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ed3aeeb | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 | from pathlib import Path
from scripts import run_mlir_batch
def test_count_text_markers_distinguishes_quant_and_float_compute(tmp_path: Path) -> None:
path = tmp_path / "sample.mlir"
path.write_text(
'\n'.join([
'%0 = "onnx.QuantizeLinear"() : () -> tensor<1xi8>',
'%1 = "onnx.DequantizeLinear"() : () -> tensor<1xf32>',
'%2 = llvm.fmul %a, %b : f32',
'%3 = "onnx.MatMulInteger"() : () -> tensor<1xi8>',
])
)
markers = run_mlir_batch.count_text_markers(path)
assert markers["onnx_quantize_linear_ops"] == 1
assert markers["onnx_dequantize_linear_ops"] == 1
assert markers["onnx_qoperator_ops"] == 1
assert markers["llvm_float_compute_ops"] == 1
assert markers["i8_mentions"] == 2
def test_eligible_rows_covers_all_active_pairs() -> None:
rows = run_mlir_batch.eligible_rows()
assert len(rows) == 21
assert all(row["eligibility"] == "ELIGIBLE" for row in rows)
assert "AD01" in {row["model_id"] for row in rows}
def test_different_setting_never_overwrites_existing_ir(tmp_path: Path) -> None:
source = tmp_path / "input.mlir"
source.write_text("module {}\n")
output = tmp_path / "model" / "mlir" / "fp32" / "onnx.mlir"
output.parent.mkdir(parents=True)
output.write_text("protected prior IR\n")
result = run_mlir_batch.run_command_stage(
model_root=tmp_path / "model",
variant="fp32",
stage="onnx_dialect_parse",
command=["/usr/bin/false"],
inputs=[source],
output=output,
command_output=None,
timeout_sec=1,
settings={"toolchain_lock_sha256": "0" * 64},
reuse_failures=False,
)
assert result["status"] == "BLOCKED"
assert result["secondary_failure_code"] == "OUTPUT_SETTINGS_CONFLICT"
assert output.read_text() == "protected prior IR\n"
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