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mikekgfbmalfet
mikekgfb
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malfet
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remove macos-12 test (#501)
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‎.github/workflows/pull.yml

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@@ -458,81 +458,6 @@ jobs:
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python torchchat.py generate stories15M
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python torchchat.py remove stories15m
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test-tinystories-eager:
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strategy:
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matrix:
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runner: [macos-12]
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runs-on: ${{matrix.runner}}
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steps:
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- name: Checkout repo
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uses: actions/checkout@v2
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- name: Setup Python
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uses: actions/setup-python@v2
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with:
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python-version: 3.11
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- name: Print machine info
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run: |
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uname -a
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if [ $(uname -s) == Darwin ]; then
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sysctl machdep.cpu.brand_string
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sysctl machdep.cpu.core_count
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fi
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- name: Install requirements
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run: |
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pip install --pre torch --index-url https://download.pytorch.org/whl/nightly/cpu
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pip install -r requirements.txt
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python3 -c 'import torch;print(f"torch: {torch.__version__, torch.version.git_version}")'
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- name: Download checkpoints
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run: |
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mkdir -p checkpoints/stories15M
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pushd checkpoints/stories15M
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wget https://huggingface.co/karpathy/tinyllamas/resolve/main/stories15M.pt
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wget https://github.com/karpathy/llama2.c/raw/master/tokenizer.model
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popd
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- name: Run inference
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run: |
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export MODEL_PATH=checkpoints/stories15M/stories15M.pt
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export MODEL_NAME=stories15M
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export MODEL_DIR=/tmp
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for DTYPE in bfloat16 float16 float32; do
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# if [ $(uname -s) == Darwin ]; then
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# export DTYPE=float16
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# fi
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python3 torchchat.py generate --dtype ${DTYPE} --checkpoint-path ${MODEL_PATH} --temperature 0
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echo "******************************************"
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echo "******* Emb: channel-wise quantized ******"
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echo "******************************************"
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python3 torchchat.py generate --dtype ${DTYPE} --quant '{"embedding" : {"bitwidth": 8, "groupsize": 0}}' --checkpoint-path ${MODEL_PATH} --temperature 0
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echo "******************************************"
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echo "******** Emb: group-wise quantized *******"
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echo "******************************************"
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python3 torchchat.py generate --dtype ${DTYPE} --quant '{"embedding" : {"bitwidth": 8, "groupsize": 8}}' --checkpoint-path ${MODEL_PATH} --temperature 0
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echo "******************************************"
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echo "******* INT8 channel-wise quantized ******"
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echo "******************************************"
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python3 torchchat.py generate --dtype ${DTYPE} --quant '{"linear:int8" : {"bitwidth": 8, "groupsize": 0}}' --checkpoint-path ${MODEL_PATH} --temperature 0
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echo "******************************************"
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echo "******** INT8 group-wise quantized *******"
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echo "******************************************"
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python3 torchchat.py generate --dtype ${DTYPE} --quant '{"linear:int8" : {"bitwidth": 8, "groupsize": 8}}' --checkpoint-path ${MODEL_PATH} --temperature 0
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echo "******************************************"
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echo "******** INT4 group-wise quantized *******"
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echo "******************************************"
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echo "INT4 should work on MacOS on x86, but cannot be tested"
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echo "because nightlies are too old!"
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# python3 torchchat.py generate --dtype ${DTYPE} --quant '{"linear:int4" : {"groupsize": 32}}' --checkpoint-path ${MODEL_PATH} --temperature 0
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echo "tests complete for ${DTYPE}"
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done
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echo "tests complete for all dtypes!"
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test-mps:
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uses: pytorch/test-infra/.github/workflows/macos_job.yml@main
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with:

‎parking_lot/macos-12-x86.yml

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@@ -0,0 +1,75 @@
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test-tinystories-eager:
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strategy:
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matrix:
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runner: [macos-12]
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runs-on: ${{matrix.runner}}
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steps:
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- name: Checkout repo
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uses: actions/checkout@v2
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- name: Setup Python
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uses: actions/setup-python@v2
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with:
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python-version: 3.11
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- name: Print machine info
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run: |
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uname -a
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if [ $(uname -s) == Darwin ]; then
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sysctl machdep.cpu.brand_string
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sysctl machdep.cpu.core_count
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fi
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- name: Install requirements
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run: |
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pip install --pre torch --index-url https://download.pytorch.org/whl/nightly/cpu
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pip install -r requirements.txt
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python3 -c 'import torch;print(f"torch: {torch.__version__, torch.version.git_version}")'
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- name: Download checkpoints
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run: |
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mkdir -p checkpoints/stories15M
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pushd checkpoints/stories15M
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wget https://huggingface.co/karpathy/tinyllamas/resolve/main/stories15M.pt
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wget https://github.com/karpathy/llama2.c/raw/master/tokenizer.model
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popd
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- name: Run inference
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run: |
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export MODEL_PATH=checkpoints/stories15M/stories15M.pt
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export MODEL_NAME=stories15M
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export MODEL_DIR=/tmp
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for DTYPE in bfloat16 float16 float32; do
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# if [ $(uname -s) == Darwin ]; then
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# export DTYPE=float16
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# fi
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python3 torchchat.py generate --dtype ${DTYPE} --checkpoint-path ${MODEL_PATH} --temperature 0
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echo "******************************************"
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echo "******* Emb: channel-wise quantized ******"
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echo "******************************************"
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python3 torchchat.py generate --dtype ${DTYPE} --quant '{"embedding" : {"bitwidth": 8, "groupsize": 0}}' --checkpoint-path ${MODEL_PATH} --temperature 0
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echo "******************************************"
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echo "******** Emb: group-wise quantized *******"
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echo "******************************************"
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python3 torchchat.py generate --dtype ${DTYPE} --quant '{"embedding" : {"bitwidth": 8, "groupsize": 8}}' --checkpoint-path ${MODEL_PATH} --temperature 0
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echo "******************************************"
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echo "******* INT8 channel-wise quantized ******"
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echo "******************************************"
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python3 torchchat.py generate --dtype ${DTYPE} --quant '{"linear:int8" : {"bitwidth": 8, "groupsize": 0}}' --checkpoint-path ${MODEL_PATH} --temperature 0
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echo "******************************************"
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echo "******** INT8 group-wise quantized *******"
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echo "******************************************"
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python3 torchchat.py generate --dtype ${DTYPE} --quant '{"linear:int8" : {"bitwidth": 8, "groupsize": 8}}' --checkpoint-path ${MODEL_PATH} --temperature 0
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echo "******************************************"
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echo "******** INT4 group-wise quantized *******"
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echo "******************************************"
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echo "INT4 should work on MacOS on x86, but cannot be tested"
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echo "because nightlies are too old!"
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# python3 torchchat.py generate --dtype ${DTYPE} --quant '{"linear:int4" : {"groupsize": 32}}' --checkpoint-path ${MODEL_PATH} --temperature 0
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echo "tests complete for ${DTYPE}"
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done
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echo "tests complete for all dtypes!"

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