Small changes
Browse files- app.py +29 -1
- src/display/css_html_js.py +1 -0
- src/display/utils.py +4 -15
app.py
CHANGED
@@ -11,7 +11,6 @@ from src.envs import API, EVAL_REQUESTS_PATH, EVAL_RESULTS_PATH, QUEUE_REPO, REP
|
|
11 |
from src.populate import get_evaluation_queue_df, get_leaderboard_df
|
12 |
from src.submission.submit import add_new_eval
|
13 |
|
14 |
-
|
15 |
# Define task metadata (icons, names, descriptions)
|
16 |
TASK_METADATA = {
|
17 |
"TE": {"icon": "π", "name": "Textual Entailment", "tooltip": ""},
|
@@ -30,6 +29,33 @@ def restart_space():
|
|
30 |
"""Restart the Hugging Face space."""
|
31 |
API.restart_space(repo_id=REPO_ID)
|
32 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
33 |
# Helper function for leaderboard initialization
|
34 |
def init_leaderboard(dataframe, default_selection=None, hidden_columns=None):
|
35 |
"""Initialize and return a leaderboard."""
|
@@ -53,6 +79,7 @@ def init_leaderboard(dataframe, default_selection=None, hidden_columns=None):
|
|
53 |
bool_checkboxgroup_label="Hide models",
|
54 |
interactive=False,
|
55 |
)
|
|
|
56 |
|
57 |
|
58 |
def download_snapshot(repo, local_dir):
|
@@ -80,6 +107,7 @@ with demo:
|
|
80 |
gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text")
|
81 |
|
82 |
with gr.Tabs(elem_classes="tab-buttons") as tabs:
|
|
|
83 |
# Main leaderboard tab
|
84 |
with gr.TabItem("π
EVALITA-LLM Benchmark"):
|
85 |
|
|
|
11 |
from src.populate import get_evaluation_queue_df, get_leaderboard_df
|
12 |
from src.submission.submit import add_new_eval
|
13 |
|
|
|
14 |
# Define task metadata (icons, names, descriptions)
|
15 |
TASK_METADATA = {
|
16 |
"TE": {"icon": "π", "name": "Textual Entailment", "tooltip": ""},
|
|
|
29 |
"""Restart the Hugging Face space."""
|
30 |
API.restart_space(repo_id=REPO_ID)
|
31 |
|
32 |
+
|
33 |
+
def init_leaderboard(dataframe, default_selection=None, hidden_columns=None):
|
34 |
+
"""Initialize and return a leaderboard."""
|
35 |
+
if dataframe is None or dataframe.empty:
|
36 |
+
raise ValueError("Leaderboard DataFrame is empty or None.")
|
37 |
+
|
38 |
+
field_list = fields(AutoEvalColumn)
|
39 |
+
|
40 |
+
return Leaderboard(
|
41 |
+
value=dataframe,
|
42 |
+
datatype=[c.type for c in field_list],
|
43 |
+
select_columns=SelectColumns(
|
44 |
+
default_selection=default_selection or [c.name for c in field_list if c.displayed_by_default],
|
45 |
+
cant_deselect=[c.name for c in field_list if c.never_hidden],
|
46 |
+
label="Select Columns to Display:",
|
47 |
+
),
|
48 |
+
search_columns=[AutoEvalColumn.model.name, AutoEvalColumn.license.name],
|
49 |
+
hide_columns=hidden_columns or [c.name for c in field_list if c.hidden],
|
50 |
+
filter_columns=[
|
51 |
+
ColumnFilter(AutoEvalColumn.fewshot_type.name, type="checkboxgroup", label="N-Few-Shot Learning (FS)"),
|
52 |
+
ColumnFilter(AutoEvalColumn.params.name, type="slider", min=0, max=150, label="Select the number of parameters (B)"),
|
53 |
+
],
|
54 |
+
bool_checkboxgroup_label="Hide models",
|
55 |
+
interactive=False,
|
56 |
+
)
|
57 |
+
|
58 |
+
'''
|
59 |
# Helper function for leaderboard initialization
|
60 |
def init_leaderboard(dataframe, default_selection=None, hidden_columns=None):
|
61 |
"""Initialize and return a leaderboard."""
|
|
|
79 |
bool_checkboxgroup_label="Hide models",
|
80 |
interactive=False,
|
81 |
)
|
82 |
+
'''
|
83 |
|
84 |
|
85 |
def download_snapshot(repo, local_dir):
|
|
|
107 |
gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text")
|
108 |
|
109 |
with gr.Tabs(elem_classes="tab-buttons") as tabs:
|
110 |
+
|
111 |
# Main leaderboard tab
|
112 |
with gr.TabItem("π
EVALITA-LLM Benchmark"):
|
113 |
|
src/display/css_html_js.py
CHANGED
@@ -94,6 +94,7 @@ custom_css = """
|
|
94 |
#box-filter > .form{
|
95 |
border: 0
|
96 |
}
|
|
|
97 |
"""
|
98 |
|
99 |
get_window_url_params = """
|
|
|
94 |
#box-filter > .form{
|
95 |
border: 0
|
96 |
}
|
97 |
+
|
98 |
"""
|
99 |
|
100 |
get_window_url_params = """
|
src/display/utils.py
CHANGED
@@ -89,8 +89,6 @@ class ModelType(Enum):
|
|
89 |
return ModelType.IFT
|
90 |
return ModelType.Unknown
|
91 |
|
92 |
-
|
93 |
-
|
94 |
@dataclass
|
95 |
class FewShotDetails:
|
96 |
name: str
|
@@ -113,10 +111,6 @@ class FewShotType(Enum):
|
|
113 |
return FewShotType.FS
|
114 |
return FewShotType.Unknown
|
115 |
|
116 |
-
|
117 |
-
|
118 |
-
|
119 |
-
|
120 |
class WeightType(Enum):
|
121 |
Adapter = ModelDetails("Adapter")
|
122 |
Original = ModelDetails("Original")
|
@@ -142,9 +136,7 @@ EVAL_TYPES = [c.type for c in fields(EvalQueueColumn)]
|
|
142 |
|
143 |
BENCHMARK_COLS = [t.value.col_name for t in Tasks]
|
144 |
|
145 |
-
|
146 |
-
# Roberto
|
147 |
-
|
148 |
# Nuovi valori per CPS, AVERAGE, BEST, e ID nella tabella
|
149 |
@dataclass
|
150 |
class NewColumnContent:
|
@@ -153,18 +145,15 @@ class NewColumnContent:
|
|
153 |
displayed_by_default: bool
|
154 |
hidden: bool = False
|
155 |
never_hidden: bool = False
|
|
|
156 |
|
157 |
-
|
158 |
new_column_dict = []
|
159 |
# Aggiungi CPS, VERAGE, BEST, ID
|
160 |
new_column_dict.append(["CPS", NewColumnContent, NewColumnContent("CPS", "number", True)])
|
161 |
new_column_dict.append(["AVERAGE", NewColumnContent, NewColumnContent("Average β¬οΈ", "number", True)])
|
162 |
new_column_dict.append(["BEST", NewColumnContent, NewColumnContent("Best Performance", "number", True)])
|
163 |
new_column_dict.append(["ID", NewColumnContent, NewColumnContent("ID", "str", True)])
|
164 |
-
|
165 |
-
# Puoi usare make_dataclass per creare la classe dinamicamente come per AutoEvalColumn
|
166 |
NewColumn = make_dataclass("NewColumn", new_column_dict, frozen=True)
|
167 |
-
|
168 |
-
# Includi questi nuovi valori nei COLS o in altre variabili di configurazione, se necessario
|
169 |
NEW_COLS = [c.name for c in fields(NewColumn) if not c.hidden]
|
170 |
-
|
|
|
89 |
return ModelType.IFT
|
90 |
return ModelType.Unknown
|
91 |
|
|
|
|
|
92 |
@dataclass
|
93 |
class FewShotDetails:
|
94 |
name: str
|
|
|
111 |
return FewShotType.FS
|
112 |
return FewShotType.Unknown
|
113 |
|
|
|
|
|
|
|
|
|
114 |
class WeightType(Enum):
|
115 |
Adapter = ModelDetails("Adapter")
|
116 |
Original = ModelDetails("Original")
|
|
|
136 |
|
137 |
BENCHMARK_COLS = [t.value.col_name for t in Tasks]
|
138 |
|
139 |
+
'''
|
|
|
|
|
140 |
# Nuovi valori per CPS, AVERAGE, BEST, e ID nella tabella
|
141 |
@dataclass
|
142 |
class NewColumnContent:
|
|
|
145 |
displayed_by_default: bool
|
146 |
hidden: bool = False
|
147 |
never_hidden: bool = False
|
148 |
+
'''
|
149 |
|
150 |
+
'''
|
151 |
new_column_dict = []
|
152 |
# Aggiungi CPS, VERAGE, BEST, ID
|
153 |
new_column_dict.append(["CPS", NewColumnContent, NewColumnContent("CPS", "number", True)])
|
154 |
new_column_dict.append(["AVERAGE", NewColumnContent, NewColumnContent("Average β¬οΈ", "number", True)])
|
155 |
new_column_dict.append(["BEST", NewColumnContent, NewColumnContent("Best Performance", "number", True)])
|
156 |
new_column_dict.append(["ID", NewColumnContent, NewColumnContent("ID", "str", True)])
|
|
|
|
|
157 |
NewColumn = make_dataclass("NewColumn", new_column_dict, frozen=True)
|
|
|
|
|
158 |
NEW_COLS = [c.name for c in fields(NewColumn) if not c.hidden]
|
159 |
+
'''
|