{ "cells": [ { "cell_type": "code", "execution_count": null, "id": "d6930748", "metadata": { "id": "d6930748" }, "outputs": [], "source": [ "import pandas as pd\n", "books = pd.read_csv('books_with_categories.csv', encoding='utf-8')" ] }, { "cell_type": "code", "execution_count": null, "id": "d6ff324f", "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 536, "referenced_widgets": [ "61e648fe33614b03a86be583ee35ca33", "e905accca6b046b6b44a44d011a6f064", "8893394b48f942f2a073ed99d38426a1", "357a5f0af6bd489284e0045bad659537", "cb43c40d992a45398d391ec306b8af19", "1208c8a3be0948d9a42dc11daee0f47c", "32e2054cb4ac481d9c91cf5aaa0ec06a", "0633b2d79c4742f190e1341ad7a146b1", "6ca08a81babf4284a0e04360cda08725", "bc010ee6245e4c5584a63c7709af4839", "75167bb727c34cab8319de241d368547", "194aae11d83f4f97b009bafc435cb62d", "d3cd8004d32b4909a5ee995b1bfa5988", "bead9a403b934559a1ffe5854ab9fca4", "89a280535a994db2a83fb5429694ff68", "23e8aac376d9472fa18fd52448841269", 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"e0d0a2fbbd094d9eb6a2d4d4d50c8292", "b429037fa947464a9c507d4c07c5eb7f", "e07d5dda39454431bea3edf4858149f1", "b4125224150f4987962339e43b4ac3a3", "330bcc66a09b4c639ccfc59a7210c3d4", "e4daeb803c234ea2b8f64c75ecef3142", "f97d0861b41d46a1acec2d55192653a7", "40ff14ee97844d7aaafb355162d70a2a", "cde502fd09de4c2cbe4a13efe30bf1cf", "b0d6ef88fd434155839098b7975157f1", "975d683e9bc44d8b9ffd726cd20f3a3d", "b2ef2e7b518c48458c62be93cb9716d2", "d7999f94db1b483ba74b5f2d47ed9d0a", "a851170c9f7d401eb5bb1f5e987f97c1", "70bde43e74dc4964b1660d9276bb0d2c", "b21574af60534e61b569db8469cae96c", "e1729343a2324fe5a82e13c8b982bd48", "2bb28be893af4e37ab8e78343eb03188", "11be452e60e44be38a36d3a9b9495963", "c1a3caa7ce0840bfb2ba6cd8f8140fb9", "0c09dd02f2b44488aed2534ff70dc418", "4b782f34fee441d7a6cf1b6b1236d355", "09d1b05fdc7a456695a6b4b0f67b7be2", "dd086159781043faafac18d707191845", "5ba049dae16749f69cbb0b2142a75038", "3708f36e529f4d4ba95a14328a60a7c5", "90fabe9e64594f5d9cdc416da589c8a7", "2345f0edf49840e1a3532523f14b1e98", "d59085244e9740d58a91cab22607800d", "09f2160355b246d08dc2cc347aff6ae9", "29b0d752d0354ab7bf66f587d08999ec", "319ae6364b6e417e960336412f14b18d", "7c04042fe41947a5ba01a7eaea35978c", "eb087af24ff241ca839e166256dc52bb", "492cb21eb46e4ea4b12c25f0bf2e62dc", "aece7214a8d14b0f975ef6eef815ab55", "87d84d8d479848379ca421ac77a84d98", "92a7f01b3f84467fb7a0942ab32aeb8a", "fe28621bc0854a1aa36ccb93b209ff8d", "2e4bc789778246fd9bc6dc2a0851a2c5", "7368587fdb1f432d88de68c16ee84351", "dc4c3835d7434c749133f9ba0eaa9e4a", "ec782d60ffb84bcdbbdb1615bcbc6b16", "1b87f98b6845483ab5c096e25d691b42", "3da205828cb5403499af80149d32b87b" ] }, "id": "d6ff324f", "outputId": "5c6a5f64-9e68-411e-b679-a52431bfa124" }, "outputs": [], "source": [ "from transformers import pipeline\n", "\n", "classifier = pipeline(\"text-classification\",\n", " model=\"j-hartmann/emotion-english-distilroberta-base\",\n", " top_k=None,\n", " device=\"cuda\")\n", "\n", "classifier(\"I love this\")" ] }, { "cell_type": "code", "execution_count": null, "id": "e063829b", "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "e063829b", "outputId": "61215d23-504d-40f8-968f-b89e23d0f5ef" }, "outputs": [], "source": [ "classifier(books['description'][0])" ] }, { "cell_type": "code", "execution_count": null, "id": "9ec78c4c", "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "9ec78c4c", "outputId": "51788cb9-b0d5-4a30-a788-1a2f888887f5" }, "outputs": [], "source": [ "classifier(books['description'][0].split('.'))" ] }, { "cell_type": "code", "execution_count": null, "id": "ef09fe63", "metadata": { "id": "ef09fe63" }, "outputs": [], "source": [ "sentences = books['description'][0].split('.')" ] }, { "cell_type": "code", "execution_count": null, "id": "c7c29fc8", "metadata": { "id": "c7c29fc8" }, "outputs": [], "source": [ "prediction = classifier(sentences)" ] }, { "cell_type": "code", "execution_count": null, "id": "e178c538", "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "e178c538", "outputId": "552aebde-9df7-4d79-8eab-afc363fea074" }, "outputs": [], "source": [ "sorted(prediction[0], key=lambda x: x['label'])" ] }, { "cell_type": "code", "execution_count": null, "id": "e843a9f0", "metadata": { "id": "e843a9f0" }, "outputs": [], "source": [ "import numpy as np\n", "\n", "emotion_labels = [\"anger\", \"disgust\", \"fear\", \"joy\", \"sadness\", \"surprise\", \"neutral\"]\n", "isbn = []\n", "emotion_scores = {label: [] for label in emotion_labels}\n", "\n", "def calculate_max_emotion_scores(predictions):\n", " per_emotion_scores = {label: [] for label in emotion_labels}\n", " for prediction in predictions:\n", " sorted_predictions = sorted(prediction, key=lambda x: x[\"label\"])\n", " for index, label in enumerate(emotion_labels):\n", " per_emotion_scores[label].append(sorted_predictions[index][\"score\"])\n", " return {label: np.max(scores) for label, scores in per_emotion_scores.items()}\n" ] }, { "cell_type": "code", "execution_count": null, "id": "_OTMVwCWwmmr", "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "_OTMVwCWwmmr", "outputId": "6371de0f-1e0c-4392-a245-19cda792eb2c" }, "outputs": [], "source": [ "from tqdm import tqdm\n", "emotion_labels = [\"anger\", \"disgust\", \"fear\", \"joy\", \"sadness\", \"surprise\", \"neutral\"]\n", "isbn = []\n", "emotion_scores = {label: [] for label in emotion_labels}\n", "for i in tqdm(range(len(books))):\n", " isbn.append(books['isbn13'][i])\n", " sentences = books['description'][i].split('.')\n", " prediction = classifier(sentences)\n", " max_emotion_scores = calculate_max_emotion_scores(prediction)\n", " for label in emotion_labels:\n", " emotion_scores[label].append(max_emotion_scores[label])" ] }, { "cell_type": "code", "execution_count": null, "id": "c3a0932c", "metadata": { "id": "c3a0932c" }, "outputs": [], "source": [ "emotions_df = pd.DataFrame(emotion_scores)\n", "emotions_df['isbn13'] = isbn" ] }, { "cell_type": "code", "execution_count": null, "id": "0-sYKl8Mx9XA", "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 206 }, "id": "0-sYKl8Mx9XA", "outputId": "9f341c50-729d-43b8-8322-5a2f7ce1202f" }, "outputs": [], "source": [ "emotions_df.head()" ] }, { "cell_type": "code", "execution_count": null, "id": "uxYqpMAex9Ze", "metadata": { "id": "uxYqpMAex9Ze" }, "outputs": [], "source": [ "books = pd.merge(books, emotions_df, on='isbn13')" ] }, { "cell_type": "code", "execution_count": null, "id": "jqq2Fl00x9cL", "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 620 }, "id": "jqq2Fl00x9cL", "outputId": "5685e191-6700-4e15-f803-f21d26c30262" }, "outputs": [], "source": [ "books.head()" ] }, { "cell_type": "code", "execution_count": null, "id": "pND892LNx9el", "metadata": { "id": "pND892LNx9el" }, "outputs": [], "source": [ "books.to_csv(\"books_with_emotions.csv\", index = False)" ] } ], "metadata": { "accelerator": "GPU", "colab": { 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