| |
| |
| """Llama 3.2 90B decoder JSON must match ModelOptimizations baseline except LI_QKV_DECODE (issue #36378).""" |
| from pathlib import Path |
|
|
| import pytest |
|
|
| from models.tt_transformers.tt.model_config import ( |
| DecodersPrecision, |
| MathFidelitySetting, |
| ModelOptimizations, |
| OpGroup, |
| TensorGroup, |
| parse_decoder_json, |
| ) |
|
|
| _MN = "Llama-3.2-90B-Instruct" |
| _TT_ROOT = Path(__file__).resolve().parents[1] |
| _ACC = _TT_ROOT / "model_params" / _MN / "accuracy_decoder_config.json" |
| _PERF = _TT_ROOT / "model_params" / _MN / "performance_decoder_config.json" |
|
|
|
|
| def _tensor_map(m: ModelOptimizations): |
| return { |
| k.name: m.tensor_dtype_settings[k].name |
| for k in TensorGroup |
| if k in m.tensor_dtype_settings and m.tensor_dtype_settings[k] is not None |
| } |
|
|
|
|
| def _op_map(m: ModelOptimizations): |
| return {k.name: m.op_fidelity_settings[k].name for k in OpGroup if k in m.op_fidelity_settings} |
|
|
|
|
| def _assert_json_matches_baseline_except_qkv_decode(json_path: Path, opt_fn): |
| baseline = opt_fn(_MN) |
| b_tensor = _tensor_map(baseline) |
| b_op = _op_map(baseline) |
| loaded = parse_decoder_json(json_path, default_optimization=opt_fn) |
| n = len(loaded.decoder_optimizations) |
| assert n == 80 |
| for di in range(n): |
| j = loaded.decoder_optimizations[di] |
| j_tensor = _tensor_map(j) |
| j_op = _op_map(j) |
| assert j_tensor == b_tensor, f"decoder {di} tensor_dtype mismatch" |
| for ok, vb in b_op.items(): |
| jv = j_op.get(ok) |
| if ok == OpGroup.LI_QKV_DECODE.name: |
| assert ( |
| vb == MathFidelitySetting.HIFI2.name and jv == MathFidelitySetting.HIFI2_NOL1ACC.name |
| ), f"decoder {di} LI_QKV_DECODE expected HIFI2->HIFI2_NOL1ACC, got {vb}->{jv}" |
| else: |
| assert jv == vb, f"decoder {di} op {ok} baseline={vb} json={jv}" |
|
|
|
|
| @pytest.mark.skipif(not _ACC.is_file(), reason="accuracy_decoder_config.json not present") |
| def test_llama90b_accuracy_decoder_json_matches_baseline_except_qkv_decode(): |
| _assert_json_matches_baseline_except_qkv_decode(_ACC, ModelOptimizations.accuracy) |
|
|
|
|
| @pytest.mark.skipif(not _PERF.is_file(), reason="performance_decoder_config.json not present") |
| def test_llama90b_performance_decoder_json_matches_baseline_except_qkv_decode(): |
| _assert_json_matches_baseline_except_qkv_decode(_PERF, ModelOptimizations.performance) |
|
|
|
|
| def test_llama90b_decoders_precision_without_json_layers_match_accuracy_baseline(): |
| """When no JSON is used, DecodersPrecision repeats optimization_level(model_name) per layer.""" |
| base = ModelOptimizations.accuracy(_MN) |
| dp = DecodersPrecision(80, _MN, base) |
| for i in range(80): |
| assert dp.decoder_optimizations[i]._full_name == base._full_name |
|
|
