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benchmarks.yml
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# Copyright (c) 2022 Graphcore Ltd. All rights reserved.
# --- Benchmark Message Passing Neural Network model ---
train_options: &train_options
env:
TF_POPLAR_FLAGS: '--executable_cache_path=./tf_cache/'
data:
throughput:
regexp: 'throughput: *(.*?) samples\/sec'
skip: 1
loss:
regexp: 'loss: *(\d*\.\d*)'
reduction_type: "final"
output:
- [samples/sec, 'throughput']
- [loss, 'loss']
tf2_message_passing_graph_isomorphism_train_gen_4ipu:
<<: *train_options
description: |
This benchmark measures the throughput of
Graph Isomorphism MPNN training
on a generated dataset.
cmd: >-
python3 run_training.py
--model=graph_isomorphism
--epochs=20
--replicas=4
--micro_batch_size=256
--use_edges=True
--lr=1e-5
--loss_scaling=1.0
--generated_data=True
--generated_batches_per_epoch=16384
--n_nodes_per_pack=24
--n_edges_per_pack=50
--n_graphs_per_pack=1
--do_validation=False
--do_test=False
--checkpoint_every_n_epochs=10
--wandb=False
tf2_message_passing_interaction_network_train_gen_1ipu:
<<: *train_options
description: |
This benchmark measures the throughput of
Interaction Network MPNN training
on a generated dataset.
cmd: >-
python3 run_training.py
--model=interaction_network
--epochs=20
--replicas=1
--micro_batch_size=128
--lr=1e-5
--loss_scaling=1.0
--generated_data=True
--n_nodes_per_pack=24
--n_edges_per_pack=50
--n_graphs_per_pack=1
--do_validation=False
--do_test=False
--checkpoint_every_n_epochs=10
--wandb=False
tf2_message_passing_graph_network_train_gen_1ipu:
<<: *train_options
description: |
This benchmark measures the throughput of
Graph Network MPNN training
on a generated dataset.
cmd: >-
python3 run_training.py
--model=graph_network
--epochs=20
--replicas=1
--micro_batch_size=128
--lr=1e-5
--loss_scaling=1.0
--generated_data=True
--n_nodes_per_pack=24
--n_edges_per_pack=50
--n_graphs_per_pack=1
--do_validation=False
--do_test=False
--checkpoint_every_n_epochs=10
--wandb=False