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Update app.py
Browse files
app.py
CHANGED
@@ -77,17 +77,15 @@ def generate_html_table_from_df(df):
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html += '<tr>'
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html += f'<td style="padding: 8px; width: {static_width}px;">{row["Model"]}</td>'
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html += f'<td style="padding: 8px;">{row["Provider"]}</td>'
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html += (
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f'<div style="background-color: {bar_color}; width: {bar_width:.1f}%; height: 10px;"></div></td>'
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)
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html += f'<td style="padding: 8px;">{row["Score"]}</td>'
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html += '</tr>'
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html += '</tbody></table>'
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return f'<div class="table-container">{html}</div>'
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def process_df(task, sort_order="Low to High", filter_fn=None):
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df = pd.read_csv(
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if df.columns[0].startswith("Unnamed:"):
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df = df.iloc[:, 1:]
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df['energy_score'] = df['energy_score'].astype(int)
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@@ -123,7 +121,7 @@ def generate_info_callout(ratio, scope_text):
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def get_global_callout():
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all_df = pd.DataFrame()
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for task in tasks:
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df = pd.read_csv(
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if df.columns[0].startswith("Unnamed:"):
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df = df.iloc[:, 1:]
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df['gpu_energy_numeric'] = pd.to_numeric(df['total_gpu_energy'], errors='raise') * 1000
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@@ -134,7 +132,7 @@ def get_global_callout():
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### ZIP DOWNLOAD FUNCTIONS ###
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def zip_csv_files():
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data_dir = "data
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zip_filename = "data.zip"
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with zipfile.ZipFile(zip_filename, "w", zipfile.ZIP_DEFLATED) as zipf:
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for filename in os.listdir(data_dir):
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@@ -241,7 +239,7 @@ def update_extractive_qa(sort_order):
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def update_all_tasks(sort_order):
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all_df = pd.DataFrame()
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for task in tasks:
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df = pd.read_csv(
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if df.columns[0].startswith("Unnamed:"):
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df = df.iloc[:, 1:]
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df['energy_score'] = df['energy_score'].astype(int)
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@@ -260,6 +258,18 @@ def update_all_tasks(sort_order):
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### BUILD THE GRADIO INTERFACE ###
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demo = gr.Blocks(css="""
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.gr-dataframe table {
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table-layout: fixed;
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@@ -279,8 +289,8 @@ demo = gr.Blocks(css="""
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""")
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with demo:
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#
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gr.HTML(f
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<div style="display: flex; justify-content: space-evenly; align-items: center; margin-bottom: 20px;">
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<a href="https://huggingface.co/spaces/AIEnergyScore/submission_portal" style="text-decoration: none; font-weight: bold; font-size: 1.1em; color: black; font-family: 'Inter', sans-serif;">Submission Portal</a>
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<a href="https://huggingface.co/spaces/AIEnergyScore/Label" style="text-decoration: none; font-weight: bold; font-size: 1.1em; color: black; font-family: 'Inter', sans-serif;">Label Generator</a>
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@@ -289,51 +299,14 @@ with demo:
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{get_zip_data_link()}
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<a href="https://huggingface.co/spaces/AIEnergyScore/README/discussions" style="text-decoration: none; font-weight: bold; font-size: 1.1em; color: black; font-family: 'Inter', sans-serif;">Community</a>
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</div>
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#
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alt="Logo"
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style="width:300px; max-width:300px; height:auto; display: inline-block;">
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<div style="position: absolute; top: 50%; left: calc(50% + 160px); transform: translateY(-50%);">
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<!-- Insert the global callout HTML here -->
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{global_callout_html}
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</div>
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</div>
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{% endraw %}
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{% raw %}
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<script>
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// The following script block is just a placeholder. In Gradio we will generate the full HTML in Python.
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</script>
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{% endraw %}
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{% endraw %}
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{% raw %}
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<script>
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</script>
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{% endraw %}
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{% raw %}
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{% endraw %}
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{# Compute the global callout HTML in Python #}
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{% python %}
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global_callout_html = get_global_callout()
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{% endpython %}
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{% raw %}
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<div style="position: relative; width: 100%; text-align: center; margin-bottom: 20px;">
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<img src="https://huggingface.co/spaces/AIEnergyScore/Leaderboard/resolve/main/logo.png"
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alt="Logo"
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style="width:300px; max-width:300px; height:auto; display: inline-block;">
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<div style="position: absolute; top: 50%; left: calc(50% + 160px); transform: translateY(-50%);">
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{global_callout_html}
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</div>
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</div>
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{% endraw %}
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<!-- --- Tabs for the different tasks --- -->
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with gr.Tabs():
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#
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with gr.TabItem("Text Generation π¬"):
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with gr.Row():
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with gr.Column(scale=4):
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@@ -342,17 +315,9 @@ global_callout_html = get_global_callout()
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"B (Single Cloud GPU) 20-66B parameters",
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"C (Multiple Cloud GPUs) >66B parameters"
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]
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model_class_dropdown = gr.Dropdown(
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choices=model_class_options,
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label="Select Model Class",
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value=model_class_options[0]
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)
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with gr.Column(scale=4):
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sort_dropdown_tg = gr.Dropdown(
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choices=["Low to High", "High to Low"],
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label="Sort",
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value="Low to High"
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)
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with gr.Column(scale=4):
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tg_callout = gr.HTML()
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tg_table = gr.HTML()
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@@ -362,15 +327,11 @@ global_callout_html = get_global_callout()
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model_class_dropdown.change(fn=update_text_generation, inputs=[model_class_dropdown, sort_dropdown_tg], outputs=[tg_callout, tg_table])
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sort_dropdown_tg.change(fn=update_text_generation, inputs=[model_class_dropdown, sort_dropdown_tg], outputs=[tg_callout, tg_table])
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#
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with gr.TabItem("Image Generation π·"):
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with gr.Row():
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with gr.Column(scale=8):
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sort_dropdown_img = gr.Dropdown(
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choices=["Low to High", "High to Low"],
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label="Sort",
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value="Low to High"
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)
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with gr.Column(scale=4):
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img_callout = gr.HTML()
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img_table = gr.HTML()
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@@ -379,15 +340,11 @@ global_callout_html = get_global_callout()
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img_table.value = init_table
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sort_dropdown_img.change(fn=update_image_generation, inputs=sort_dropdown_img, outputs=[img_callout, img_table])
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#
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with gr.TabItem("Text Classification π"):
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with gr.Row():
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with gr.Column(scale=8):
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sort_dropdown_tc = gr.Dropdown(
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choices=["Low to High", "High to Low"],
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label="Sort",
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value="Low to High"
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)
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with gr.Column(scale=4):
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tc_callout = gr.HTML()
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tc_table = gr.HTML()
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@@ -396,15 +353,11 @@ global_callout_html = get_global_callout()
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tc_table.value = init_table
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sort_dropdown_tc.change(fn=update_text_classification, inputs=sort_dropdown_tc, outputs=[tc_callout, tc_table])
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#
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with gr.TabItem("Image Classification πΌοΈ"):
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with gr.Row():
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with gr.Column(scale=8):
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sort_dropdown_ic = gr.Dropdown(
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choices=["Low to High", "High to Low"],
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label="Sort",
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value="Low to High"
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)
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with gr.Column(scale=4):
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ic_callout = gr.HTML()
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ic_table = gr.HTML()
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@@ -413,15 +366,11 @@ global_callout_html = get_global_callout()
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ic_table.value = init_table
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sort_dropdown_ic.change(fn=update_image_classification, inputs=sort_dropdown_ic, outputs=[ic_callout, ic_table])
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#
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with gr.TabItem("Image Captioning π"):
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with gr.Row():
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with gr.Column(scale=8):
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sort_dropdown_icap = gr.Dropdown(
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choices=["Low to High", "High to Low"],
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label="Sort",
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value="Low to High"
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)
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with gr.Column(scale=4):
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icap_callout = gr.HTML()
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icap_table = gr.HTML()
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icap_table.value = init_table
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sort_dropdown_icap.change(fn=update_image_captioning, inputs=sort_dropdown_icap, outputs=[icap_callout, icap_table])
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#
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with gr.TabItem("Summarization π"):
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with gr.Row():
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with gr.Column(scale=8):
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sort_dropdown_sum = gr.Dropdown(
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choices=["Low to High", "High to Low"],
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label="Sort",
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value="Low to High"
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)
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with gr.Column(scale=4):
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sum_callout = gr.HTML()
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sum_table = gr.HTML()
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sum_table.value = init_table
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sort_dropdown_sum.change(fn=update_summarization, inputs=sort_dropdown_sum, outputs=[sum_callout, sum_table])
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#
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with gr.TabItem("Automatic Speech Recognition π¬"):
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with gr.Row():
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with gr.Column(scale=8):
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sort_dropdown_asr = gr.Dropdown(
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choices=["Low to High", "High to Low"],
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label="Sort",
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value="Low to High"
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)
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with gr.Column(scale=4):
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asr_callout = gr.HTML()
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asr_table = gr.HTML()
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asr_table.value = init_table
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sort_dropdown_asr.change(fn=update_asr, inputs=sort_dropdown_asr, outputs=[asr_callout, asr_table])
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#
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with gr.TabItem("Object Detection π"):
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with gr.Row():
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with gr.Column(scale=8):
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sort_dropdown_od = gr.Dropdown(
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choices=["Low to High", "High to Low"],
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label="Sort",
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value="Low to High"
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)
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with gr.Column(scale=4):
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od_callout = gr.HTML()
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od_table = gr.HTML()
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od_table.value = init_table
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sort_dropdown_od.change(fn=update_object_detection, inputs=sort_dropdown_od, outputs=[od_callout, od_table])
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#
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with gr.TabItem("Sentence Similarity π"):
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with gr.Row():
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with gr.Column(scale=8):
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sort_dropdown_ss = gr.Dropdown(
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choices=["Low to High", "High to Low"],
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label="Sort",
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value="Low to High"
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)
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with gr.Column(scale=4):
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ss_callout = gr.HTML()
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ss_table = gr.HTML()
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ss_table.value = init_table
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sort_dropdown_ss.change(fn=update_sentence_similarity, inputs=sort_dropdown_ss, outputs=[ss_callout, ss_table])
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#
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with gr.TabItem("Extractive QA β"):
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with gr.Row():
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with gr.Column(scale=8):
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sort_dropdown_qa = gr.Dropdown(
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choices=["Low to High", "High to Low"],
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label="Sort",
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value="Low to High"
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)
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with gr.Column(scale=4):
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qa_callout = gr.HTML()
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qa_table = gr.HTML()
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qa_table.value = init_table
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sort_dropdown_qa.change(fn=update_extractive_qa, inputs=sort_dropdown_qa, outputs=[qa_callout, qa_table])
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#
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with gr.TabItem("All Tasks π‘"):
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with gr.Row():
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with gr.Column(scale=8):
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sort_dropdown_all = gr.Dropdown(
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choices=["Low to High", "High to Low"],
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label="Sort",
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value="Low to High"
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)
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with gr.Column(scale=4):
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all_callout = gr.HTML()
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all_table = gr.HTML()
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)
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gr.Markdown("Last updated: February 2025")
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demo.launch()
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html += '<tr>'
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html += f'<td style="padding: 8px; width: {static_width}px;">{row["Model"]}</td>'
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html += f'<td style="padding: 8px;">{row["Provider"]}</td>'
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html += (f'<td style="padding: 8px;">{energy_str}<br>'
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f'<div style="background-color: {bar_color}; width: {bar_width:.1f}%; height: 10px;"></div></td>')
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html += f'<td style="padding: 8px;">{row["Score"]}</td>'
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html += '</tr>'
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html += '</tbody></table>'
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return f'<div class="table-container">{html}</div>'
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def process_df(task, sort_order="Low to High", filter_fn=None):
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df = pd.read_csv(os.path.join("data", "energy", task))
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if df.columns[0].startswith("Unnamed:"):
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df = df.iloc[:, 1:]
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df['energy_score'] = df['energy_score'].astype(int)
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def get_global_callout():
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all_df = pd.DataFrame()
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for task in tasks:
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df = pd.read_csv(os.path.join("data", "energy", task))
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if df.columns[0].startswith("Unnamed:"):
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df = df.iloc[:, 1:]
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df['gpu_energy_numeric'] = pd.to_numeric(df['total_gpu_energy'], errors='raise') * 1000
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### ZIP DOWNLOAD FUNCTIONS ###
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def zip_csv_files():
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data_dir = os.path.join("data", "energy")
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zip_filename = "data.zip"
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with zipfile.ZipFile(zip_filename, "w", zipfile.ZIP_DEFLATED) as zipf:
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for filename in os.listdir(data_dir):
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def update_all_tasks(sort_order):
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all_df = pd.DataFrame()
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for task in tasks:
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df = pd.read_csv(os.path.join("data", "energy", task))
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if df.columns[0].startswith("Unnamed:"):
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df = df.iloc[:, 1:]
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df['energy_score'] = df['energy_score'].astype(int)
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### BUILD THE GRADIO INTERFACE ###
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# Compute the global header HTML using the global callout.
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global_header_html = f"""
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<div style="position: relative; width: 100%; text-align: center; margin-bottom: 20px;">
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<img src="https://huggingface.co/spaces/AIEnergyScore/Leaderboard/resolve/main/logo.png"
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alt="Logo"
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style="width:300px; max-width:300px; height:auto; display: inline-block;">
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<div style="position: absolute; top: 50%; left: calc(50% + 160px); transform: translateY(-50%);">
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{get_global_callout()}
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</div>
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</div>
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"""
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demo = gr.Blocks(css="""
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.gr-dataframe table {
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table-layout: fixed;
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""")
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with demo:
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# Header Links
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gr.HTML(f"""
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<div style="display: flex; justify-content: space-evenly; align-items: center; margin-bottom: 20px;">
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<a href="https://huggingface.co/spaces/AIEnergyScore/submission_portal" style="text-decoration: none; font-weight: bold; font-size: 1.1em; color: black; font-family: 'Inter', sans-serif;">Submission Portal</a>
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<a href="https://huggingface.co/spaces/AIEnergyScore/Label" style="text-decoration: none; font-weight: bold; font-size: 1.1em; color: black; font-family: 'Inter', sans-serif;">Label Generator</a>
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{get_zip_data_link()}
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<a href="https://huggingface.co/spaces/AIEnergyScore/README/discussions" style="text-decoration: none; font-weight: bold; font-size: 1.1em; color: black; font-family: 'Inter', sans-serif;">Community</a>
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</div>
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""")
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# Global Header: Centered Logo with Global Callout
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gr.HTML(global_header_html)
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# Tabs for different tasks
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with gr.Tabs():
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# Text Generation Tab
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with gr.TabItem("Text Generation π¬"):
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with gr.Row():
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with gr.Column(scale=4):
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"B (Single Cloud GPU) 20-66B parameters",
|
316 |
"C (Multiple Cloud GPUs) >66B parameters"
|
317 |
]
|
318 |
+
model_class_dropdown = gr.Dropdown(choices=model_class_options, label="Select Model Class", value=model_class_options[0])
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|
319 |
with gr.Column(scale=4):
|
320 |
+
sort_dropdown_tg = gr.Dropdown(choices=["Low to High", "High to Low"], label="Sort", value="Low to High")
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|
321 |
with gr.Column(scale=4):
|
322 |
tg_callout = gr.HTML()
|
323 |
tg_table = gr.HTML()
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|
327 |
model_class_dropdown.change(fn=update_text_generation, inputs=[model_class_dropdown, sort_dropdown_tg], outputs=[tg_callout, tg_table])
|
328 |
sort_dropdown_tg.change(fn=update_text_generation, inputs=[model_class_dropdown, sort_dropdown_tg], outputs=[tg_callout, tg_table])
|
329 |
|
330 |
+
# Image Generation Tab
|
331 |
with gr.TabItem("Image Generation π·"):
|
332 |
with gr.Row():
|
333 |
with gr.Column(scale=8):
|
334 |
+
sort_dropdown_img = gr.Dropdown(choices=["Low to High", "High to Low"], label="Sort", value="Low to High")
|
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|
335 |
with gr.Column(scale=4):
|
336 |
img_callout = gr.HTML()
|
337 |
img_table = gr.HTML()
|
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|
340 |
img_table.value = init_table
|
341 |
sort_dropdown_img.change(fn=update_image_generation, inputs=sort_dropdown_img, outputs=[img_callout, img_table])
|
342 |
|
343 |
+
# Text Classification Tab
|
344 |
with gr.TabItem("Text Classification π"):
|
345 |
with gr.Row():
|
346 |
with gr.Column(scale=8):
|
347 |
+
sort_dropdown_tc = gr.Dropdown(choices=["Low to High", "High to Low"], label="Sort", value="Low to High")
|
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|
348 |
with gr.Column(scale=4):
|
349 |
tc_callout = gr.HTML()
|
350 |
tc_table = gr.HTML()
|
|
|
353 |
tc_table.value = init_table
|
354 |
sort_dropdown_tc.change(fn=update_text_classification, inputs=sort_dropdown_tc, outputs=[tc_callout, tc_table])
|
355 |
|
356 |
+
# Image Classification Tab
|
357 |
with gr.TabItem("Image Classification πΌοΈ"):
|
358 |
with gr.Row():
|
359 |
with gr.Column(scale=8):
|
360 |
+
sort_dropdown_ic = gr.Dropdown(choices=["Low to High", "High to Low"], label="Sort", value="Low to High")
|
|
|
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|
|
|
|
|
361 |
with gr.Column(scale=4):
|
362 |
ic_callout = gr.HTML()
|
363 |
ic_table = gr.HTML()
|
|
|
366 |
ic_table.value = init_table
|
367 |
sort_dropdown_ic.change(fn=update_image_classification, inputs=sort_dropdown_ic, outputs=[ic_callout, ic_table])
|
368 |
|
369 |
+
# Image Captioning Tab
|
370 |
with gr.TabItem("Image Captioning π"):
|
371 |
with gr.Row():
|
372 |
with gr.Column(scale=8):
|
373 |
+
sort_dropdown_icap = gr.Dropdown(choices=["Low to High", "High to Low"], label="Sort", value="Low to High")
|
|
|
|
|
|
|
|
|
374 |
with gr.Column(scale=4):
|
375 |
icap_callout = gr.HTML()
|
376 |
icap_table = gr.HTML()
|
|
|
379 |
icap_table.value = init_table
|
380 |
sort_dropdown_icap.change(fn=update_image_captioning, inputs=sort_dropdown_icap, outputs=[icap_callout, icap_table])
|
381 |
|
382 |
+
# Summarization Tab
|
383 |
with gr.TabItem("Summarization π"):
|
384 |
with gr.Row():
|
385 |
with gr.Column(scale=8):
|
386 |
+
sort_dropdown_sum = gr.Dropdown(choices=["Low to High", "High to Low"], label="Sort", value="Low to High")
|
|
|
|
|
|
|
|
|
387 |
with gr.Column(scale=4):
|
388 |
sum_callout = gr.HTML()
|
389 |
sum_table = gr.HTML()
|
|
|
392 |
sum_table.value = init_table
|
393 |
sort_dropdown_sum.change(fn=update_summarization, inputs=sort_dropdown_sum, outputs=[sum_callout, sum_table])
|
394 |
|
395 |
+
# Automatic Speech Recognition Tab
|
396 |
with gr.TabItem("Automatic Speech Recognition π¬"):
|
397 |
with gr.Row():
|
398 |
with gr.Column(scale=8):
|
399 |
+
sort_dropdown_asr = gr.Dropdown(choices=["Low to High", "High to Low"], label="Sort", value="Low to High")
|
|
|
|
|
|
|
|
|
400 |
with gr.Column(scale=4):
|
401 |
asr_callout = gr.HTML()
|
402 |
asr_table = gr.HTML()
|
|
|
405 |
asr_table.value = init_table
|
406 |
sort_dropdown_asr.change(fn=update_asr, inputs=sort_dropdown_asr, outputs=[asr_callout, asr_table])
|
407 |
|
408 |
+
# Object Detection Tab
|
409 |
with gr.TabItem("Object Detection π"):
|
410 |
with gr.Row():
|
411 |
with gr.Column(scale=8):
|
412 |
+
sort_dropdown_od = gr.Dropdown(choices=["Low to High", "High to Low"], label="Sort", value="Low to High")
|
|
|
|
|
|
|
|
|
413 |
with gr.Column(scale=4):
|
414 |
od_callout = gr.HTML()
|
415 |
od_table = gr.HTML()
|
|
|
418 |
od_table.value = init_table
|
419 |
sort_dropdown_od.change(fn=update_object_detection, inputs=sort_dropdown_od, outputs=[od_callout, od_table])
|
420 |
|
421 |
+
# Sentence Similarity Tab
|
422 |
with gr.TabItem("Sentence Similarity π"):
|
423 |
with gr.Row():
|
424 |
with gr.Column(scale=8):
|
425 |
+
sort_dropdown_ss = gr.Dropdown(choices=["Low to High", "High to Low"], label="Sort", value="Low to High")
|
|
|
|
|
|
|
|
|
426 |
with gr.Column(scale=4):
|
427 |
ss_callout = gr.HTML()
|
428 |
ss_table = gr.HTML()
|
|
|
431 |
ss_table.value = init_table
|
432 |
sort_dropdown_ss.change(fn=update_sentence_similarity, inputs=sort_dropdown_ss, outputs=[ss_callout, ss_table])
|
433 |
|
434 |
+
# Extractive QA Tab
|
435 |
with gr.TabItem("Extractive QA β"):
|
436 |
with gr.Row():
|
437 |
with gr.Column(scale=8):
|
438 |
+
sort_dropdown_qa = gr.Dropdown(choices=["Low to High", "High to Low"], label="Sort", value="Low to High")
|
|
|
|
|
|
|
|
|
439 |
with gr.Column(scale=4):
|
440 |
qa_callout = gr.HTML()
|
441 |
qa_table = gr.HTML()
|
|
|
444 |
qa_table.value = init_table
|
445 |
sort_dropdown_qa.change(fn=update_extractive_qa, inputs=sort_dropdown_qa, outputs=[qa_callout, qa_table])
|
446 |
|
447 |
+
# All Tasks Tab
|
448 |
with gr.TabItem("All Tasks π‘"):
|
449 |
with gr.Row():
|
450 |
with gr.Column(scale=8):
|
451 |
+
sort_dropdown_all = gr.Dropdown(choices=["Low to High", "High to Low"], label="Sort", value="Low to High")
|
|
|
|
|
|
|
|
|
452 |
with gr.Column(scale=4):
|
453 |
all_callout = gr.HTML()
|
454 |
all_table = gr.HTML()
|
|
|
467 |
)
|
468 |
gr.Markdown("Last updated: February 2025")
|
469 |
|
470 |
+
demo.launch()
|