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45eee48 | 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 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 | """Tests for parametric fallback in simulation.py.
These test the fallback paths that run when real training is unavailable.
We force fallback by monkeypatching _get_real_curves to return None.
"""
from __future__ import annotations
from unittest.mock import patch
from ml_training_debugger.scenarios import sample_scenario
from ml_training_debugger.simulation import (
gen_loss_history,
gen_val_accuracy_history,
gen_val_loss_history,
)
def _force_fallback(*args, **kwargs):
return None
class TestParametricFallbackLoss:
@patch("ml_training_debugger.simulation._get_real_curves", _force_fallback)
def test_task_001_fallback(self) -> None:
s = sample_scenario("task_001", seed=42)
hist = gen_loss_history(s)
assert len(hist) == 20
@patch("ml_training_debugger.simulation._get_real_curves", _force_fallback)
def test_task_002_fallback(self) -> None:
s = sample_scenario("task_002", seed=42)
hist = gen_loss_history(s)
assert len(hist) == 20
@patch("ml_training_debugger.simulation._get_real_curves", _force_fallback)
def test_task_003_fallback(self) -> None:
s = sample_scenario("task_003", seed=42)
hist = gen_loss_history(s)
assert len(hist) == 20
@patch("ml_training_debugger.simulation._get_real_curves", _force_fallback)
def test_task_004_fallback(self) -> None:
s = sample_scenario("task_004", seed=42)
hist = gen_loss_history(s)
assert len(hist) == 20
@patch("ml_training_debugger.simulation._get_real_curves", _force_fallback)
def test_task_005_fallback(self) -> None:
s = sample_scenario("task_005", seed=42)
hist = gen_loss_history(s)
assert len(hist) == 20
@patch("ml_training_debugger.simulation._get_real_curves", _force_fallback)
def test_task_006_fallback(self) -> None:
s = sample_scenario("task_006", seed=42)
hist = gen_loss_history(s)
assert len(hist) == 20
@patch("ml_training_debugger.simulation._get_real_curves", _force_fallback)
def test_task_007_fallback(self) -> None:
s = sample_scenario("task_007", seed=42)
hist = gen_loss_history(s)
assert len(hist) == 20
class TestParametricFallbackValAcc:
@patch("ml_training_debugger.simulation._get_real_curves", _force_fallback)
def test_task_001_fallback(self) -> None:
s = sample_scenario("task_001", seed=42)
hist = gen_val_accuracy_history(s)
assert len(hist) == 20
@patch("ml_training_debugger.simulation._get_real_curves", _force_fallback)
def test_task_003_fallback(self) -> None:
s = sample_scenario("task_003", seed=42)
hist = gen_val_accuracy_history(s)
assert len(hist) == 20
@patch("ml_training_debugger.simulation._get_real_curves", _force_fallback)
def test_task_004_fallback(self) -> None:
s = sample_scenario("task_004", seed=42)
hist = gen_val_accuracy_history(s)
assert len(hist) == 20
@patch("ml_training_debugger.simulation._get_real_curves", _force_fallback)
def test_task_005_fallback(self) -> None:
s = sample_scenario("task_005", seed=42)
hist = gen_val_accuracy_history(s)
assert len(hist) == 20
@patch("ml_training_debugger.simulation._get_real_curves", _force_fallback)
def test_task_006_fallback(self) -> None:
s = sample_scenario("task_006", seed=42)
hist = gen_val_accuracy_history(s)
assert len(hist) == 20
@patch("ml_training_debugger.simulation._get_real_curves", _force_fallback)
def test_task_007_fallback(self) -> None:
s = sample_scenario("task_007", seed=42)
hist = gen_val_accuracy_history(s)
assert len(hist) == 20
class TestParametricFallbackValLoss:
@patch("ml_training_debugger.simulation._get_real_curves", _force_fallback)
def test_task_001_fallback(self) -> None:
s = sample_scenario("task_001", seed=42)
hist = gen_val_loss_history(s)
assert len(hist) == 20
@patch("ml_training_debugger.simulation._get_real_curves", _force_fallback)
def test_task_004_fallback(self) -> None:
s = sample_scenario("task_004", seed=42)
hist = gen_val_loss_history(s)
assert len(hist) == 20
@patch("ml_training_debugger.simulation._get_real_curves", _force_fallback)
def test_task_005_fallback(self) -> None:
s = sample_scenario("task_005", seed=42)
hist = gen_val_loss_history(s)
assert len(hist) == 20
@patch("ml_training_debugger.simulation._get_real_curves", _force_fallback)
def test_task_006_fallback(self) -> None:
s = sample_scenario("task_006", seed=42)
hist = gen_val_loss_history(s)
assert len(hist) == 20
@patch("ml_training_debugger.simulation._get_real_curves", _force_fallback)
def test_task_007_fallback(self) -> None:
s = sample_scenario("task_007", seed=42)
hist = gen_val_loss_history(s)
assert len(hist) == 20
@patch("ml_training_debugger.simulation._get_real_curves", _force_fallback)
def test_fallback_default(self) -> None:
"""Test the final fallback path for unknown root cause."""
from ml_training_debugger.models import RootCauseDiagnosis
from ml_training_debugger.scenarios import ScenarioParams
# Use scheduler root cause but force fallback
s = ScenarioParams(
task_id="task_999",
root_cause=RootCauseDiagnosis.SCHEDULER_MISCONFIGURED,
seed=42,
)
hist = gen_val_loss_history(s)
assert len(hist) == 20
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