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run.ipynb

@@ -1 +1 @@
-{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: slider_release"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "\n", "\n", "def identity(x, state):\n", "    state += 1\n", "    return x, state, state\n", "\n", "\n", "with gr.Blocks() as demo:\n", "    slider = gr.Slider(0, 100, step=0.1)\n", "    state = gr.State(value=0)\n", "    with gr.Row():\n", "        number = gr.Number(label=\"On release\")\n", "        number2 = gr.Number(label=\"Number of events fired\")\n", "    slider.release(identity, inputs=[slider, state], outputs=[number, state, number2], api_name=\"predict\")\n", "\n", "if __name__ == \"__main__\":\n", "    print(\"here\")\n", "    demo.launch()\n", "    print(demo.server_port)\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
+{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: slider_release"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "\n", "def identity(x, state):\n", "    state += 1\n", "    return x, state, state\n", "\n", "with gr.Blocks() as demo:\n", "    slider = gr.Slider(0, 100, step=0.1)\n", "    state = gr.State(value=0)\n", "    with gr.Row():\n", "        number = gr.Number(label=\"On release\")\n", "        number2 = gr.Number(label=\"Number of events fired\")\n", "    slider.release(identity, inputs=[slider, state], outputs=[number, state, number2], api_name=\"predict\")\n", "\n", "if __name__ == \"__main__\":\n", "    print(\"here\")\n", "    demo.launch()\n", "    print(demo.server_port)\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

run.py

@@ -1,11 +1,9 @@
 import gradio as gr
 
-
 def identity(x, state):
     state += 1
     return x, state, state
 
-
 with gr.Blocks() as demo:
     slider = gr.Slider(0, 100, step=0.1)
     state = gr.State(value=0)