12c826816d
* chunked cross entropy loss * refactor so we can add test * use relative import * update schema description
41 lines
1.1 KiB
Python
41 lines
1.1 KiB
Python
"""
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test suite for chunked cross entropy
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"""
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import pytest
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import torch
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from torch import nn
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from axolotl.monkeypatch.loss.chunked import get_causal_lm_loss
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@pytest.fixture
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def chunked_fixtures():
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model_dim = 512
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vocab_size = 1024 * 256
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seq_len = 2048
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batch_size = 1
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lm_head = nn.Linear(model_dim, vocab_size)
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hidden_state = torch.randn(batch_size, seq_len, model_dim)
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labels = torch.randint(low=0, high=vocab_size, size=(batch_size, seq_len))
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return lm_head, hidden_state, labels, vocab_size
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def test_chunked_forward(chunked_fixtures): # pylint: disable=redefined-outer-name
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lm_head, hidden_state, labels, vocab_size = chunked_fixtures
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lm_loss = get_causal_lm_loss()
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logits = lm_head(hidden_state)
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chunked_lm_loss = lm_loss(logits, labels)
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logits_flattened = logits.view(-1, vocab_size)
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labels_flattened = labels.view(-1)
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loss = nn.functional.cross_entropy(
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logits_flattened.float(), labels_flattened, reduction="mean"
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)
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assert torch.allclose(chunked_lm_loss, loss, atol=1e-2, rtol=1e-2)
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