hysts HF staff commited on
Commit
a0b4c37
·
1 Parent(s): fe7e796
Files changed (1) hide show
  1. app.py +0 -29
app.py CHANGED
@@ -58,7 +58,6 @@ def restart_space() -> None:
58
 
59
  # Space initialization
60
  try:
61
- print(EVAL_REQUESTS_PATH)
62
  snapshot_download(
63
  repo_id=QUEUE_REPO,
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  local_dir=EVAL_REQUESTS_PATH,
@@ -96,17 +95,12 @@ def filter_models(
96
  version_query: list[str],
97
  vllm_query: list[str],
98
  ) -> pd.DataFrame:
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- print(f"Initial df shape: {df.shape}")
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- print(f"Initial df content:\n{df}")
101
-
102
  # Filter by model type
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  type_emoji = [t.split()[0] for t in type_query]
104
  df = df[df["T"].isin(type_emoji)]
105
- print(f"After type filter: {df.shape}")
106
 
107
  # Filter by precision
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  df = df[df["Precision"].isin(precision_query)]
109
- print(f"After precision filter: {df.shape}")
110
 
111
  # Filter by model size
112
  # Note: When `df` is empty, `size_mask` is empty, and the shape of `df[size_mask]` becomes (0, 0),
@@ -118,26 +112,19 @@ def filter_models(
118
  if "Unknown" in size_query:
119
  size_mask |= df["#Params (B)"].isna() | (df["#Params (B)"] == 0)
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  df = df[size_mask]
121
- print(f"After size filter: {df.shape}")
122
 
123
  # Filter by special tokens setting
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  df = df[df["Add Special Tokens"].isin(add_special_tokens_query)]
125
- print(f"After add_special_tokens filter: {df.shape}")
126
 
127
  # Filter by number of few-shot examples
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  df = df[df["Few-shot"].astype(str).isin(num_few_shots_query)]
129
- print(f"After num_few_shots filter: {df.shape}")
130
 
131
  # Filter by evaluator version
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  df = df[df["llm-jp-eval version"].isin(version_query)]
133
- print(f"After version filter: {df.shape}")
134
 
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  # Filter by vLLM version
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  df = df[df["vllm version"].isin(vllm_query)]
137
- print(f"After vllm version filter: {df.shape}")
138
 
139
- print("Filtered dataframe head:")
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- print(df.head())
141
  return df
142
 
143
 
@@ -190,10 +177,6 @@ def update_table(
190
  *columns,
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  ) -> pd.DataFrame:
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  columns = [item for column in columns for item in column]
193
- print(
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- f"Update table called with: type_query={type_query}, precision_query={precision_query}, size_query={size_query}"
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- )
196
-
197
  filtered_df = filter_models(
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  ORIGINAL_DF,
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  type_query,
@@ -204,21 +187,9 @@ def update_table(
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  version_query,
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  vllm_query,
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  )
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- print(f"filtered_df shape after filter_models: {filtered_df.shape}")
208
-
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  filtered_df = search_models_by_multiple_names(filtered_df, query)
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- print(f"filtered_df shape after search_models_by_multiple_names: {filtered_df.shape}")
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-
212
- print(
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- f"Filter applied: query={query}, columns={columns}, type_query={type_query}, precision_query={precision_query}"
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- )
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- print("Filtered dataframe head:")
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- print(filtered_df.head())
217
 
218
  df = select_columns(filtered_df, columns)
219
- print(f"Final df shape: {df.shape}")
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- print("Final dataframe head:")
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- print(df.head())
222
  return df
223
 
224
 
 
58
 
59
  # Space initialization
60
  try:
 
61
  snapshot_download(
62
  repo_id=QUEUE_REPO,
63
  local_dir=EVAL_REQUESTS_PATH,
 
95
  version_query: list[str],
96
  vllm_query: list[str],
97
  ) -> pd.DataFrame:
 
 
 
98
  # Filter by model type
99
  type_emoji = [t.split()[0] for t in type_query]
100
  df = df[df["T"].isin(type_emoji)]
 
101
 
102
  # Filter by precision
103
  df = df[df["Precision"].isin(precision_query)]
 
104
 
105
  # Filter by model size
106
  # Note: When `df` is empty, `size_mask` is empty, and the shape of `df[size_mask]` becomes (0, 0),
 
112
  if "Unknown" in size_query:
113
  size_mask |= df["#Params (B)"].isna() | (df["#Params (B)"] == 0)
114
  df = df[size_mask]
 
115
 
116
  # Filter by special tokens setting
117
  df = df[df["Add Special Tokens"].isin(add_special_tokens_query)]
 
118
 
119
  # Filter by number of few-shot examples
120
  df = df[df["Few-shot"].astype(str).isin(num_few_shots_query)]
 
121
 
122
  # Filter by evaluator version
123
  df = df[df["llm-jp-eval version"].isin(version_query)]
 
124
 
125
  # Filter by vLLM version
126
  df = df[df["vllm version"].isin(vllm_query)]
 
127
 
 
 
128
  return df
129
 
130
 
 
177
  *columns,
178
  ) -> pd.DataFrame:
179
  columns = [item for column in columns for item in column]
 
 
 
 
180
  filtered_df = filter_models(
181
  ORIGINAL_DF,
182
  type_query,
 
187
  version_query,
188
  vllm_query,
189
  )
 
 
190
  filtered_df = search_models_by_multiple_names(filtered_df, query)
 
 
 
 
 
 
 
191
 
192
  df = select_columns(filtered_df, columns)
 
 
 
193
  return df
194
 
195