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Suppress new Pyrefly findings before upgrading to v1.2.0 #352

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Merged
copybara-service merged 1 commit into from
Sep 9, 2026
Merged

Suppress new Pyrefly findings before upgrading to v1.2.0 #352

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4 changes: 2 additions & 2 deletions learned_optimization/outer_trainers/gradient_learner.py
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Original file line number Diff line number Diff line change
Expand Up @@ -463,8 +463,8 @@ def extract_one(idx, x):
metrics[f"mean||{cfg_name}/grad_norm"] = norm
metrics[f"mean||{family_name}/mean_loss"] = estimator_out.mean_loss
metrics[f"mean||{cfg_name}/mean_loss"] = estimator_out.mean_loss
metrics[f"sample||{family_name}/time"] = time.time() - stime
metrics[f"sample||{cfg_name}/time"] = time.time() - stime
metrics[f"sample||{family_name}/time"] = time.time() - stime # pyrefly: ignore[unsupported-operation]
metrics[f"sample||{cfg_name}/time"] = time.time() - stime # pyrefly: ignore[unsupported-operation]

metrics_list.append(metrics)

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20 changes: 10 additions & 10 deletions learned_optimization/population/examples/complex_cnn/train_threads.py
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Expand Up @@ -160,18 +160,18 @@ def mutate_fn(
beta2 = 1 - onp.exp(oml_beta2 + onp.random.normal() * 0.03)

return { # pytype: disable=bad-return-type # jax-ndarray
"learning_rate": onp.exp(loglr + offset),
"beta1": beta1,
"beta2": beta2,
"hue": onp.clip(onp.random.normal() * 0.03 + meta_params["hue"], 0, 1),
"contrast_high": contrast_high,
"contrast_low": contrast_low,
"saturation_high": saturation_high,
"saturation_low": saturation_low,
"smooth_labels": onp.clip(
"learning_rate": onp.exp(loglr + offset), # pyrefly: ignore[bad-assignment]
"beta1": beta1, # pyrefly: ignore[bad-assignment]
"beta2": beta2, # pyrefly: ignore[bad-assignment]
"hue": onp.clip(onp.random.normal() * 0.03 + meta_params["hue"], 0, 1), # pyrefly: ignore[bad-assignment]
"contrast_high": contrast_high, # pyrefly: ignore[bad-assignment]
"contrast_low": contrast_low, # pyrefly: ignore[bad-assignment]
"saturation_high": saturation_high, # pyrefly: ignore[bad-assignment]
"saturation_low": saturation_low, # pyrefly: ignore[bad-assignment]
"smooth_labels": onp.clip( # pyrefly: ignore[bad-assignment]
onp.random.normal() * 0.03 + meta_params["smooth_labels"], 0, 1
),
"batch_size": int(
"batch_size": int( # pyrefly: ignore[bad-assignment]
meta_params["batch_size"] * (1 + onp.random.normal() * 0.1)
),
}
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