mirror of
https://github.com/storytold/storyteller-ml.git
synced 2026-10-18 07:41:03 +00:00
Brandon Thomas
77 lines
2.4 KiB
Python
77 lines
2.4 KiB
Python
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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try:
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import apex
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apex_available = True
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except Exception:
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apex_available = False
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import os
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import tempfile
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import onnx
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import pytest
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import torch
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import nemo.collections.nlp as nemo_nlp
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from nemo.core.classes import typecheck
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def get_pretrained_bert_345m_uncased_model():
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model_name = "megatron-bert-345m-uncased"
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model = nemo_nlp.modules.get_lm_model(pretrained_model_name=model_name)
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if torch.cuda.is_available():
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model = model.cuda()
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return model
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class TestMegatron:
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@pytest.mark.run_only_on('GPU')
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@pytest.mark.unit
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def test_list_pretrained_models(self):
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pretrained_lm_models = nemo_nlp.modules.get_pretrained_lm_models_list()
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assert len(pretrained_lm_models) > 0
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@pytest.mark.with_downloads()
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@pytest.mark.run_only_on('GPU')
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@pytest.mark.unit
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@pytest.mark.skip("Only one Megatron model is allowed")
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def test_get_model(self):
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model = get_pretrained_bert_345m_uncased_model()
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assert isinstance(model, nemo_nlp.modules.MegatronBertEncoder)
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typecheck.set_typecheck_enabled(enabled=False)
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inp = model.input_example()
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out = model.forward(*inp)
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typecheck.set_typecheck_enabled(enabled=True)
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@pytest.mark.skipif(not os.path.exists('/home/TestData/nlp'), reason='Not a Jenkins machine')
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@pytest.mark.with_downloads()
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@pytest.mark.run_only_on('GPU')
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@pytest.mark.unit
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def test_onnx_export(self):
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model = get_pretrained_bert_345m_uncased_model()
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assert model
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with tempfile.TemporaryDirectory() as tmpdir:
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# Generate filename in the temporary directory.
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# Test export.
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model.export(os.path.join(".", "megatron.onnx"))
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if __name__ == "__main__":
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t = TestMegatron()
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t.test_onnx_export()
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