Delete WandB run saved (uploaded) files

Wandb_delete_file.ipynb

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  "cells": [
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      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "LNfsesgjK_jh"
      },
      "outputs": [],
      "source": [
        "!pip install -qU wandb"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import wandb\n",
        "wandb.login(relogin=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 69
        },
        "id": "nXvBX1OoLF6I",
        "outputId": "08f76d40-10ce-4300-97c4-f5f5afc26fef"
      },
      "execution_count": 1,
      "outputs": [
        {
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          "data": {
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            "application/javascript": [
              "\n",
              "        window._wandbApiKey = new Promise((resolve, reject) => {\n",
              "            function loadScript(url) {\n",
              "            return new Promise(function(resolve, reject) {\n",
              "                let newScript = document.createElement(\"script\");\n",
              "                newScript.onerror = reject;\n",
              "                newScript.onload = resolve;\n",
              "                document.body.appendChild(newScript);\n",
              "                newScript.src = url;\n",
              "            });\n",
              "            }\n",
              "            loadScript(\"https://cdn.jsdelivr.net/npm/postmate/build/postmate.min.js\").then(() => {\n",
              "            const iframe = document.createElement('iframe')\n",
              "            iframe.style.cssText = \"width:0;height:0;border:none\"\n",
              "            document.body.appendChild(iframe)\n",
              "            const handshake = new Postmate({\n",
              "                container: iframe,\n",
              "                url: 'https://wandb.ai/authorize'\n",
              "            });\n",
              "            const timeout = setTimeout(() => reject(\"Couldn't auto authenticate\"), 5000)\n",
              "            handshake.then(function(child) {\n",
              "                child.on('authorize', data => {\n",
              "                    clearTimeout(timeout)\n",
              "                    resolve(data)\n",
              "                });\n",
              "            });\n",
              "            })\n",
              "        });\n",
              "    "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\u001b[34m\u001b[1mwandb\u001b[0m: Appending key for api.wandb.ai to your netrc file: /root/.netrc\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "metadata": {},
          "execution_count": 1
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# !gdown 1FV5g1Tha_XNgqiXZNsGePQgsaEA7Q2bc\n",
        "!unzip -qq /content/Transfer_learning.zip"
      ],
      "metadata": {
        "id": "CqXN-yqgLIAw"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "run_id = \"ko4bopp5\"\n",
        "\n",
        "run = wandb.init(project=\"Classification_Oxford_flowers102\", id=run_id, resume=\"allow\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 104
        },
        "id": "jIrQx_2PLUDz",
        "outputId": "49778f89-3311-4161-84ca-e613bf9ae806"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Tracking run with wandb version 0.15.3"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Run data is saved locally in <code>/content/wandb/run-20230602_222419-ko4bopp5</code>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Resuming run <strong><a href='https://wandb.ai/opencv_courses/Classification_Oxford_flowers102/runs/ko4bopp5' target=\"_blank\">fresh-valley-2</a></strong> to <a href='https://wandb.ai/opencv_courses/Classification_Oxford_flowers102' target=\"_blank\">Weights & Biases</a> (<a href='https://wandb.me/run' target=\"_blank\">docs</a>)<br/>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              " View project at <a href='https://wandb.ai/opencv_courses/Classification_Oxford_flowers102' target=\"_blank\">https://wandb.ai/opencv_courses/Classification_Oxford_flowers102</a>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              " View run at <a href='https://wandb.ai/opencv_courses/Classification_Oxford_flowers102/runs/ko4bopp5' target=\"_blank\">https://wandb.ai/opencv_courses/Classification_Oxford_flowers102/runs/ko4bopp5</a>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "api = wandb.Api()\n",
        "\n",
        "old_run = api.run(rf\"opencv_courses/Classification_Oxford_flowers102/runs/{run_id}\")\n",
        "\n",
        "# for i in old_run.files():\n",
        "#     print(i.name)\n",
        "\n",
        "for file in old_run.files():\n",
        "    if \".tar\" in file.name:\n",
        "        print(file.name)\n",
        "        file.delete()    \n",
        "        print(\"File deleted successfully.\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "L_WjoNEVLr3b",
        "outputId": "933886b4-6013-4a24-8378-71bc006e6d99"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "model_checkpoint/version_2/ckpt.tar\n",
            "File deleted successfully.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "\n",
        "wandb.save(os.path.join(os.getcwd(), f\"{run_id}\", \"ckpt.tar\"))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FsNHv_hKL_Qx",
        "outputId": "3f28758f-df9e-403b-dbf1-d6fd293ca6a7"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['/content/wandb/run-20230602_222419-ko4bopp5/files/ckpt.tar']"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "run.finish()"
      ],
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          "height": 440,
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        },
        "id": "qn1uSz69MNok",
        "outputId": "9c7b705a-6934-4deb-d28c-fe9f6ff02a4e"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Waiting for W&B process to finish... <strong style=\"color:green\">(success).</strong>"
            ]
          },
          "metadata": {}
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        {
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          "data": {
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              "VBox(children=(Label(value='79.283 MB of 79.283 MB uploaded (0.000 MB deduped)\\r'), FloatProgress(value=1.0, m…"
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            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "bf51effd47094417a7c0bd5f48812091"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<style>\n",
              "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: left ; width: auto;} td:nth-child(2) {text-align: left ; width: 100%}\n",
              "    .wandb-row { display: flex; flex-direction: row; flex-wrap: wrap; justify-content: flex-start; width: 100% }\n",
              "    .wandb-col { display: flex; flex-direction: column; flex-basis: 100%; flex: 1; padding: 10px; }\n",
              "    </style>\n",
              "<div class=\"wandb-row\"><div class=\"wandb-col\"><h3>Run summary:</h3><br/><table class=\"wandb\"><tr><td>acc</td><td>0.91283</td></tr><tr><td>best_valid_acc</td><td>0.89314</td></tr><tr><td>best_valid_loss</td><td>1.40355</td></tr><tr><td>epoch</td><td>49</td></tr><tr><td>loss</td><td>1.55636</td></tr><tr><td>test_acc</td><td>0.88922</td></tr><tr><td>test_loss</td><td>1.3624</td></tr><tr><td>val_acc</td><td>0.89314</td></tr><tr><td>val_loss</td><td>1.41417</td></tr></table><br/></div></div>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              " View run <strong style=\"color:#cdcd00\">fresh-valley-2</strong> at: <a href='https://wandb.ai/opencv_courses/Classification_Oxford_flowers102/runs/ko4bopp5' target=\"_blank\">https://wandb.ai/opencv_courses/Classification_Oxford_flowers102/runs/ko4bopp5</a><br/>Synced 3 W&B file(s), 0 media file(s), 0 artifact file(s) and 1 other file(s)"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "Find logs at: <code>./wandb/run-20230602_222419-ko4bopp5/logs</code>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "-QVCwrYcNnDo"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}