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70 lines
1.8 KiB
70 lines
1.8 KiB
#!/usr/bin/env python
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# -*- encoding: utf-8 -*-
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import pytest
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import torch
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from checks_2d.check_layer_2d import (
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check_classifier_given_embed_weight,
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check_classifier_no_given_weight,
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check_embed,
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check_layernorm,
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check_linear,
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check_loss,
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check_patch_embed,
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check_vocab_parallel_classifier_given_embed_weight,
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check_vocab_parallel_classifier_no_given_weight,
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check_vocab_parallel_embed,
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check_vocab_parallel_loss,
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)
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from checks_2d.check_operation_2d import check_AB, check_ABT, check_ATB
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from colossalai.core import global_context as gpc
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from colossalai.initialize import launch
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from colossalai.logging import disable_existing_loggers
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from colossalai.testing import rerun_if_address_is_in_use, spawn
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CONFIG = dict(parallel=dict(pipeline=dict(size=1), tensor=dict(size=4, mode='2d')),)
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def check_operations():
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check_AB()
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check_ABT()
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check_ATB()
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def check_layer():
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check_linear()
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check_layernorm()
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check_embed()
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check_patch_embed()
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check_vocab_parallel_embed()
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check_classifier_no_given_weight()
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check_vocab_parallel_classifier_no_given_weight()
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check_classifier_given_embed_weight()
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check_vocab_parallel_classifier_given_embed_weight()
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check_loss()
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check_vocab_parallel_loss()
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def check_layer_and_operation(rank, world_size, port):
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disable_existing_loggers()
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launch(config=CONFIG, rank=rank, world_size=world_size, host='localhost', port=port, backend='nccl')
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torch.backends.cuda.matmul.allow_tf32 = False
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torch.backends.cudnn.allow_tf32 = False
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torch.backends.cudnn.deterministic = True
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# check_operations()
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check_layer()
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gpc.destroy()
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torch.cuda.empty_cache()
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@pytest.mark.dist
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@rerun_if_address_is_in_use()
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def test_2d():
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spawn(check_layer_and_operation, 4)
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if __name__ == '__main__':
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test_2d()
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