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[testing] fix cwm #42261

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Merged
merged 4 commits into from
Nov 19, 2025
+21 −76
Merged

[testing] fix cwm #42261

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516af7c
fix
ydshieh Nov 18, 2025
8645170
fix
ydshieh Nov 19, 2025
fb81067
fix
ydshieh Nov 19, 2025
e7cb6cb
fix
ydshieh Nov 19, 2025
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97 changes: 21 additions & 76 deletions tests/models/cwm/test_modeling_cwm.py
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Original file line number Diff line number Diff line change
Expand Up @@ -17,6 +17,7 @@
from transformers import is_torch_available
from transformers.testing_utils import (
cleanup,
require_read_token,
require_torch,
require_torch_accelerator,
slow,
Expand Down Expand Up @@ -85,6 +86,7 @@ class CwmModelTest(CausalLMModelTest, unittest.TestCase):

@require_torch_accelerator
@slow
@require_read_token
class CwmIntegrationTest(unittest.TestCase):
def setUp(self):
cleanup(torch_device, gc_collect=True)
Expand Down Expand Up @@ -116,45 +118,14 @@ def test_cwm_integration(self):
with torch.no_grad():
out = model(**inputs)

# fmt: off
expected_logits = torch.tensor(
[
0.5625,
2.9531,
9.1875,
0.4746,
-0.3613,
2.2031,
2.9844,
1.5312,
0.5859,
1.5391,
2.7500,
3.4375,
2.0156,
2.1719,
1.5469,
2.5469,
2.8438,
1.8203,
1.7188,
1.3984,
1.0469,
0.1748,
0.4453,
0.1533,
-0.1157,
0.8516,
2.2344,
5.2188,
1.2891,
1.5234,
0.8555,
0.6992,
],
[0.5625, 2.9531, 9.1875, 0.5039, -0.3262, 2.2344, 3.0312, 1.5312, 0.5664, 1.5625, 2.7656, 3.4219, 2.0312, 2.1719, 1.5391, 2.5469, 2.8281, 1.8125, 1.7109, 1.3906, 1.0391, 0.1621, 0.4277, 0.1455, -0.1230, 0.8477, 2.2344, 5.2188, 1.2969, 1.5547, 0.8516, 0.7148],
dtype=torch.bfloat16,
).to(model.device)
# fmt: on

self.assertTrue(torch.allclose(out.logits[0, -1, :32], expected_logits, atol=1e-2, rtol=1e-2))
torch.testing.assert_close(out.logits[0, -1, :32], expected_logits, atol=1e-2, rtol=1e-2)

self.assertEqual(out.logits.shape[1], inputs.input_ids.shape[1])
self.assertEqual(out.logits.shape[2], model.config.vocab_size)
Expand All @@ -166,10 +137,13 @@ def test_cwm_sliding_window_long_sequence(self):
from transformers import AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("facebook/cwm")
model = CwmForCausalLM.from_pretrained("facebook/cwm", device_map="auto", dtype=torch.bfloat16)
# original `sliding_window` is `8192`, but it causes GPU OOM on A10
model = CwmForCausalLM.from_pretrained(
"facebook/cwm", device_map="auto", dtype=torch.bfloat16, sliding_window=4096
)

sliding_window = model.config.sliding_window
long_text = "for i in range(1000):\n print(f'iteration {i}')\n" * 600
long_text = "for i in range(1000):\n print(f'iteration {i}')\n" * 270

inputs = tokenizer(long_text, return_tensors="pt").to(model.device)
seq_len = inputs.input_ids.shape[1]
Expand All @@ -182,50 +156,21 @@ def test_cwm_sliding_window_long_sequence(self):
with torch.no_grad():
out = model(**inputs)

# fmt: off
expected_logits = torch.tensor(
[
4.7812,
6.1875,
13.1875,
4.4062,
5.0312,
3.9844,
6.6875,
4.8438,
2.3125,
6.5000,
4.4688,
0.5195,
5.6562,
3.3125,
2.7500,
4.9062,
5.5938,
4.1562,
3.9531,
2.4062,
3.2812,
2.8594,
3.4688,
2.9688,
2.6875,
3.4531,
2.7344,
7.2812,
4.5000,
5.7500,
2.3438,
5.9688,
],
[5.2812, 6.4688, 12.8125, 4.6875, 5.2500, 4.2500, 6.9688, 4.9375, 2.7656, 6.5938, 4.9688, 1.1016, 5.9375, 3.7500, 3.1094, 5.5312, 6.1250, 4.7500, 4.5312, 2.8281, 4.0625, 3.3125, 3.9219, 3.3906, 3.1406, 3.6719, 3.2031, 7.0938, 4.8750, 6.0000, 2.7188, 6.2500],
dtype=torch.bfloat16,
).to(model.device)
# fmt: on

self.assertTrue(torch.allclose(out.logits[0, -1, :32], expected_logits, atol=1e-2, rtol=1e-2))
torch.testing.assert_close(out.logits[0, -1, :32], expected_logits, atol=1e-2, rtol=1e-2)

self.assertEqual(out.logits.shape[1], seq_len)
self.assertEqual(out.logits.shape[2], model.config.vocab_size)
self.assertFalse(torch.isnan(out.logits).any())
self.assertFalse(torch.isinf(out.logits).any())
logits = out.logits.to("cpu")

self.assertEqual(logits.shape[1], seq_len)
self.assertEqual(logits.shape[2], model.config.vocab_size)
self.assertFalse(torch.isnan(logits).any())
self.assertFalse(torch.isinf(logits).any())

for i, layer in enumerate(model.model.layers):
if model.config.layer_types[i] == "sliding_attention":
Expand Down