Refactor variable names
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c7959edff5
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@ -47,16 +47,16 @@ struct Stats {
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struct tensor_statistics {
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std::string tensor;
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Stats stats;
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float sum_values = 0.0f;
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float mean_values = 0.0f;
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float max_values = 0.0f;
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float min_values = 0.0f;
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int elements = 0;
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float stddev = 0.0f;
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float entropy = 0.0f;
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float zd_score = 0.0f;
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float cossim = 0.0f;
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float l2_norm = 0.0f;
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float sum_values = 0.0f;
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float mean_values = 0.0f;
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float max_values = 0.0f;
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float min_values = 0.0f;
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int elements = 0;
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float std_deviation = 0.0f;
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float entropy = 0.0f;
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float zd_score = 0.0f;
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float cossim = 0.0f;
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float l2_norm = 0.0f;
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};
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class IMatrixCollector {
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@ -227,10 +227,10 @@ static bool compute_vector_statistics(std::vector<tensor_statistics> & tstats, c
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}
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}
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int z_score = 0;
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int zd_score = 0;
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if (std_deviation > 0.0f) {
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for (const auto act : activations) {
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if (const float z = (act - mean) / std_deviation; std::fabs(z) > 1.0f) z_score++;
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if (const float z = (act - mean) / std_deviation; std::fabs(z) > 1.0f) zd_score++;
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}
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}
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@ -242,9 +242,9 @@ static bool compute_vector_statistics(std::vector<tensor_statistics> & tstats, c
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ts.max_values = max;
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ts.min_values = min;
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ts.elements = static_cast<int>(activations.size());
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ts.stddev = std_deviation;
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ts.std_deviation = std_deviation;
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ts.entropy = entropy;
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ts.zd_score = static_cast<float>(z_score) / ts.elements;
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ts.zd_score = static_cast<float>(zd_score) / ts.elements;
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return e.activations.empty();
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}
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@ -1334,7 +1334,7 @@ static bool show_statistics(const common_params & params) {
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tstat.min_values,
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tstat.max_values,
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tstat.mean_values,
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tstat.stddev,
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tstat.std_deviation,
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tstat.elements,
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tstat.entropy,
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100.0f * (tstat.entropy / std::log2(tstat.elements)),
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