def modular_nli_reader(resources_or_conf: Union[dict, SharedResources] = None):
"""Creates a Modular NLI reader instance. Model defined in config."""
from jack.readers.multiple_choice.shared import MultipleChoiceSingleSupportInputModule
from jack.readers.natural_language_inference.modular_nli_model import ModularNLIModel
from jack.readers.multiple_choice.shared import SimpleMCOutputModule
shared_resources = create_shared_resources(resources_or_conf)
input_module = MultipleChoiceSingleSupportInputModule(shared_resources)
model_module = ModularNLIModel(shared_resources)
output_module = SimpleMCOutputModule(shared_resources)
return TFReader(shared_resources, input_module, model_module,
output_module)
def esim_snli_reader(resources_or_conf: Union[dict, SharedResources] = None):
"""Creates a SNLI reader instance (multiple choice qa model).
This particular reader uses an Enhanced LSTM Model (ESIM), as described in [1].
[1] Qian Chen et al. - Enhanced LSTM for Natural Language Inference. ACL 2017
"""
from jack.readers.multiple_choice.shared import SingleSupportFixedClassInputs
from jack.readers.natural_language_inference.esim import ESIMModel
from jack.readers.multiple_choice.shared import SimpleMCOutputModule
shared_resources = create_shared_resources(resources_or_conf)
input_module = SingleSupportFixedClassInputs(shared_resources)
model_module = ESIMModel(shared_resources)
output_module = SimpleMCOutputModule(shared_resources)
return TFReader(shared_resources, input_module, model_module,
output_module)
def dam_snli_reader(resources_or_conf: Union[dict, SharedResources] = None):
"""Creates a SNLI reader instance (multiple choice qa model).
This particular reader uses a Decomposable Attention Model, as described in [1].
[1] Ankur P. Parikh et al. - A Decomposable Attention Model for Natural Language Inference. EMNLP 2016
"""
from jack.readers.multiple_choice.shared import SingleSupportFixedClassInputs
from jack.readers.natural_language_inference.decomposable_attention import DecomposableAttentionModel
from jack.readers.multiple_choice.shared import SimpleMCOutputModule
shared_resources = create_shared_resources(resources_or_conf)
input_module = SingleSupportFixedClassInputs(shared_resources)
model_module = DecomposableAttentionModel(shared_resources)
output_module = SimpleMCOutputModule(shared_resources)
return TFReader(shared_resources, input_module, model_module,
output_module)
def cbilstm_snli_reader(resources_or_conf: Union[dict,
SharedResources] = None):
"""
Creates a SNLI reader instance (multiple choice qa model).
This particular reader uses a conditional Bidirectional LSTM, as described in [1].
[1] Tim Rocktäschel et al. - Reasoning about Entailment with Neural Attention. ICLR 2016
"""
from jack.readers.multiple_choice.shared import SingleSupportFixedClassInputs
from jack.readers.natural_language_inference.bilstm import PairOfBiLSTMOverSupportAndQuestionModel
from jack.readers.multiple_choice.shared import SimpleMCOutputModule
shared_resources = create_shared_resources(resources_or_conf)
input_module = SingleSupportFixedClassInputs(shared_resources)
model_module = PairOfBiLSTMOverSupportAndQuestionModel(shared_resources)
output_module = SimpleMCOutputModule(shared_resources)
return TFReader(shared_resources, input_module, model_module,
output_module)