# bloom-demo Early dev prototype for decentralized bloom. Not for public eyes **yet**. Roadmap: [issue #12](https://github.com/learning-at-home/bloom-demo/issues/12) Latest news @ main branch (max 5): - [Jul 4] @dbaranchuk implemented chained rpc_forward and rpc_backward (for prompt tuning) - [Jul 3] @dbaranchuk optimized DistributedBloom to reduce embeddings/logits RAM usage - [Jul 1] @yozh added RemoteSequential and test for full model exact match - [June 28] @dbaranchunk added quick deployment scripts for testnet ### install ```bash conda create -y --name bloom-demo python=3.8.12 pip conda activate bloom-demo conda install -y -c conda-forge cudatoolkit-dev==11.3.1 cudatoolkit==11.3.1 cudnn==8.2.1.32 pip install torch==1.11.0+cu113 torchvision==0.12.0+cu113 -f https://download.pytorch.org/whl/torch_stable.html pip install accelerate==0.10.0 huggingface-hub==0.7.0 hivemind==1.1.0 pip install bitsandbytes-cuda113==0.26.0 pip install https://github.com/huggingface/transformers/archive/6589e510fa4e6c442059de2fab84752535de9b23.zip ``` ### run local inference: No networking whatsoever, used to verify architecture optimizations ```bash # run one bloom block for a few steps -- on a local machine python -m cli.inference_one_block --config cli/config.json # see other args ``` ### run distributed inference / training First, run one or more servers like this: ```bash # minimalistic server with non-trained bloom blocks python -m cli.run_server --converted_model_name_or_path bigscience/test-bloomd-6b3 \ --block_indices 3:5 --torch_dtype float32 --identity_path ./server1.id --host_maddrs /ip4/127.0.0.1/tcp/31337 # when running multiple servers: # - give each server a unique --identity_path (or remote --identity_path arg when debugging) # - if running multiple servers on the same machine, give each a unique port (last integer in --host_maddrs, 0 means random port) # - when running over the internet, change --host_maddrs according to https://learning-at-home.readthedocs.io/en/latest/user/dht.html#running-across-the-internet # - each server except first should have --initial_peers pointing to one of pre-existing servers ``` Then open a python notebook or console and run: ```python import torch import hivemind from src import get_remote_module dht = hivemind.DHT( initial_peers=[TODO_COPY_FULL_ADDRESS_FROM_ANY_OF_THE_SERVERS], # e.g. /ip4/127.0.0.1/... client_mode=True, start=True, ) layer3, layer4 = get_remote_module(dht, ['bigscience/test-bloomd-6b3.3', 'bigscience/test-bloomd-6b3.4']) assert layer3 is not None and layer4 is not None, "one or both layers were not found in DHT" # test forward/backward, two blocks outputs, = layer4(*layer3(torch.randn(1, 64, 4096))) loss = (outputs * torch.randn_like(outputs)).norm() loss.backward() # test inference, one block with layer3.begin_inference_session() as sess: for i in range(10): res = sess.step(torch.ones(1, 1, 4096)) ``` ### convert regular bloom to distributed ```bash # convert model from HF hub to a distributed format (can take hours depending on your connection!) MY_WRITE_TOKEN=TODO_WRITE_TOKEN_FROM_https://huggingface.co/settings/token python -m cli.convert_model --model bigscience/bloom-6b3 \ --output_path ./converted_model --output_repo bigscience/test-bloomd-6b3 \ --use_auth_token $MY_WRITE_TOKEN # ^-- todo replace output repo with something you have access to ``` ### test local vs remote block (allclose) To test distributed inference, run one or more servers, then open a new shell and run pytest with environment variables: ```bash # shell A: serve blocks 3 and 4 python -m cli.run_server --converted_model_name_or_path bigscience/test-bloomd-6b3 \ --block_indices 3:5 --torch_dtype float32 --identity_path ./server1.id --host_maddrs /ip4/127.0.0.1/tcp/31337 # shell B: connect to the swarm and test individual blocks for exact match export PYTHONPATH=. INITIAL_PEERS="/ip4/TODO_COPY_INITIAL_PEERS_FROM_SERVER_OUTPUT" BLOCK_UID=bigscience/test-bloomd-6b3.3 pytest tests/test_block_exact_match.py BLOCK_UID=bigscience/test-bloomd-6b3.4 pytest tests/test_block_exact_match.py # the test below will fail because there is no server that serves layer 7 # BLOCK_UID=bigscience/test-bloomd-6b3.7 pytest tests/test_block_exact_match.py BLOCK_UID=bigscience/test-bloomd-6b3.4 pytest tests/test_block_exact_match.py ```