Source code for texar.torch.modules.connectors.connector_base

# Copyright 2019 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.
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Base class for connectors that transform inputs into specified output shape.

from abc import ABC
from typing import Generic, Optional, TypeVar
from texar.torch.hyperparams import HParams
from texar.torch.module_base import ModuleBase

__all__ = [

OutputSize = TypeVar('OutputSize')
HParamsType = Optional[HParams]

[docs]class ConnectorBase(ModuleBase, Generic[OutputSize], ABC): r"""Base class inherited by all connector classes. A connector is to transform inputs into outputs with any specified structure and shape. For example, transforming 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 torch.Size, or a tuple of torch.Sizes. For example, to transform inputs to have decoder state size, set :python:`output_size=decoder.state_size`. hparams (dict, optional): Hyperparameters. Missing hyperparameter will be set to default values. See :meth:`default_hparams` for the hyperparameter structure and default values. """ def __init__(self, output_size: OutputSize, hparams: HParamsType = None): super().__init__(hparams=hparams) self._output_size = output_size
[docs] @staticmethod def default_hparams(): r"""Returns a dictionary of hyperparameters with default values. """ return { "name": "connector" }
@property def output_size(self): return self._output_size