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import math |
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import pandas as pd |
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import gradio as gr |
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import datetime |
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import numpy as np |
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from dgl.data import YelpDataset |
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import dgl |
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import torch as th |
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from dgl.dataloading import LaborSampler, NeighborSampler |
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data = YelpDataset() |
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device = 'cpu' |
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g = data[0].to(device) |
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num_layers = 3 |
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fanouts = [10] * num_layers |
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samplers = [LaborSampler(fanouts, importance_sampling=1), LaborSampler(fanouts, importance_sampling=0), NeighborSampler(fanouts)] |
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names = ['LABOR-1', 'LABOR-0', 'NS'] |
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indices = th.arange(g.num_nodes()).to(device) |
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batch_size=1024 |
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loaders = [dgl.dataloading.DataLoader(g, indices, sampler, batch_size=batch_size, shuffle=True, drop_last=True) for sampler in samplers] |
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def get_time(): |
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return datetime.datetime.now() |
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plot_end = 2 * math.pi |
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def get_plot2(period=1): |
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global plot_end |
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x = np.arange(plot_end - 2 * math.pi, plot_end, 0.02) |
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y = np.sin(2 * math.pi * period * x) |
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update = gr.LinePlot.update( |
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value=pd.DataFrame({"x": x, "y": y}), |
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x="x", |
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y="y", |
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title="Plot (updates every second)", |
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width=600, |
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height=350, |
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) |
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plot_end += 2 * math.pi |
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if plot_end > 1000: |
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plot_end = 2 * math.pi |
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return update |
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results = [] |
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def get_plot(batch_size=1024): |
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for sampled in zip(*loaders): |
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results.append([s[0].shape for s in sampled]) |
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break |
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t = th.tensor(results) |
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x = "sampler" |
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y = "# vertices" |
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d = {x: [], y: []} |
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for i, name in enumerate(names): |
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yy = t[:, i] |
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d[y] += yy.tolist() |
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d[x] += [name] * yy.shape[0] |
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update = gr.BarPlot.update( |
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value=pd.DataFrame(d), |
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x=x, |
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y=y, |
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title="Number of sampled vertices", |
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width=600, |
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height=350 |
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) |
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return update |
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with gr.Blocks() as demo: |
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with gr.Row(): |
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with gr.Column(): |
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c_time2 = gr.Textbox(label="Current Time refreshed every second") |
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gr.Textbox( |
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"Change the value of the slider to automatically update the plot", |
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label="", |
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) |
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batch_size = gr.Number( |
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label="batch size", value=1024, show_label=True |
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) |
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plot = gr.BarPlot(show_label=False) |
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with gr.Column(): |
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name = gr.Textbox(label="Enter your name") |
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greeting = gr.Textbox(label="Greeting") |
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button = gr.Button(value="Greet") |
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button.click(lambda s: f"Hello {s}", name, greeting) |
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demo.load(lambda: datetime.datetime.now(), None, c_time2, every=10) |
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dep = demo.load(get_plot, None, plot, every=10) |
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batch_size.submit(get_plot, batch_size, plot, every=10, cancels=[dep]) |
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if __name__ == "__main__": |
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demo.queue().launch() |
