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requirements.txt

@@ -1,2 +1,2 @@
-gradio-client @ git+https://github.com/gradio-app/gradio@88941b655e708ab14611341ed3fe57452fbbfc58#subdirectory=client/python
-https://gradio-pypi-previews.s3.amazonaws.com/88941b655e708ab14611341ed3fe57452fbbfc58/gradio-5.20.1-py3-none-any.whl
+gradio-client @ git+https://github.com/gradio-app/gradio@681254453a15dadde068feaec176bb984710292b#subdirectory=client/python
+https://gradio-pypi-previews.s3.amazonaws.com/681254453a15dadde068feaec176bb984710292b/gradio-5.20.1-py3-none-any.whl

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", "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, show_fullscreen_button=True),\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, show_fullscreen_button=True),\n", "    \"numpy\",\n", "    examples=[\n", "        [np.zeros((30, 30)).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

@@ -10,7 +10,7 @@ demo = gr.Interface(
     gr.Dataframe(type="numpy", datatype="number", row_count=5, col_count=3, show_fullscreen_button=True),
     "numpy",
     examples=[
-        [np.zeros((3, 3)).tolist()],
+        [np.zeros((30, 30)).tolist()],
         [np.ones((2, 2)).tolist()],
         [np.random.randint(0, 10, (3, 10)).tolist()],
         [np.random.randint(0, 10, (10, 3)).tolist()],