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This behaviour is the source of the following dependency conflicts.\n", - "cudf-cu12 24.4.1 requires pyarrow<15.0.0a0,>=14.0.1, but you have pyarrow 17.0.0 which is incompatible.\n", - "gcsfs 2024.6.1 requires fsspec==2024.6.1, but you have fsspec 2024.5.0 which is incompatible.\n", - "ibis-framework 8.0.0 requires pyarrow<16,>=2, but you have pyarrow 17.0.0 which is incompatible.\u001b[0m\u001b[31m\n", - "\u001b[0m" - ] - } - ], - "source": [ - "!pip install git+https://github.com/simplifine-llm/Simplifine.git -q\n", - "!pip install datasets -q" - ] - }, - { - "cell_type": "code", - "source": [ - "from simplifine_alpha import train_engine\n", - "from trl import SFTConfig\n", - "\n", - "dataset_name = 'community-datasets/fake_news_english'\n", - "\n", - "# defining prompt config\n", - "sft_prompt_config = train_engine.sftPromptConfig(\n", - " keys = ['url_of_article', 'fake_or_satire'],\n", - " template = \"###URL: {url_of_article}. \\n###CLS: {fake_or_satire}\",\n", - " response_template = '. \\n###CLS: ',\n", - " use_chat_template=True\n", - " )\n", - "\n", - "# defining training config\n", - "sft_config = SFTConfig(\n", - " output_dir='/content/fake_news_english_phi3',\n", - " per_device_train_batch_size=1,\n", - " gradient_accumulation_steps=4,\n", - " learning_rate=1e-5,\n", - " num_train_epochs=2,\n", - " report_to='none',\n", - " fp16=True,\n", - " gradient_checkpointing=True,\n", - ")\n", - "\n", - "model_name = 'TinyLlama/TinyLlama-1.1B-Chat-v1.0'\n", - "\n", - "# this is just for demo purposes, this will take a while here, no quantization, no lora...\n", - "train_engine.sft_train(model_name=model_name, dataset_name=dataset_name,\n", - " sft_config = sft_config, sft_prompt_config=sft_prompt_config,\n", - " use_zero=False, use_ddp=False\n", - " )" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 1000, - "referenced_widgets": [ - "85b43ab19cda4f72a77fdfd5dc096496", - "121146c229204799b4d6c7defb3d6474", - "05fba94d8a2c4e1c9beda729c24511cf", - "b34a0424b9c54f20adfcf36fd31c20ec", - 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If you have GPU or other accelerator, we were unable to detect it.\n", - "[2024-08-06 17:41:44,222] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cpu (auto detect)\n" - ] - }, - { - "output_type": "stream", - "name": "stderr", - "text": [ - "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:89: UserWarning: \n", - "The secret `HF_TOKEN` does not exist in your Colab secrets.\n", - "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n", - "You will be able to reuse this secret in all of your notebooks.\n", - "Please note that authentication is recommended but still optional to access public models or datasets.\n", - " warnings.warn(\n" - ] - }, - { - "output_type": "display_data", - "data": { - "text/plain": [ - "tokenizer_config.json: 0%| | 0.00/1.29k [00:00\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 26\u001b[0m \u001b[0mmodel_name\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'TinyLlama/TinyLlama-1.1B-Chat-v1.0'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 27\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 28\u001b[0;31m train_engine.sft_train(model_name=model_name, dataset_name=dataset_name,\n\u001b[0m\u001b[1;32m 29\u001b[0m \u001b[0msft_config\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msft_config\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msft_prompt_config\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msft_prompt_config\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 30\u001b[0m \u001b[0muse_zero\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0muse_ddp\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - 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"\u001b[0;32m/usr/local/lib/python3.10/dist-packages/accelerate/accelerator.py\u001b[0m in \u001b[0;36mbackward\u001b[0;34m(self, loss, **kwargs)\u001b[0m\n\u001b[1;32m 2149\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlomo_backward\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mloss\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlearning_rate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2150\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2151\u001b[0;31m \u001b[0mloss\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbackward\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2152\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2153\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mset_trigger\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/torch/_tensor.py\u001b[0m in \u001b[0;36mbackward\u001b[0;34m(self, gradient, retain_graph, create_graph, inputs)\u001b[0m\n\u001b[1;32m 523\u001b[0m \u001b[0minputs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0minputs\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 524\u001b[0m )\n\u001b[0;32m--> 525\u001b[0;31m torch.autograd.backward(\n\u001b[0m\u001b[1;32m 526\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgradient\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mretain_graph\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcreate_graph\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minputs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0minputs\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 527\u001b[0m )\n", - "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/torch/autograd/__init__.py\u001b[0m in \u001b[0;36mbackward\u001b[0;34m(tensors, grad_tensors, retain_graph, create_graph, grad_variables, inputs)\u001b[0m\n\u001b[1;32m 265\u001b[0m \u001b[0;31m# some Python versions print out the first line of a multi-line function\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 266\u001b[0m \u001b[0;31m# calls in the traceback and some print out the last line\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 267\u001b[0;31m _engine_run_backward(\n\u001b[0m\u001b[1;32m 268\u001b[0m \u001b[0mtensors\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 269\u001b[0m \u001b[0mgrad_tensors_\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/torch/autograd/graph.py\u001b[0m in \u001b[0;36m_engine_run_backward\u001b[0;34m(t_outputs, *args, **kwargs)\u001b[0m\n\u001b[1;32m 742\u001b[0m \u001b[0munregister_hooks\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_register_logging_hooks_on_whole_graph\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mt_outputs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 743\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 744\u001b[0;31m return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass\n\u001b[0m\u001b[1;32m 745\u001b[0m \u001b[0mt_outputs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 746\u001b[0m ) # Calls into the C++ engine to run the backward pass\n", - "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/torch/autograd/function.py\u001b[0m in \u001b[0;36mapply\u001b[0;34m(self, *args)\u001b[0m\n\u001b[1;32m 299\u001b[0m )\n\u001b[1;32m 300\u001b[0m \u001b[0muser_fn\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mvjp_fn\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mvjp_fn\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mFunction\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvjp\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0mbackward_fn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 301\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0muser_fn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 302\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 303\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mapply_jvp\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/torch/utils/checkpoint.py\u001b[0m in \u001b[0;36mbackward\u001b[0;34m(ctx, *args)\u001b[0m\n\u001b[1;32m 318\u001b[0m \u001b[0;34m\" this checkpoint() is not necessary\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 319\u001b[0m )\n\u001b[0;32m--> 320\u001b[0;31m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mautograd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbackward\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0moutputs_with_grad\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0margs_with_grad\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 321\u001b[0m grads = tuple(\n\u001b[1;32m 322\u001b[0m \u001b[0minp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgrad\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minp\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTensor\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/torch/autograd/__init__.py\u001b[0m in \u001b[0;36mbackward\u001b[0;34m(tensors, grad_tensors, retain_graph, create_graph, grad_variables, inputs)\u001b[0m\n\u001b[1;32m 265\u001b[0m \u001b[0;31m# some Python versions print out the first line of a multi-line function\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 266\u001b[0m \u001b[0;31m# calls in the traceback and some print out the last line\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 267\u001b[0;31m _engine_run_backward(\n\u001b[0m\u001b[1;32m 268\u001b[0m \u001b[0mtensors\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 269\u001b[0m \u001b[0mgrad_tensors_\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/torch/autograd/graph.py\u001b[0m in \u001b[0;36m_engine_run_backward\u001b[0;34m(t_outputs, *args, **kwargs)\u001b[0m\n\u001b[1;32m 742\u001b[0m \u001b[0munregister_hooks\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_register_logging_hooks_on_whole_graph\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mt_outputs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 743\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 744\u001b[0;31m return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass\n\u001b[0m\u001b[1;32m 745\u001b[0m \u001b[0mt_outputs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 746\u001b[0m ) # Calls into the C++ engine to run the backward pass\n", - "\u001b[0;31mKeyboardInterrupt\u001b[0m: " - ] - } - ] - }, - { - "cell_type": "code", - "source": [ - "from simplifine_alpha import train_utils\n", - "\n", - "# change name to phi 3\n", - "model_name = 'microsoft/Phi-3-mini-4k-instruct'\n", - "simplifine_api_key = ''\n", - "gpu_type = 'a100'\n", - "client = train_utils.Client(simplifine_api_key, gpu_type)\n", - "\n", - "job_name = 'fake_news_english_phi3'\n", - "\n", - "\n", - "client.sft_train_cloud(job_name=job_name, model_name=model_name, dataset_name=dataset_name,\n", - " sft_config = sft_config, sft_prompt_config=sft_prompt_config,\n", - " use_zero=True, use_ddp=False\n", - " )" - ], - "metadata": { - "id": "O1zdn8r85n-o", - "colab": { - "base_uri": "https://localhost:8080/" - }, - "outputId": "d2510f4d-5246-4631-df37-8a741cf92240" - }, - "execution_count": 2, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "[2024-08-07 18:34:35,105] [WARNING] [real_accelerator.py:162:get_accelerator] Setting accelerator to CPU. If you have GPU or other accelerator, we were unable to detect it.\n", - "[2024-08-07 18:34:35,110] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cpu (auto detect)\n" - ] - } - ] - }, - { - "cell_type": "markdown", - "source": [ - "You can check the status of your job. The status can be any of the following:\n", - "\n", - "\n", - "```\n", - "pending | in progress | stopped | completed\n", - "```\n", - "\n" - ], - "metadata": { - "id": "W88J_Ef7yaYG" - } - }, - { - "cell_type": "code", - "source": [ - "status = client.get_all_jobs()\n", - "for num,i in enumerate(status[-1:]):\n", - " print(f'Job {num}: {i}')" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "l70vZyPV6_AC", - "outputId": "b32db3fe-e353-4105-e8b7-63a772d7ccde" - }, - "execution_count": 3, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "Job 0: {'job_id': '183c65ad-2b4e-4d11-b2a5-d66232d5b15b', 'job_name': 'fake_news_english_phi3', 'status': 'completed'}\n" - ] - } - ] - }, - { - "cell_type": "markdown", - "source": [ - "To see how things are going, you can take a look at the logs, to see if there were any errors or what not." - ], - "metadata": { - "id": "BDe93gbayl_n" - } - }, - { - "cell_type": "code", - "source": [ - "# getting the job_id of the last job\n", - "job_id = status[-1]['job_id']\n", - "\n", - "logs = client.get_train_logs(job_id)\n", - "print(logs['response'])" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "jt35FPNn8ADK", - "outputId": "1de668ed-718e-452d-eb85-0632d7652008" - }, - "execution_count": 4, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "W0806 18:14:41.510000 129132731527296 torch/distributed/run.py:779] \n", - "W0806 18:14:41.510000 129132731527296 torch/distributed/run.py:779] *****************************************\n", - "W0806 18:14:41.510000 129132731527296 torch/distributed/run.py:779] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. \n", - "W0806 18:14:41.510000 129132731527296 torch/distributed/run.py:779] *****************************************\n", - "[2024-08-06 18:14:46,878] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect)\n", - "[2024-08-06 18:14:46,910] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect)\n", - "\u001b[93m [WARNING] \u001b[0m async_io requires the dev libaio .so object and headers but these were not found.\n", - "[2024-08-06 18:14:46,961] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect)\n", - "\u001b[93m [WARNING] \u001b[0m async_io: please install the libaio-dev package with apt\n", - "\u001b[93m [WARNING] \u001b[0m If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found.\n", - "\u001b[93m [WARNING] \u001b[0m Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH\n", - "\u001b[93m [WARNING] \u001b[0m async_io requires the dev libaio .so object and headers but these were not found.\n", - "\u001b[93m [WARNING] \u001b[0m async_io: please install the libaio-dev package with apt\n", - "\u001b[93m [WARNING] \u001b[0m If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found.\n", - "\u001b[93m [WARNING] \u001b[0m Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH\n", - "\u001b[93m [WARNING] \u001b[0m async_io requires the dev libaio .so object and headers but these were not found.\n", - "\u001b[93m [WARNING] \u001b[0m async_io: please install the libaio-dev package with apt\n", - "\u001b[93m [WARNING] \u001b[0m If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found.\n", - "\u001b[93m [WARNING] \u001b[0m Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH\n", - "\u001b[93m [WARNING] \u001b[0m sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.4\n", - "\u001b[93m [WARNING] \u001b[0m using untested triton version (3.0.0), only 1.0.0 is known to be compatible\n", - "[2024-08-06 18:14:47,065] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect)\n", - "/home/ubuntu/mlenv/lib/python3.12/site-packages/deepspeed/runtime/zero/linear.py:47: FutureWarning: `torch.cuda.amp.custom_fwd(args...)` is deprecated. Please use `torch.amp.custom_fwd(args..., device_type='cuda')` instead.\n", - " @autocast_custom_fwd\n", - "/home/ubuntu/mlenv/lib/python3.12/site-packages/deepspeed/runtime/zero/linear.py:66: FutureWarning: `torch.cuda.amp.custom_bwd(args...)` is deprecated. Please use `torch.amp.custom_bwd(args..., device_type='cuda')` instead.\n", - " @autocast_custom_bwd\n", - "\u001b[93m [WARNING] \u001b[0m sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.4\n", - "\u001b[93m [WARNING] \u001b[0m using untested triton version (3.0.0), only 1.0.0 is known to be compatible\n", - "[2024-08-06 18:14:47,135] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect)\n", - "\u001b[93m [WARNING] \u001b[0m async_io requires the dev libaio .so object and headers but these were not found.\n", - "/home/ubuntu/mlenv/lib/python3.12/site-packages/deepspeed/runtime/zero/linear.py:47: FutureWarning: `torch.cuda.amp.custom_fwd(args...)` is deprecated. Please use `torch.amp.custom_fwd(args..., device_type='cuda')` instead.\n", - " @autocast_custom_fwd\n", - "/home/ubuntu/mlenv/lib/python3.12/site-packages/deepspeed/runtime/zero/linear.py:66: FutureWarning: `torch.cuda.amp.custom_bwd(args...)` is deprecated. Please use `torch.amp.custom_bwd(args..., device_type='cuda')` instead.\n", - " @autocast_custom_bwd\n", - "\u001b[93m [WARNING] \u001b[0m async_io: please install the libaio-dev package with apt\n", - "\u001b[93m [WARNING] \u001b[0m If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found.\n", - "\u001b[93m [WARNING] \u001b[0m Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH\n", - "[2024-08-06 18:14:47,158] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect)\n", - "[2024-08-06 18:14:47,172] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect)\n", - "[2024-08-06 18:14:47,194] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect)\n", - "\u001b[93m [WARNING] \u001b[0m async_io requires the dev libaio .so object and headers but these were not found.\n", - "\u001b[93m [WARNING] \u001b[0m sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.4\n", - "\u001b[93m [WARNING] \u001b[0m using untested triton version (3.0.0), only 1.0.0 is known to be compatible\n", - "\u001b[93m [WARNING] \u001b[0m async_io: please install the libaio-dev package with apt\n", - "\u001b[93m [WARNING] \u001b[0m If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found.\n", - "\u001b[93m [WARNING] \u001b[0m Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH\n", - "\u001b[93m [WARNING] \u001b[0m async_io requires the dev libaio .so object and headers but these were not found.\n", - "\u001b[93m [WARNING] \u001b[0m async_io: please install the libaio-dev package with apt\n", - "\u001b[93m [WARNING] \u001b[0m If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found.\n", - "\u001b[93m [WARNING] \u001b[0m Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH\n", - "\u001b[93m [WARNING] \u001b[0m async_io requires the dev libaio .so object and headers but these were not found.\n", - "/home/ubuntu/mlenv/lib/python3.12/site-packages/deepspeed/runtime/zero/linear.py:47: FutureWarning: `torch.cuda.amp.custom_fwd(args...)` is deprecated. Please use `torch.amp.custom_fwd(args..., device_type='cuda')` instead.\n", - " @autocast_custom_fwd\n", - "/home/ubuntu/mlenv/lib/python3.12/site-packages/deepspeed/runtime/zero/linear.py:66: FutureWarning: `torch.cuda.amp.custom_bwd(args...)` is deprecated. Please use `torch.amp.custom_bwd(args..., device_type='cuda')` instead.\n", - " @autocast_custom_bwd\n", - "\u001b[93m [WARNING] \u001b[0m async_io: please install the libaio-dev package with apt\n", - "\u001b[93m [WARNING] \u001b[0m If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found.\n", - "\u001b[93m [WARNING] \u001b[0m Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH\n", - "\u001b[93m [WARNING] \u001b[0m async_io requires the dev libaio .so object and headers but these were not found.\n", - "\u001b[93m [WARNING] \u001b[0m sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.4\n", - "\u001b[93m [WARNING] \u001b[0m using untested triton version (3.0.0), only 1.0.0 is known to be compatible\n", - "\u001b[93m [WARNING] \u001b[0m async_io: please install the libaio-dev package with apt\n", - "\u001b[93m [WARNING] \u001b[0m If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found.\n", - "\u001b[93m [WARNING] \u001b[0m Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH\n", - "/home/ubuntu/mlenv/lib/python3.12/site-packages/deepspeed/runtime/zero/linear.py:47: FutureWarning: `torch.cuda.amp.custom_fwd(args...)` is deprecated. Please use `torch.amp.custom_fwd(args..., device_type='cuda')` instead.\n", - " @autocast_custom_fwd\n", - "/home/ubuntu/mlenv/lib/python3.12/site-packages/deepspeed/runtime/zero/linear.py:66: FutureWarning: `torch.cuda.amp.custom_bwd(args...)` is deprecated. Please use `torch.amp.custom_bwd(args..., device_type='cuda')` instead.\n", - " @autocast_custom_bwd\n", - "\u001b[93m [WARNING] \u001b[0m sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.4\n", - "\u001b[93m [WARNING] \u001b[0m using untested triton version (3.0.0), only 1.0.0 is known to be compatible\n", - "\u001b[93m [WARNING] \u001b[0m sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.4\n", - "\u001b[93m [WARNING] \u001b[0m using untested triton version (3.0.0), only 1.0.0 is known to be compatible\n", - "/home/ubuntu/mlenv/lib/python3.12/site-packages/deepspeed/runtime/zero/linear.py:47: FutureWarning: `torch.cuda.amp.custom_fwd(args...)` is deprecated. Please use `torch.amp.custom_fwd(args..., device_type='cuda')` instead.\n", - " @autocast_custom_fwd\n", - "/home/ubuntu/mlenv/lib/python3.12/site-packages/deepspeed/runtime/zero/linear.py:66: FutureWarning: `torch.cuda.amp.custom_bwd(args...)` is deprecated. Please use `torch.amp.custom_bwd(args..., device_type='cuda')` instead.\n", - " @autocast_custom_bwd\n", - "\u001b[93m [WARNING] \u001b[0m sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.4\n", - "\u001b[93m [WARNING] \u001b[0m using untested triton version (3.0.0), only 1.0.0 is known to be compatible\n", - "/home/ubuntu/mlenv/lib/python3.12/site-packages/deepspeed/runtime/zero/linear.py:47: FutureWarning: `torch.cuda.amp.custom_fwd(args...)` is deprecated. Please use `torch.amp.custom_fwd(args..., device_type='cuda')` instead.\n", - " @autocast_custom_fwd\n", - "/home/ubuntu/mlenv/lib/python3.12/site-packages/deepspeed/runtime/zero/linear.py:66: FutureWarning: `torch.cuda.amp.custom_bwd(args...)` is deprecated. Please use `torch.amp.custom_bwd(args..., device_type='cuda')` instead.\n", - " @autocast_custom_bwd\n", - "\u001b[93m [WARNING] \u001b[0m sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.4\n", - "\u001b[93m [WARNING] \u001b[0m using untested triton version (3.0.0), only 1.0.0 is known to be compatible\n", - "/home/ubuntu/mlenv/lib/python3.12/site-packages/deepspeed/runtime/zero/linear.py:47: FutureWarning: `torch.cuda.amp.custom_fwd(args...)` is deprecated. Please use `torch.amp.custom_fwd(args..., device_type='cuda')` instead.\n", - " @autocast_custom_fwd\n", - "/home/ubuntu/mlenv/lib/python3.12/site-packages/deepspeed/runtime/zero/linear.py:66: FutureWarning: `torch.cuda.amp.custom_bwd(args...)` is deprecated. Please use `torch.amp.custom_bwd(args..., device_type='cuda')` instead.\n", - " @autocast_custom_bwd\n", - "/home/ubuntu/mlenv/lib/python3.12/site-packages/deepspeed/runtime/zero/linear.py:47: FutureWarning: `torch.cuda.amp.custom_fwd(args...)` is deprecated. Please use `torch.amp.custom_fwd(args..., device_type='cuda')` instead.\n", - " @autocast_custom_fwd\n", - "/home/ubuntu/mlenv/lib/python3.12/site-packages/deepspeed/runtime/zero/linear.py:66: FutureWarning: `torch.cuda.amp.custom_bwd(args...)` is deprecated. Please use `torch.amp.custom_bwd(args..., device_type='cuda')` instead.\n", - " @autocast_custom_bwd\n", - "[2024-08-06 18:14:48,688] [INFO] [comm.py:637:init_distributed] cdb=None\n", - "[2024-08-06 18:14:48,695] [INFO] [comm.py:637:init_distributed] cdb=None\n", - "[2024-08-06 18:14:48,785] [INFO] [comm.py:637:init_distributed] cdb=None\n", - "[2024-08-06 18:14:48,850] [INFO] [comm.py:637:init_distributed] cdb=None\n", - "[2024-08-06 18:14:48,890] [INFO] [comm.py:637:init_distributed] cdb=None\n", - "Destroying existing process group\n", - "Destroying existing process group\n", - "[2024-08-06 18:14:48,922] [INFO] [comm.py:637:init_distributed] cdb=None\n", - "[2024-08-06 18:14:48,946] [INFO] [comm.py:637:init_distributed] cdb=None\n", - "[2024-08-06 18:14:48,947] [INFO] [comm.py:637:init_distributed] cdb=None\n", - "Destroying existing process group\n", - "Destroying existing process group\n", - "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n", - "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n", - "Destroying existing process group\n", - "Destroying existing process group\n", - "Destroying existing process group\n", - "Destroying existing process group\n", - "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n", - "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n", - "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n", - "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n", - "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n", - "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n", - "\n", - "Map: 0%| | 0/393 [00:00