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Relax transformers lower bound to >=4.41 (#364)

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Abdul Fatir 2025-11-05 14:27:46 +01:00 committed by GitHub
parent c23d34cd88
commit 93419cfe9f
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2 changed files with 4 additions and 4 deletions
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2
pyproject.toml
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@ -15,7 +15,7 @@ license = { file = "LICENSE" }
requires-python = ">=3.10"
dependencies = [
"torch>=2.0,<3",
"transformers>=4.49,<5",
"transformers>=4.41,<5",
"accelerate>=0.34,<2",
"numpy>=1.21,<3",
"einops>=0.7.0,<1",

6
test/test_chronos2.py
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@ -327,7 +327,7 @@ def test_when_input_is_invalid_then_predict_raises_value_error(pipeline, inputs,
@pytest.mark.parametrize("input_dtype", [torch.float32, torch.bfloat16, torch.int64])
def test_pipeline_predict_can_handle_different_model_and_input_dtypes(dtype: torch.dtype, input_dtype: torch.dtype):
pipeline = BaseChronosPipeline.from_pretrained(
Path(__file__).parent / "dummy-chronos2-model", device_map="cpu", dtype=dtype
Path(__file__).parent / "dummy-chronos2-model", device_map="cpu", torch_dtype=dtype
)
context = 10 * torch.rand(size=(4, 3, 16)) + 10
context = context.to(dtype=input_dtype)
@ -1018,13 +1018,13 @@ def test_eager_and_sdpa_produce_identical_outputs(pipeline):
# Reload pipeline with SDPA
model_path = Path(__file__).parent / "dummy-chronos2-model"
pipeline_sdpa = BaseChronosPipeline.from_pretrained(
model_path, device_map="cpu", attn_implementation="sdpa", dtype=torch.float32
model_path, device_map="cpu", attn_implementation="sdpa", torch_dtype=torch.float32
)
# Note: the original pipeline fixture uses default attn_implementation which should be sdpa
# Force eager for comparison
pipeline_eager = BaseChronosPipeline.from_pretrained(
model_path, device_map="cpu", attn_implementation="eager", dtype=torch.float32
model_path, device_map="cpu", attn_implementation="eager", torch_dtype=torch.float32
)
# Test 1: Simple univariate input