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https://github.com/NicolasBohn/NexQuant.git
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refactor: use dynamic input path and update template loader (#792)
* refactor: use dynamic input path and update template loader * fix: update include syntax for data source in prompts.yaml * add customization path * docs: update prompts for ensemble scoring and metric direction * chore: remove obsolete data_science/share.yaml file
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@@ -226,7 +226,11 @@ class DataLoaderCoSTEER(CoSTEER):
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new_exp = super().develop(exp)
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env = get_ds_env(
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extra_volumes={f"{DS_RD_SETTING.local_data_path}/{self.scen.competition}": "/kaggle/input"},
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extra_volumes={
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f"{DS_RD_SETTING.local_data_path}/{self.scen.competition}": T(
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"scenarios.data_science.share:scen.input_path"
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).r()
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},
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running_timeout_period=DS_RD_SETTING.full_timeout,
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)
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@@ -46,7 +46,11 @@ class DataLoaderCoSTEEREvaluator(CoSTEEREvaluator):
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)
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env = get_ds_env(
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extra_volumes={f"{DS_RD_SETTING.local_data_path}/sample/{self.scen.competition}": "/kaggle/input"}
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extra_volumes={
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f"{DS_RD_SETTING.local_data_path}/sample/{self.scen.competition}": T(
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"scenarios.data_science.share:scen.input_path"
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).r()
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}
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)
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# TODO: do we need to clean the generated temporary content?
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@@ -48,7 +48,7 @@ spec:
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- `test_ids` (DT): Identifiers for the test data.
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- Docstring Requirements:
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- Describe the purpose of the function.
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- Specify the data source location (`/kaggle/input/`).
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- Specify the data source location (`{% include "scenarios.data_science.share:scen.input_path" %}`).
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- Clearly define the structure and type of the output.
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- Inferred data shape to each input and output data variables. To uncertain dimension, use -1.
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2. Notes:
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@@ -268,7 +268,7 @@ data_loader_coder:
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{% endif %}
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## Guidelines
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1. Ensure that the dataset is loaded strictly from `/kaggle/input/`, following the exact folder structure described in the **Data Folder Description**, and do not attempt to load data from the current directory (`./`).
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1. Ensure that the dataset is loaded strictly from `{% include "scenarios.data_science.share:scen.input_path" %}`, following the exact folder structure described in the **Data Folder Description**, and do not attempt to load data from the current directory (`./`).
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2. You should avoid using logging module to output information in your generated code, and instead use the print() function.
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3. You should use the following cache decorator to cache the results of the function:
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```python
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