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Commit df89801f authored by Erick Lavoie's avatar Erick Lavoie
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Added experiments on removing edges for CIFAR10

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#!/usr/bin/env bash
# Path to current script
SCRIPT_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )"
TOOLS=$SCRIPT_DIR/$(cat toolspath); cd $TOOLS
# Add current working directory to executable namespace
export PATH=$PATH:$TOOLS
# Setup root directory for resolution of imports:
# the path of all local python libraries are relative to this
export PYTHONPATH=$TOOLS
# Each command outputs the run directory, which is then used
# by the next command to add parameters and generate information
# used by the simulator. For a list of available options for each
# command, run 'export PYTHONPATH=.; <command> --help'.
for RM_EDGES in 1 5; do
for C_GRAD in '--clique-gradient' ''; do
setup/meta.py \
--script $SCRIPT_DIR/`basename "$0"` \
--results-directory $SCRIPT_DIR/tmp \
--seed 1 |
setup/dataset.py \
--name cifar10 \
--train-examples-per-class 5000 5000 5000 5000 5000 5000 5000 5000 5000 5000 \
--validation-examples-per-class 0 0 0 0 0 0 0 0 0 0 |
setup/nodes/google-fl.py \
--name 2-shards-eq-classes \
--nb-nodes 100 \
--local-shards 2 \
--shard-size 250 |
setup/topology/d_cliques/greedy_swap.py \
--interclique fully-connected \
--max-clique-size 10 \
--max-steps 1000 |
setup/model/gn_lenet.py |
simulate/algorithm/d_sgd.py \
--batch-size 20 \
--learning-momentum 0.9 \
$C_GRAD \
--learning-rate 0.002 |
simulate/logger.py \
--accuracy-logging-interval 10\
--nb-processes 1 |
simulate/run.py \
--nb-epochs 100;
done;
done
#!/usr/bin/env bash
# Path to current script
SCRIPT_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )"
TOOLS=$SCRIPT_DIR/$(cat toolspath); cd $TOOLS
# Add current working directory to executable namespace
export PATH=$PATH:$TOOLS
# Setup root directory for resolution of imports:
# the path of all local python libraries are relative to this
export PYTHONPATH=$TOOLS
# Each command outputs the run directory, which is then used
# by the next command to add parameters and generate information
# used by the simulator. For a list of available options for each
# command, run 'export PYTHONPATH=.; <command> --help'.
for RM_EDGES in 1 5; do
for C_GRAD in '--clique-gradient' ''; do
setup/meta.py \
--script $SCRIPT_DIR/`basename "$0"` \
--results-directory $SCRIPT_DIR/tmp \
--seed 1 |
setup/dataset.py \
--name cifar10 \
--train-examples-per-class 4500 4500 4500 4500 4500 4500 4500 4500 4500 4500 \
--validation-examples-per-class 500 500 500 500 500 500 500 500 500 500 |
setup/nodes.py \
--name max-local-skew \
--nb-nodes 100 \
--nodes-per-class 10 10 10 10 10 10 10 10 10 10 \
--local-classes 1 |
setup/topology/d_cliques/ideal.py \
--interclique fully-connected |
setup/model/gn_lenet.py |
simulate/algorithm/d_sgd.py \
--batch-size 20 \
--learning-momentum 0.9 \
$C_GRAD \
--learning-rate 0.002 |
simulate/logger.py \
--accuracy-logging-interval 10\
--nb-processes 1 |
simulate/run.py \
--nb-epochs 100;
done;
done
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