30 lines
1.1 KiB
Python
30 lines
1.1 KiB
Python
#####################################################
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# Copyright (c) Xuanyi Dong [GitHub D-X-Y], 2021.03 #
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#####################################################
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# pytest ./tests/test_super_vit.py -s #
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#####################################################
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import sys
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import unittest
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import torch
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from xautodl.xmodels import transformers
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from xautodl.utils.flop_benchmark import count_parameters
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class TestSuperViT(unittest.TestCase):
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"""Test the super re-arrange layer."""
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def test_super_vit(self):
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model = transformers.get_transformer("vit-base")
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tensor = torch.rand((16, 3, 256, 256))
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print("The tensor shape: {:}".format(tensor.shape))
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print(model)
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outs = model(tensor)
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print("The output tensor shape: {:}".format(outs.shape))
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def test_model_size(self):
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name2config = transformers.name2config
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for name, config in name2config.items():
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model = transformers.get_transformer(config)
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size = count_parameters(model, "mb", True)
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print('{:10s} : size={:.2f}MB'.format(name, size))
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