onxx rename and prune

pull/2034/head
Hui Zhang 3 years ago
parent 28c1794b9b
commit 6477b6f3e6

@ -0,0 +1,127 @@
#!/usr/bin/env python3 -W ignore::DeprecationWarning
import argparse
import copy
import sys
import onnx
def parse_arguments():
parser = argparse.ArgumentParser()
parser.add_argument(
'--model',
required=True,
help='Path of directory saved the input model.')
parser.add_argument(
'--output_names',
required=True,
nargs='+',
help='The outputs of pruned model.')
parser.add_argument(
'--save_file', required=True, help='Path to save the new onnx model.')
return parser.parse_args()
if __name__ == '__main__':
args = parse_arguments()
if len(set(args.output_names)) < len(args.output_names):
print(
"[ERROR] There's dumplicate name in --output_names, which is not allowed."
)
sys.exit(-1)
model = onnx.load(args.model)
# collect all node outputs and graph output
output_tensor_names = set()
for node in model.graph.node:
for out in node.output:
# may contain model output
output_tensor_names.add(out)
# for out in model.graph.output:
# output_tensor_names.add(out.name)
for output_name in args.output_names:
if output_name not in output_tensor_names:
print(
"[ERROR] Cannot find output tensor name '{}' in onnx model graph.".
format(output_name))
sys.exit(-1)
output_node_indices = set() # has output names
output_to_node = dict() # all node outputs
for i, node in enumerate(model.graph.node):
for out in node.output:
output_to_node[out] = i
if out in args.output_names:
output_node_indices.add(i)
# from outputs find all the ancestors
reserved_node_indices = copy.deepcopy(
output_node_indices) # nodes need to keep
reserved_inputs = set() # model input to keep
new_output_node_indices = copy.deepcopy(output_node_indices)
while True and len(new_output_node_indices) > 0:
output_node_indices = copy.deepcopy(new_output_node_indices)
new_output_node_indices = set()
for out_node_idx in output_node_indices:
# backtrace to parenet
for ipt in model.graph.node[out_node_idx].input:
if ipt in output_to_node:
reserved_node_indices.add(output_to_node[ipt])
new_output_node_indices.add(output_to_node[ipt])
else:
reserved_inputs.add(ipt)
num_inputs = len(model.graph.input)
num_outputs = len(model.graph.output)
num_nodes = len(model.graph.node)
print(
f"old graph has {num_inputs} inputs, {num_outputs} outpus, {num_nodes} nodes"
)
print(f"{len(reserved_node_indices)} node to keep.")
# del node not to keep
for idx in range(num_nodes - 1, -1, -1):
if idx not in reserved_node_indices:
del model.graph.node[idx]
# del graph input not to keep
for idx in range(num_inputs - 1, -1, -1):
if model.graph.input[idx].name not in reserved_inputs:
del model.graph.input[idx]
# del old graph outputs
for i in range(num_outputs):
del model.graph.output[0]
# new graph output as user input
for out in args.output_names:
model.graph.output.extend([onnx.ValueInfoProto(name=out)])
# infer shape
try:
from onnx_infer_shape import SymbolicShapeInference
model = SymbolicShapeInference.infer_shapes(
model,
int_max=2**31 - 1,
auto_merge=True,
guess_output_rank=False,
verbose=1)
except Exception as e:
print(f"skip infer shape step: {e}")
# check onnx model
onnx.checker.check_model(model)
# save onnx model
onnx.save(model, args.save_file)
print("[Finished] The new model saved in {}.".format(args.save_file))
print("[DEBUG INFO] The inputs of new model: {}".format(
[x.name for x in model.graph.input]))
print("[DEBUG INFO] The outputs of new model: {}".format(
[x.name for x in model.graph.output]))

@ -0,0 +1,110 @@
#!/usr/bin/env python3 -W ignore::DeprecationWarning
import argparse
import sys
import onnx
def parse_arguments():
parser = argparse.ArgumentParser()
parser.add_argument(
'--model',
required=True,
help='Path of directory saved the input model.')
parser.add_argument(
'--origin_names',
required=True,
nargs='+',
help='The original name you want to modify.')
parser.add_argument(
'--new_names',
required=True,
nargs='+',
help='The new name you want change to, the number of new_names should be same with the number of origin_names'
)
parser.add_argument(
'--save_file', required=True, help='Path to save the new onnx model.')
return parser.parse_args()
if __name__ == '__main__':
args = parse_arguments()
if len(set(args.origin_names)) < len(args.origin_names):
print(
"[ERROR] There's dumplicate name in --origin_names, which is not allowed."
)
sys.exit(-1)
if len(set(args.new_names)) < len(args.new_names):
print(
"[ERROR] There's dumplicate name in --new_names, which is not allowed."
)
sys.exit(-1)
if len(args.new_names) != len(args.origin_names):
print(
"[ERROR] Number of --new_names must be same with the number of --origin_names."
)
sys.exit(-1)
model = onnx.load(args.model)
# collect input and all node output
output_tensor_names = set()
for ipt in model.graph.input:
output_tensor_names.add(ipt.name)
for node in model.graph.node:
for out in node.output:
output_tensor_names.add(out)
for origin_name in args.origin_names:
if origin_name not in output_tensor_names:
print(
f"[ERROR] Cannot find tensor name '{origin_name}' in onnx model graph."
)
sys.exit(-1)
for new_name in args.new_names:
if new_name in output_tensor_names:
print(
"[ERROR] The defined new_name '{}' is already exist in the onnx model, which is not allowed."
)
sys.exit(-1)
# rename graph input
for i, ipt in enumerate(model.graph.input):
if ipt.name in args.origin_names:
idx = args.origin_names.index(ipt.name)
model.graph.input[i].name = args.new_names[idx]
# rename node input and output
for i, node in enumerate(model.graph.node):
for j, ipt in enumerate(node.input):
if ipt in args.origin_names:
idx = args.origin_names.index(ipt)
model.graph.node[i].input[j] = args.new_names[idx]
for j, out in enumerate(node.output):
if out in args.origin_names:
idx = args.origin_names.index(out)
model.graph.node[i].output[j] = args.new_names[idx]
# rename graph output
for i, out in enumerate(model.graph.output):
if out.name in args.origin_names:
idx = args.origin_names.index(out.name)
model.graph.output[i].name = args.new_names[idx]
# check onnx model
onnx.checker.check_model(model)
# save model
onnx.save(model, args.save_file)
print("[Finished] The new model saved in {}.".format(args.save_file))
print("[DEBUG INFO] The inputs of new model: {}".format(
[x.name for x in model.graph.input]))
print("[DEBUG INFO] The outputs of new model: {}".format(
[x.name for x in model.graph.output]))

@ -3,6 +3,7 @@
set -e set -e
if [ $# != 5 ]; then if [ $# != 5 ]; then
# local/prune.sh data/exp/deepspeech2_online/checkpoints avg_1.jit.pdmodel avg_1.jit.pdiparams softmax_0.tmp_0,tmp_5,concat_0.tmp_0,concat_1.tmp_0 $PWD
echo "usage: $0 model_dir model_filename param_filename outputs_names save_dir" echo "usage: $0 model_dir model_filename param_filename outputs_names save_dir"
exit 1 exit 1
fi fi

@ -1,6 +1,7 @@
#!/bin/bash #!/bin/bash
if [ $# != 4 ];then if [ $# != 4 ];then
# local/tonnx.sh data/exp/deepspeech2_online/checkpoints avg_1.jit.pdmodel avg_1.jit.pdiparams exp/model.onnx
echo "usage: $0 model_dir model_name param_name onnx_output_name" echo "usage: $0 model_dir model_name param_name onnx_output_name"
exit 1 exit 1
fi fi
@ -11,6 +12,7 @@ param=$3
output=$4 output=$4
pip install paddle2onnx pip install paddle2onnx
pip install onnx
# https://github.com/PaddlePaddle/Paddle2ONNX#%E5%91%BD%E4%BB%A4%E8%A1%8C%E8%BD%AC%E6%8D%A2 # https://github.com/PaddlePaddle/Paddle2ONNX#%E5%91%BD%E4%BB%A4%E8%A1%8C%E8%BD%AC%E6%8D%A2
paddle2onnx --model_dir $dir \ paddle2onnx --model_dir $dir \

@ -10,6 +10,9 @@ stop_stage=100
. utils/parse_options.sh . utils/parse_options.sh
data=data data=data
exp=exp
mkdir -p $data $exp
if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ];then if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ];then
test -f $data/asr0_deepspeech2_online_wenetspeech_ckpt_1.0.0a.model.tar.gz || wget -c https://paddlespeech.bj.bcebos.com/s2t/wenetspeech/asr0/asr0_deepspeech2_online_wenetspeech_ckpt_1.0.0a.model.tar.gz -P $data test -f $data/asr0_deepspeech2_online_wenetspeech_ckpt_1.0.0a.model.tar.gz || wget -c https://paddlespeech.bj.bcebos.com/s2t/wenetspeech/asr0/asr0_deepspeech2_online_wenetspeech_ckpt_1.0.0a.model.tar.gz -P $data
@ -25,21 +28,24 @@ param=avg_1.jit.pdiparams
output_names=softmax_0.tmp_0,tmp_5,concat_0.tmp_0,concat_1.tmp_0 output_names=softmax_0.tmp_0,tmp_5,concat_0.tmp_0,concat_1.tmp_0
if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ];then if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ];then
mkdir -p $data/prune mkdir -p $exp/prune
# prune model deps on output_names. # prune model deps on output_names.
./local/prune.sh $dir $model $param $output_names $data/prune ./local/prune.sh $dir $model $param $output_names $exp/prune
fi fi
input_shape_dict="{'audio_chunk':[1,-1,161], 'audio_chunk_lens':[1], 'chunk_state_c_box':[5, 1, 1024], 'chunk_state_h_box':[5,1,1024]}" input_shape_dict="{'audio_chunk':[1,-1,161], 'audio_chunk_lens':[1], 'chunk_state_c_box':[5, 1, 1024], 'chunk_state_h_box':[5,1,1024]}"
if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ];then if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ];then
mkdir -p $data/shape mkdir -p $exp/shape
python3 local/pd_infer_shape.py \ python3 local/pd_infer_shape.py \
--model_dir $dir \ --model_dir $dir \
--model_filename $model \ --model_filename $model \
--params_filename $param \ --params_filename $param \
--save_dir $data/shape \ --save_dir $exp/shape \
--input_shape_dict=${input_shape_dict} --input_shape_dict=${input_shape_dict}
fi fi
if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ];then
./local/tonnx.sh $dir $model $param $exp/model.onnx
fi
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