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fix: sparse weights iterator end->end (#4647)
* fix: sparse weights iterator end->end * fix sparse not_null and allow more bits for sparse * validate warning * lint * use fmt * clang * use warning interface * Update settings.json * use str
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Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,22 @@ | ||
using no cache | ||
Reading datafile = train-sets/cb_test.ldf | ||
num sources = 1 | ||
Num weight bits = 18 | ||
learning rate = 0.5 | ||
initial_t = 3 | ||
power_t = 0.5 | ||
cb_type = mtr | ||
Enabled learners: gd, scorer-identity, csoaa_ldf-rank, cb_adf, cb_explore_adf_greedy, shared_feature_merger | ||
Input label = CB | ||
Output pred = ACTION_PROBS | ||
average since example example current current current | ||
loss last counter weight label predict features | ||
0.066667 0.066667 1 1.0 0:1:0.5 1:0.48 15 | ||
0.033333 0.000000 2 2.0 1:0:0.5 1:0.95 6 | ||
|
||
finished run | ||
number of examples = 3 | ||
weighted example sum = 3.000000 | ||
weighted label sum = 0.000000 | ||
average loss = 0.033333 | ||
total feature number = 27 |
Empty file.
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Original file line number | Diff line number | Diff line change |
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@@ -0,0 +1,23 @@ | ||
final_regressor = standard_sparse_model.vw | ||
using no cache | ||
Reading datafile = train-sets/cb_test.ldf | ||
num sources = 1 | ||
Num weight bits = 18 | ||
learning rate = 0.5 | ||
initial_t = 0 | ||
power_t = 0.5 | ||
cb_type = mtr | ||
Enabled learners: gd, scorer-identity, csoaa_ldf-rank, cb_adf, cb_explore_adf_greedy, shared_feature_merger | ||
Input label = CB | ||
Output pred = ACTION_PROBS | ||
average since example example current current current | ||
loss last counter weight label predict features | ||
0.666667 0.666667 1 1.0 0:1:0.5 0:0.33 15 | ||
0.333333 0.000000 2 2.0 1:0:0.5 1:0.95 6 | ||
|
||
finished run | ||
number of examples = 3 | ||
weighted example sum = 3.000000 | ||
weighted label sum = 0.000000 | ||
average loss = 0.333333 | ||
total feature number = 27 |
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