{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import env" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "31\n", "5\n", "3\n" ] } ], "source": [] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "包含None!\n", "[123 None]\n" ] } ], "source": [ "import numpy as np\n", "\n", "def qa(aa = None):\n", " try:\n", " isaanone = aa.any() == None\n", " if aa.all() == None:\n", " print(\"包含None!\")\n", " except:\n", " isaanone =True\n", " if isaanone:\n", " print('none')\n", " else:\n", " print(aa)\n", "\n", "qa(np.array([123,None]))" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[[[1 1 1 1 1]\n", " [1 2 1 1 1]]\n", "\n", " [[2 1 3 4 5]\n", " [2 2 3 4 5]]\n", "\n", " [[3 1 3 4 5]\n", " [3 2 3 4 5]]]\n", "-\n", "tf.Tensor(\n", "[[1 1 1 1 1]\n", " [2 1 3 4 5]\n", " [3 1 3 4 5]], shape=(3, 5), dtype=int32)\n", "-\n", "tf.Tensor(\n", "[[1 2 1 1 1]\n", " [2 2 3 4 5]\n", " [3 2 3 4 5]], shape=(3, 5), dtype=int32)\n" ] } ], "source": [ "import numpy as np\n", "import tensorflow as tf\n", "\n", "aa = np.array([[[1,1,1,1,1],[1,2,1,1,1],[1,3,1,1,1]],\n", " [[2,1,3,4,5],[2,2,3,4,5],[2,3,3,4,5]],\n", " [[3,1,3,4,5],[3,2,3,4,5],[3,3,3,4,5]]])\n", "tt = tf.constant(aa)\n", "bb = np.array([6,3,6,3,2,3])\n", "\n", "print(aa[:,0:2])\n", "aa[:,2:]\n", "\n", "for asd in tf.transpose(aa[:,0:2],perm=[1,0,2]):\n", " print('-')\n", " print(asd)" ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import tensorflow as tf\n", "aa = tf.constant(0)\n", "bb = aa+1\n", "bb\n" ] } ], "metadata": { "interpreter": { "hash": "86e2db13b09bd6be22cb599ea60c1572b9ef36ebeaa27a4c8e961d6df315ac32" }, "kernelspec": { "display_name": "Python 3.9.7 64-bit", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.7" }, "orig_nbformat": 4 }, "nbformat": 4, "nbformat_minor": 2 }