From d37575a69f3c66c8b7449b31de03e3a1e99d8668 Mon Sep 17 00:00:00 2001 From: Guy Giesbrecht Date: Fri, 18 Oct 2024 13:56:51 -0700 Subject: [PATCH] A very basic notebook for using Janus with Google colab. 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100% (31/31), done.\u001b[K\n", + "remote: Total 35 (delta 4), reused 35 (delta 4), pack-reused 0 (from 0)\u001b[K\n", + "Receiving objects: 100% (35/35), 955.66 KiB | 6.73 MiB/s, done.\n", + "Resolving deltas: 100% (4/4), done.\n" + ] + } + ], + "source": [ + "!git clone https://github.com/deepseek-ai/Janus.git\n" + ] + }, + { + "cell_type": "code", + "source": [ + "%cd Janus\n", + "!pip install -e .\n", + "!pip install flash-attn" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "BIeDQ1ClXwL_", + "outputId": "556e62de-2bac-4eec-9008-78f33515c790" + }, + "execution_count": 2, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "/content/Janus\n", + "Obtaining file:///content/Janus\n", + " Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n", + " Checking if build backend supports build_editable ... \u001b[?25l\u001b[?25hdone\n", + " Getting requirements to build editable ... \u001b[?25l\u001b[?25hdone\n", + " 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for flash-attn: filename=flash_attn-2.6.3-cp310-cp310-linux_x86_64.whl size=187309225 sha256=237ef9c6157db394e1ddde4ba609a21ebb98382377a27041edc09318801a6f24\n", + " Stored in directory: /root/.cache/pip/wheels/7e/e3/c3/89c7a2f3c4adc07cd1c675f8bb7b9ad4d18f64a72bccdfe826\n", + "Successfully built flash-attn\n", + "Installing collected packages: flash-attn\n", + "Successfully installed flash-attn-2.6.3\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "\n", + "import torch\n", + "from transformers import AutoModelForCausalLM\n", + "from janus.models import MultiModalityCausalLM, VLChatProcessor\n", + "from janus.utils.io import load_pil_images\n", + "\n", + "# specify the path to the model\n", + "model_path = \"deepseek-ai/Janus-1.3B\"\n", + "vl_chat_processor: VLChatProcessor = VLChatProcessor.from_pretrained(model_path)\n", + "tokenizer = vl_chat_processor.tokenizer\n", + "\n", + "vl_gpt: MultiModalityCausalLM = AutoModelForCausalLM.from_pretrained(\n", + " model_path, trust_remote_code=True\n", + ")\n", + "vl_gpt = vl_gpt.to(torch.bfloat16).cuda().eval()\n", + "\n", + "conversation = [\n", + " {\n", + " \"role\": \"User\",\n", + " \"content\": \"\\nConvert the formula into latex code.\",\n", + " \"images\": [\"images/equation.png\"],\n", + " },\n", + " {\"role\": \"Assistant\", \"content\": \"\"},\n", + "]\n", + "\n", + "# load images and prepare for inputs\n", + "pil_images = load_pil_images(conversation)\n", + "prepare_inputs = vl_chat_processor(\n", + " conversations=conversation, images=pil_images, force_batchify=True\n", + ").to(vl_gpt.device)\n", + "\n", + "# # run image encoder to get the image embeddings\n", + "inputs_embeds = vl_gpt.prepare_inputs_embeds(**prepare_inputs)\n", + "\n", + "# # run the model to get the response\n", + "outputs = vl_gpt.language_model.generate(\n", + " inputs_embeds=inputs_embeds,\n", + " attention_mask=prepare_inputs.attention_mask,\n", + " pad_token_id=tokenizer.eos_token_id,\n", + " bos_token_id=tokenizer.bos_token_id,\n", + " eos_token_id=tokenizer.eos_token_id,\n", + " max_new_tokens=512,\n", + " do_sample=False,\n", + " use_cache=True,\n", + ")\n", + "\n", + "answer = tokenizer.decode(outputs[0].cpu().tolist(), skip_special_tokens=True)\n", + "print(f\"{prepare_inputs['sft_format'][0]}\", answer)\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 547, + "referenced_widgets": [ + "763db730135046ad82de98efeff17d43", + "4f86e96fadab4c0d99817e7e586773c8", + "3d5d9b536d5547f088c5b38998b86f4b", + "e749a276bffb4136a4ca518867fcefdc", + "26d64ffbb4ae49dca04faf3a4e2e55ca", + "e4c1880a3a4048da9fb06fc699d6f130", + "c7b3782ef893473199e9140ec6208edc", + "f95595cb4b6a4f1d829cf9fd7f27e0d3", + "14a1ff29167d48a7a16cf4d848861178", + "51cb411fef0c4be4bdd47a93be2f1cf5", + "f0bace68043e4b1c92a1e3dc4b6192b7", + "e5de18967479416bacedefaeee42e0f7", + "f7bcc5523c57490aa4300fc8720e32b3", + "eef53bb650af41729306ad9d9194706e", + 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"d46166ae17a14324b0315650d231fabf", + "a0209d882c9e41a39fb4c5086dfc32fe", + "a98fe1626e154c8bb284695b262449c3", + "8abd03a7756c4b9eb19952b33072663f", + "6d8030e748004e05ba5e6ade8e444521", + "e5e1110b5ea4441c84641c6ea8889bc3", + "213741a787f342b9b41848e65597fc6a", + "fefab3bf50c84c5c83a61e7733c39e27", + "3ec2079aea414a0b85ca58a0529111b9", + "0d91dbd78efa4ca2bc5c8bfc7b6b3007", + "9d4624220b1b48b99417316a072c122a" + ] + }, + "id": "X7B6TWTvXxRu", + "outputId": "072387f9-6404-48f1-bcbb-f1acddf1c77f" + }, + "execution_count": 3, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Python version is above 3.10, patching the collections module.\n" + ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "/usr/local/lib/python3.10/dist-packages/transformers/models/auto/image_processing_auto.py:513: FutureWarning: The image_processor_class argument is deprecated and will be removed in v4.42. Please use `slow_image_processor_class`, or `fast_image_processor_class` instead\n", + " warnings.warn(\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "preprocessor_config.json: 0%| | 0.00/347 [00:00. This is expected, and simply means that the `legacy` (previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, set `legacy=False`. This should only be set if you understand what it means, and thoroughly read the reason why this was added as explained in https://github.com/huggingface/transformers/pull/24565 - if you loaded a llama tokenizer from a GGUF file you can ignore this message.\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "processor_config.json: 0%| | 0.00/210 [00:00 to the tokenizer\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "config.json: 0%| | 0.00/1.45k [00:00\n", + "Convert the formula into latex code.\n", + "\n", + "Assistant: Sure, here is the LaTeX code for the formula:\n", + "\n", + "\\[ A_n = a_0 \\left[ 1 + \\frac{3}{4} \\sum_{k=1}^{n} \\left( \\frac{4}{9} \\right)^k \\right] \\]\n" + ] + } + ] + } + ] +} \ No newline at end of file