|  | @@ -225,6 +225,8 @@ def predict_ad_group_video_mix_with_add(dt, config_key, config_param, threshold_
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				|  |  |          abtest_id, abtest_config_tag = abtest_config_list[0], abtest_config_list[1]
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				|  |  |          for key, val in threshold_data.items():
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				|  |  |              key_name = f"{config_.KEY_NAME_PREFIX_AD_THRESHOLD}{abtest_id}:{abtest_config_tag}:{abtest_group}:{key}"
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				|  |  | +            if abtest_id == 243 and (abtest_group == "ab0" or abtest_group == "ab1" or abtest_group == "ab2"):
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				|  |  | +                val=0.6983435337929007
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				|  |  |              redis_helper.set_data_to_redis(key_name=key_name, value=val, expire_time=2 * 24 * 3600)
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				|  |  |  
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				|  |  |          # 计算关怀模式实验阈值 并 写入Redis
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				|  | @@ -235,6 +237,8 @@ def predict_ad_group_video_mix_with_add(dt, config_key, config_param, threshold_
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				|  |  |              for key, val in threshold_data.items():
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				|  |  |                  up_val = val * threshold_rate
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				|  |  |                  care_model_threshold_data[key] = up_val
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				|  |  | +                if abtest_id == 243 and (abtest_group == "ab0" or abtest_group == "ab1" or abtest_group == "ab2"):
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				|  |  | +                    val = 0.6983435337929007
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				|  |  |                  up_key_name = \
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				|  |  |                      f"{config_.KEY_NAME_PREFIX_AD_THRESHOLD_CARE_MODEL}{abtest_id}:{abtest_config_tag}:{abtest_group}:{key}"
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				|  |  |                  redis_helper.set_data_to_redis(key_name=up_key_name, value=up_val, expire_time=2 * 24 * 3600)
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