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Cleaner and more outputs during training initialization.
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@@ -107,7 +107,7 @@ namespace Eval::NNUE {
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<< " - " << LayerType::get_name()
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<< std::endl;
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out << "==> largest min activation = " << largest_min_activation
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out << " - largest min activation = " << largest_min_activation
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<< " , smallest max activation = " << smallest_max_activation
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<< std::endl;
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@@ -347,17 +347,17 @@ namespace Eval::NNUE {
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<< " - " << LayerType::get_name()
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<< std::endl;
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out << "==> observed " << observed_features.count()
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out << " - observed " << observed_features.count()
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<< " (out of " << kInputDimensions << ") features"
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<< std::endl;
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out << "==> (min, max) of pre-activations = "
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out << " - (min, max) of pre-activations = "
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<< min_pre_activation_ << ", "
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<< max_pre_activation_ << " (limit = "
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<< kPreActivationLimit << ")"
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<< std::endl;
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out << "==> largest min activation = " << largest_min_activation
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out << " - largest min activation = " << largest_min_activation
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<< " , smallest max activation = " << smallest_max_activation
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<< std::endl;
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