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import megatron.core.tensor_parallel.random |
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from megatron.core.tensor_parallel.random import model_parallel_cuda_manual_seed |
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from megatron.core.tensor_parallel.random import checkpoint |
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from tests.test_utilities import Utils |
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import pytest |
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import torch |
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def test_cuda_rng_states_tracker(): |
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rng_tracker = megatron.core.tensor_parallel.random.CudaRNGStatesTracker() |
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rng_tracker.set_states({"state1": 1234}) |
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assert(rng_tracker.get_states()["state1"] == 1234) |
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rng_tracker.reset() |
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assert(rng_tracker.get_states() == {}) |
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seed = 1111 |
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rng_tracker.add("state2", seed) |
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with pytest.raises(Exception): |
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assert(rng_tracker.add("state3", seed)) |
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with pytest.raises(Exception): |
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assert(rng_tracker.add("state2", 111)) |
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assert(rng_tracker.get_states()['state2'] is not None) |
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with pytest.raises(Exception): |
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assert() |
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rng_tracker.fork("state2") |
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torch.cuda.manual_seed(seed) |
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rng_state = torch.cuda.get_rng_state() |
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assert torch.equal(rng_tracker.get_states()['state2'], rng_state) |
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def test_model_parallel_cuda_manual_seed(): |
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Utils.initialize_model_parallel(4,2) |
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model_parallel_cuda_manual_seed(0) |
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assert(megatron.core.tensor_parallel.random._CUDA_RNG_STATE_TRACKER.get_states()['model-parallel-rng'] is not None) |
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Utils.destroy_model_parallel() |
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def test_checkpoint(): |
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def test_forward(*input): |
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return input[0]+input[1] |
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assert(torch.equal(torch.ones(16)*3,checkpoint(test_forward, None, torch.ones(16), torch.ones(16)*2))) |
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Utils.initialize_model_parallel() |
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input1 = torch.ones((4,4)) |
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checkpoint(test_forward, True, input1, torch.ones((4,4))*2) |
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assert(torch.equal(torch.ones(input1.numel()).cuda(), input1)) |
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Utils.destroy_model_parallel() |