sayakpaul HF Staff commited on
Commit
b2ee710
·
verified ·
1 Parent(s): 84a87f1

Update app.py

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Files changed (1) hide show
  1. app.py +8 -3
app.py CHANGED
@@ -14,6 +14,11 @@ model_choices = sorted(df['model_cls'].dropna().unique().tolist())
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  metric_choices = ["num_params_B", "flops_G", "time_plain_s", "mem_plain_GB", "time_compile_s", "mem_compile_GB"]
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  group_choices = ["scenario"]
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  # Analysis function using global df
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  def analyze(analysis_type, n_rows, metric, selected_model):
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  columns = df.columns
@@ -37,7 +42,7 @@ def analyze(analysis_type, n_rows, metric, selected_model):
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  # prepare bars
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  scenarios = plot_df['scenario']
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- values = plot_df[metric]
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  bars = ax.barh(scenarios, values)
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  # prettify
@@ -71,8 +76,8 @@ def analyze(analysis_type, n_rows, metric, selected_model):
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  return None, fig
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  scenarios = filt['scenario']
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- plain = filt['time_plain_s']
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- compile = filt['time_compile_s']
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  x = range(len(scenarios))
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  width = 0.35
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  metric_choices = ["num_params_B", "flops_G", "time_plain_s", "mem_plain_GB", "time_compile_s", "mem_compile_GB"]
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  group_choices = ["scenario"]
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+ def filter_float(value):
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+ if isinstance(value, str):
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+ return float(value.split()[0])
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+ return value
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+
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  # Analysis function using global df
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  def analyze(analysis_type, n_rows, metric, selected_model):
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  columns = df.columns
 
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  # prepare bars
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  scenarios = plot_df['scenario']
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+ values = plot_df[metric].map(filter_float)
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  bars = ax.barh(scenarios, values)
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  # prettify
 
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  return None, fig
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  scenarios = filt['scenario']
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+ plain = filt['time_plain_s'].map(filter_float)
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+ compile = filt['time_compile_s'].map(filter_float)
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  x = range(len(scenarios))
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  width = 0.35
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