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run.ipynb

@@ -1 +1 @@
-{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: matrix_transpose"]}, {"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 numpy as np\n", "\n", "import gradio as gr\n", "\n", "\n", "def transpose(matrix):\n", "    return matrix.T\n", "\n", "\n", "demo = gr.Interface(\n", "    transpose,\n", "    gr.Dataframe(type=\"numpy\", datatype=\"number\", row_count=5, col_count=3),\n", "    \"numpy\",\n", "    examples=[\n", "        [np.zeros((3, 3)).tolist()],\n", "        [np.ones((2, 2)).tolist()],\n", "        [np.random.randint(0, 10, (3, 10)).tolist()],\n", "        [np.random.randint(0, 10, (10, 3)).tolist()],\n", "        [np.random.randint(0, 10, (10, 10)).tolist()],\n", "    ],\n", "    cache_examples=False\n", ")\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
+{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: matrix_transpose"]}, {"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 numpy as np\n", "\n", "import gradio as gr\n", "\n", "def transpose(matrix):\n", "    return matrix.T\n", "\n", "demo = gr.Interface(\n", "    transpose,\n", "    gr.Dataframe(type=\"numpy\", datatype=\"number\", row_count=5, col_count=3),\n", "    \"numpy\",\n", "    examples=[\n", "        [np.zeros((3, 3)).tolist()],\n", "        [np.ones((2, 2)).tolist()],\n", "        [np.random.randint(0, 10, (3, 10)).tolist()],\n", "        [np.random.randint(0, 10, (10, 3)).tolist()],\n", "        [np.random.randint(0, 10, (10, 10)).tolist()],\n", "    ],\n", "    cache_examples=False\n", ")\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

run.py

@@ -2,11 +2,9 @@ import numpy as np
 
 import gradio as gr
 
-
 def transpose(matrix):
     return matrix.T
 
-
 demo = gr.Interface(
     transpose,
     gr.Dataframe(type="numpy", datatype="number", row_count=5, col_count=3),