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Convert formatting to use ruff instead of yapf + isort (#26247)

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Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
This commit is contained in:
Harry Mellor
2025-10-05 15:06:22 +01:00
committed by GitHub
parent 17edd8a807
commit d6953beb91
1508 changed files with 115244 additions and 94146 deletions
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35
tests/kernels/attention/test_pack_unpack_triton.py
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@@ -39,7 +39,7 @@ def test_pack_seq_basic_fp8():
start_idx = sum(lengths_list[:b])
seq_len = lengths_list[b]
expected_data = x[start_idx:start_idx + seq_len].to(torch.float32)
expected_data = x[start_idx : start_idx + seq_len].to(torch.float32)
actual_data = packed[b, :seq_len].to(torch.float32)
assert_close(actual_data, expected_data, rtol=1e-1, atol=1e-2)
@@ -62,7 +62,7 @@ def test_pack_seq_custom_padding_fp8():
# Check valid data
for b in range(B):
start_idx = b * 10
expected_data = x[start_idx:start_idx + 10].to(torch.float32)
expected_data = x[start_idx : start_idx + 10].to(torch.float32)
actual_data = result[b, :10].to(torch.float32)
assert_close(actual_data, expected_data, rtol=1e-1, atol=1e-2)
@@ -73,9 +73,7 @@ def test_pack_seq_custom_padding_fp8():
elif pad_value > 0:
assert torch.all(padded_data > 50) # Large positive values
else:
assert torch.allclose(padded_data,
torch.zeros_like(padded_data),
atol=1e-2)
assert torch.allclose(padded_data, torch.zeros_like(padded_data), atol=1e-2)
def test_pack_seq_default_negative_inf_padding_fp8():
@@ -93,7 +91,8 @@ def test_pack_seq_default_negative_inf_padding_fp8():
# Check that padding is large negative values (fp8 representation of -inf)
padded_data = result[:, 10:].to(torch.float32)
assert torch.all(
padded_data < -100) # fp8 -inf is represented as large negative number
padded_data < -100
) # fp8 -inf is represented as large negative number
def test_pack_seq_edge_cases_fp8():
@@ -142,7 +141,7 @@ def test_pack_seq_different_block_sizes_fp8():
# Check that valid data is preserved (within fp8 precision)
for b in range(B):
start_idx = b * 25
expected_data = x[start_idx:start_idx + 25].to(torch.float32)
expected_data = x[start_idx : start_idx + 25].to(torch.float32)
actual_data = result[b, :25].to(torch.float32)
assert_close(actual_data, expected_data, rtol=1e-1, atol=1e-2)
@@ -198,10 +197,7 @@ def test_pack_unpack_roundtrip_fp8():
# Unpack without explicit start locations (computed in kernel)
unpacked_with_loc = unpack_seq_triton(packed, lengths)
assert_close(x_f32,
unpacked_with_loc.to(torch.float32),
rtol=1e-3,
atol=1e-2)
assert_close(x_f32, unpacked_with_loc.to(torch.float32), rtol=1e-3, atol=1e-2)
def test_unpack_seq_triton_edge_cases_fp8():
@@ -216,10 +212,7 @@ def test_unpack_seq_triton_edge_cases_fp8():
packed = pack_seq_triton(x, lengths)
unpacked = unpack_seq_triton(packed, lengths)
assert unpacked.shape == x.shape
assert_close(x.to(torch.float32),
unpacked.to(torch.float32),
rtol=1e-1,
atol=1e-2)
assert_close(x.to(torch.float32), unpacked.to(torch.float32), rtol=1e-1, atol=1e-2)
# Test with very short sequences
x = torch.randn(20, 4, 8, dtype=torch.float32, device=device) * 0.1
@@ -228,10 +221,9 @@ def test_unpack_seq_triton_edge_cases_fp8():
packed = pack_seq_triton(x, lengths)
unpacked = unpack_seq_triton(packed, lengths)
# Only compare the first 3 elements that were actually packed
assert_close(x[:3].to(torch.float32),
unpacked.to(torch.float32),
rtol=1e-1,
atol=1e-2)
assert_close(
x[:3].to(torch.float32), unpacked.to(torch.float32), rtol=1e-1, atol=1e-2
)
x = torch.randn(15, 8, 16, dtype=torch.float32, device=device) * 0.1
x = x.to(dtype=dtype)
@@ -239,7 +231,4 @@ def test_unpack_seq_triton_edge_cases_fp8():
packed = pack_seq_triton(x, lengths)
unpacked = unpack_seq_triton(packed, lengths)
assert unpacked.shape == x.shape
assert_close(x.to(torch.float32),
unpacked.to(torch.float32),
rtol=1e-1,
atol=1e-2)
assert_close(x.to(torch.float32), unpacked.to(torch.float32), rtol=1e-1, atol=1e-2)