inference_demo.sh

# Copyright 2024 ByteDance and/or its affiliates.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#      http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

export LAYERNORM_TYPE=fast_layernorm
export USE_DEEPSPEED_EVO_ATTENTION=true

N_sample=5
N_step=200
N_cycle=10
seed=101

input_json_path="./examples/example.json"
dump_dir="./output"
# model_name="protenix_base_default_v0.5.0"
model_name = 'protenix_tiny_detault_v0.5.0'

python3 runner/inference.py \
--model_name ${model_name} \
--seeds ${seed} \
--dump_dir ${dump_dir} \
--input_json_path ${input_json_path} \
--model.N_cycle ${N_cycle} \
--sample_diffusion.N_sample ${N_sample} \
--sample_diffusion.N_step ${N_step}

# The following is a demo to use DDP for inference
# torchrun \
#     --nproc_per_node $NPROC \
#     --master_addr $WORKER_0_HOST \
#     --master_port $WORKER_0_PORT \
#     --node_rank=$ID \
#     --nnodes=$WORKER_NUM \
#     runner/inference.py \
#     --seeds ${seed} \
#     --dump_dir ${dump_dir} \
#     --input_json_path ${input_json_path} \
#     --model.N_cycle ${N_cycle} \
#     --sample_diffusion.N_sample ${N_sample} \
#     --sample_diffusion.N_step ${N_step}