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3b27ed7996
Summary: Pull Request resolved: https://github.com/facebookresearch/pytext/pull/1510 this is the main pr that switches on hydra functionality in fairseq we migrate "args" object into omegaconf "DictConfig" at all legacy entry points in addition this migrates various components from secondary registries (like bpe encoders and tokenizers) to make the migration smoother i am going through code that references migrated fairseq components and changing it to inherit from "Legacy*" components instead. hopefully tests will catch most of this Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/1343 Reviewed By: myleott Differential Revision: D23973928 Pulled By: alexeib fbshipit-source-id: dd9554981fff51ea75c1ff343874d1d6e61793c9
71 lines
3.2 KiB
Python
71 lines
3.2 KiB
Python
# Copyright (c) Facebook, Inc. and its affiliates.
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#
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# This source code is licensed under the MIT license found in the
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# LICENSE file in the root directory of this source tree.
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import logging
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import unittest
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from fairseq.dataclass.utils import convert_namespace_to_omegaconf
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from fairseq.models.transformer import TransformerModel
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from tests.test_sequence_generator import get_dummy_task_and_parser
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class TestInferenceDropout(unittest.TestCase):
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def setUp(self):
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self.task, self.parser = get_dummy_task_and_parser()
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TransformerModel.add_args(self.parser)
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self.args = self.parser.parse_args([])
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self.args.encoder_layers = 2
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self.args.decoder_layers = 1
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logging.disable(logging.CRITICAL)
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def tearDown(self):
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logging.disable(logging.NOTSET)
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def test_sets_inference_dropout_to_true(self):
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self.args.retain_dropout = True
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self.transformer_model = TransformerModel.build_model(self.args, self.task)
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cfg = convert_namespace_to_omegaconf(self.args)
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self.transformer_model.prepare_for_inference_(cfg)
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assert self.transformer_model.encoder.dropout_module.apply_during_inference
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assert self.transformer_model.decoder.dropout_module.apply_during_inference
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for layer in self.transformer_model.encoder.layers:
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assert layer.dropout_module.apply_during_inference
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def test_inference_dropout_false_by_default(self):
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self.transformer_model = TransformerModel.build_model(self.args, self.task)
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cfg = convert_namespace_to_omegaconf(self.args)
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self.transformer_model.prepare_for_inference_(cfg)
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assert not self.transformer_model.encoder.dropout_module.apply_during_inference
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assert not self.transformer_model.decoder.dropout_module.apply_during_inference
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for layer in self.transformer_model.encoder.layers:
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assert not layer.dropout_module.apply_during_inference
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for layer in self.transformer_model.decoder.layers:
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assert not layer.dropout_module.apply_during_inference
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def test_applies_training_mode(self):
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self.transformer_model = TransformerModel.build_model(self.args, self.task)
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assert self.transformer_model.encoder.dropout_module.training
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for layer in self.transformer_model.encoder.layers:
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assert layer.dropout_module.training
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self.transformer_model.eval()
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assert not self.transformer_model.decoder.dropout_module.training
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for layer in self.transformer_model.encoder.layers:
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assert not layer.dropout_module.training
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def test_retain_modules(self):
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self.args.retain_dropout = True
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self.args.retain_dropout_modules = [
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"TransformerEncoder",
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"TransformerEncoderLayer",
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]
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self.transformer_model = TransformerModel.build_model(self.args, self.task)
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cfg = convert_namespace_to_omegaconf(self.args)
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self.transformer_model.prepare_for_inference_(cfg)
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assert self.transformer_model.encoder.dropout_module.apply_during_inference
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assert not self.transformer_model.decoder.dropout_module.apply_during_inference
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for layer in self.transformer_model.decoder.layers:
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assert not layer.dropout_module.apply_during_inference
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