Use radio
Browse files
app.py
CHANGED
@@ -140,12 +140,13 @@ BENCHMARK_DATA = {
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}
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-
def get_plot(model_name, generate_type):
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df = pd.DataFrame(BENCHMARK_DATA[generate_type][model_name])
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df["framework"] = ["PyTorch", "TF (Eager Execition)", "TF (XLA)"]
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df = pd.melt(df, id_vars=["framework"], value_vars=["T4", "3090", "A100"])
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-
# fig = plt.figure(figsize=(100, 6), dpi=200)
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g = sns.catplot(
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data=df, kind="bar",
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x="variable", y="value", hue="framework",
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@@ -171,9 +172,9 @@ with demo:
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with gr.TabItem("Greedy Search"):
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gr.Markdown(
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"""
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### Greedy Search parameters
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- `max_new_tokens = 64`;
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-
- `
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"""
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)
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with gr.Row():
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@@ -183,10 +184,15 @@ with demo:
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label="Model",
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interactive=True,
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)
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-
eager_enabler = gr.Radio(
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plot_fn = functools.partial(get_plot, generate_type="Greedy Search")
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plot = gr.Plot(value=plot_fn("T5 Small")) # Show plot when the gradio app is initialized
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model_selector.change(fn=plot_fn, inputs=model_selector, outputs=plot)
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with gr.TabItem("Sample"):
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gr.Button("New Tiger")
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with gr.TabItem("Beam Search"):
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}
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+
def get_plot(model_name, plot_eager, generate_type):
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df = pd.DataFrame(BENCHMARK_DATA[generate_type][model_name])
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df["framework"] = ["PyTorch", "TF (Eager Execition)", "TF (XLA)"]
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df = pd.melt(df, id_vars=["framework"], value_vars=["T4", "3090", "A100"])
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if plot_eager == "No":
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df = df[df["framework"] != "TF (Eager Execition)"]
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g = sns.catplot(
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data=df, kind="bar",
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x="variable", y="value", hue="framework",
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with gr.TabItem("Greedy Search"):
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gr.Markdown(
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"""
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+
### Greedy Search benchmark parameters
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- `max_new_tokens = 64`;
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- `pad_to_multiple_of = 64` for Tensorflow XLA models. Others do not pad (input prompts between 2 and 33 tokens).
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"""
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)
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with gr.Row():
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label="Model",
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interactive=True,
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)
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eager_enabler = gr.Radio(
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["Yes", "No"],
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value="Yes",
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label="Plot TF Eager Execution?",
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interactive=True
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)
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plot_fn = functools.partial(get_plot, generate_type="Greedy Search")
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plot = gr.Plot(value=plot_fn("T5 Small")) # Show plot when the gradio app is initialized
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model_selector.change(fn=plot_fn, inputs=[model_selector, eager_enabler], outputs=plot)
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with gr.TabItem("Sample"):
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gr.Button("New Tiger")
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with gr.TabItem("Beam Search"):
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