""
raise NotImplementedError
@property
def output_size(self):
"""The output size.
"""
return self._output_size