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Merge pull request #2116 from zh794390558/onnx

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[speechx]remove fluid tools for onnx export
pull/2120/head
Hui Zhang 3 years ago committed by GitHub
parent 8817bf8636 a9a3cb4860
commit 803fec21aa
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4 changed files with 3 additions and 326 deletions
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111
speechx/examples/ds2_ol/onnx/local/pd_infer_shape.py
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#!/usr/bin/env python3 -W ignore::DeprecationWarning
# https://github.com/jiangjiajun/PaddleUtils/blob/main/paddle/README.md#2-%E4%BF%AE%E6%94%B9paddle%E6%A8%A1%E5%9E%8B%E8%BE%93%E5%85%A5shape
import argparse
# paddle inference shape
def process_old_ops_desc(program):
"""set matmul op head_number attr to 1 is not exist.
Args:
program (_type_): _description_
"""
for i in range(len(program.blocks[0].ops)):
if program.blocks[0].ops[i].type == "matmul":
if not program.blocks[0].ops[i].has_attr("head_number"):
program.blocks[0].ops[i]._set_attr("head_number", 1)
def infer_shape(program, input_shape_dict):
# 2002002
model_version = program.desc._version()
# 2.2.2
paddle_version = paddle.__version__
major_ver = model_version // 1000000
minor_ver = (model_version - major_ver * 1000000) // 1000
patch_ver = model_version - major_ver * 1000000 - minor_ver * 1000
model_version = "{}.{}.{}".format(major_ver, minor_ver, patch_ver)
if model_version != paddle_version:
print(
f"[WARNING] The model is saved by paddlepaddle v{model_version}, but now your paddlepaddle is version of {paddle_version}, this difference may cause error, it is recommend you reinstall a same version of paddlepaddle for this model"
)
OP_WITHOUT_KERNEL_SET = {
'feed', 'fetch', 'recurrent', 'go', 'rnn_memory_helper_grad',
'conditional_block', 'while', 'send', 'recv', 'listen_and_serv',
'fl_listen_and_serv', 'ncclInit', 'select', 'checkpoint_notify',
'gen_bkcl_id', 'c_gen_bkcl_id', 'gen_nccl_id', 'c_gen_nccl_id',
'c_comm_init', 'c_sync_calc_stream', 'c_sync_comm_stream',
'queue_generator', 'dequeue', 'enqueue', 'heter_listen_and_serv',
'c_wait_comm', 'c_wait_compute', 'c_gen_hccl_id', 'c_comm_init_hccl',
'copy_cross_scope'
}
for k, v in input_shape_dict.items():
program.blocks[0].var(k).desc.set_shape(v)
for i in range(len(program.blocks)):
for j in range(len(program.blocks[0].ops)):
# for ops
if program.blocks[i].ops[j].type in OP_WITHOUT_KERNEL_SET:
print(f"not infer: {program.blocks[i].ops[j].type} op")
continue
print(f"infer: {program.blocks[i].ops[j].type} op")
program.blocks[i].ops[j].desc.infer_shape(program.blocks[i].desc)
def parse_arguments():
# python pd_infer_shape.py --model_dir data/exp/deepspeech2_online/checkpoints \
# --model_filename avg_1.jit.pdmodel\
# --params_filename avg_1.jit.pdiparams \
# --save_dir . \
# --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]}"
parser = argparse.ArgumentParser()
parser.add_argument(
'--model_dir',
required=True,
help='Path of directory saved the input model.')
parser.add_argument(
'--model_filename', required=True, help='model.pdmodel.')
parser.add_argument(
'--params_filename', required=True, help='model.pdiparams.')
parser.add_argument(
'--save_dir',
required=True,
help='directory to save the exported model.')
parser.add_argument(
'--input_shape_dict', required=True, help="The new shape information.")
return parser.parse_args()
if __name__ == '__main__':
args = parse_arguments()
import paddle
paddle.enable_static()
import paddle.fluid as fluid
input_shape_dict_str = args.input_shape_dict
input_shape_dict = eval(input_shape_dict_str)
print("Start to load paddle model...")
exe = fluid.Executor(fluid.CPUPlace())
prog, ipts, outs = fluid.io.load_inference_model(
args.model_dir,
exe,
model_filename=args.model_filename,
params_filename=args.params_filename)
process_old_ops_desc(prog)
infer_shape(prog, input_shape_dict)
fluid.io.save_inference_model(
args.save_dir,
ipts,
outs,
exe,
prog,
model_filename=args.model_filename,
params_filename=args.params_filename)

158
speechx/examples/ds2_ol/onnx/local/pd_prune_model.py
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#!/usr/bin/env python3 -W ignore::DeprecationWarning
# https://github.com/jiangjiajun/PaddleUtils/blob/main/paddle/README.md#1-%E8%A3%81%E5%89%AApaddle%E6%A8%A1%E5%9E%8B
import argparse
import sys
from typing import List
# paddle prune model.
def prepend_feed_ops(program,
feed_target_names: List[str],
feed_holder_name='feed'):
import paddle.fluid.core as core
if len(feed_target_names) == 0:
return
global_block = program.global_block()
feed_var = global_block.create_var(
name=feed_holder_name,
type=core.VarDesc.VarType.FEED_MINIBATCH,
persistable=True, )
for i, name in enumerate(feed_target_names, 0):
if not global_block.has_var(name):
print(
f"The input[{i}]: '{name}' doesn't exist in pruned inference program, which will be ignored in new saved model."
)
continue
out = global_block.var(name)
global_block._prepend_op(
type='feed',
inputs={'X': [feed_var]},
outputs={'Out': [out]},
attrs={'col': i}, )
def append_fetch_ops(program,
fetch_target_names: List[str],
fetch_holder_name='fetch'):
"""in the place, we will add the fetch op
Args:
program (_type_): inference program
fetch_target_names (List[str]): target names
fetch_holder_name (str, optional): fetch op name. Defaults to 'fetch'.
"""
import paddle.fluid.core as core
global_block = program.global_block()
fetch_var = global_block.create_var(
name=fetch_holder_name,
type=core.VarDesc.VarType.FETCH_LIST,
persistable=True, )
print(f"the len of fetch_target_names: {len(fetch_target_names)}")
for i, name in enumerate(fetch_target_names):
global_block.append_op(
type='fetch',
inputs={'X': [name]},
outputs={'Out': [fetch_var]},
attrs={'col': i}, )
def insert_fetch(program,
fetch_target_names: List[str],
fetch_holder_name='fetch'):
"""in the place, we will add the fetch op
Args:
program (_type_): inference program
fetch_target_names (List[str]): target names
fetch_holder_name (str, optional): fetch op name. Defaults to 'fetch'.
"""
global_block = program.global_block()
# remove fetch
need_to_remove_op_index = []
for i, op in enumerate(global_block.ops):
if op.type == 'fetch':
need_to_remove_op_index.append(i)
for index in reversed(need_to_remove_op_index):
global_block._remove_op(index)
program.desc.flush()
# append new fetch
append_fetch_ops(program, fetch_target_names, fetch_holder_name)
def parse_arguments():
parser = argparse.ArgumentParser()
parser.add_argument(
'--model_dir',
required=True,
help='Path of directory saved the input model.')
parser.add_argument(
'--model_filename', required=True, help='model.pdmodel.')
parser.add_argument(
'--params_filename', required=True, help='model.pdiparams.')
parser.add_argument(
'--output_names',
required=True,
help='The outputs of model. sep by comma')
parser.add_argument(
'--save_dir',
required=True,
help='directory to save the exported model.')
parser.add_argument('--debug', default=False, help='output debug info.')
return parser.parse_args()
if __name__ == '__main__':
args = parse_arguments()
args.output_names = args.output_names.split(",")
if len(set(args.output_names)) < len(args.output_names):
print(
f"[ERROR] There's dumplicate name in --output_names {args.output_names}, which is not allowed."
)
sys.exit(-1)
import paddle
paddle.enable_static()
# hack prepend_feed_ops
paddle.fluid.io.prepend_feed_ops = prepend_feed_ops
import paddle.fluid as fluid
print("start to load paddle model")
exe = fluid.Executor(fluid.CPUPlace())
prog, ipts, outs = fluid.io.load_inference_model(
args.model_dir,
exe,
model_filename=args.model_filename,
params_filename=args.params_filename)
print("start to load insert fetch op")
new_outputs = []
insert_fetch(prog, args.output_names)
for out_name in args.output_names:
new_outputs.append(prog.global_block().var(out_name))
# not equal to paddle.static.save_inference_model
fluid.io.save_inference_model(
args.save_dir,
ipts,
new_outputs,
exe,
prog,
model_filename=args.model_filename,
params_filename=args.params_filename)
if args.debug:
for op in prog.global_block().ops:
print(op)

23
speechx/examples/ds2_ol/onnx/local/prune.sh
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#!/bin/bash
set -e
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"
exit 1
fi
dir=$1
model=$2
param=$3
outputs=$4
save_dir=$5
python local/pd_prune_model.py \
--model_dir $dir \
--model_filename $model \
--params_filename $param \
--output_names $outputs \
--save_dir $save_dir

37
speechx/examples/ds2_ol/onnx/run.sh
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@ -39,41 +39,10 @@ if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ];then
popd
fi
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
# prune model by outputs
mkdir -p $exp/prune
# prune model deps on output_names.
./local/prune.sh $dir $model $param $output_names $exp/prune
fi
# aishell rnn hidden is 1024
# wenetspeech rnn hiddn is 2048
if [ $model_type == 'aishell' ];then
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]}"
elif [ $model_type == 'wenetspeech' ];then
input_shape_dict="{'audio_chunk':[1,-1,161], 'audio_chunk_lens':[1], 'chunk_state_c_box':[5, 1, 2048], 'chunk_state_h_box':[5,1,2048]}"
else
echo "not support: $model_type"
exit -1
fi
if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ];then
# infer shape by new shape
mkdir -p $exp/shape
echo $input_shape_dict
python3 local/pd_infer_shape.py \
--model_dir $dir \
--model_filename $model \
--params_filename $param \
--save_dir $exp/shape \
--input_shape_dict="${input_shape_dict}"
fi
input_file=$exp/static_ds2online_inputs.pickle
test -e $input_file
if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ];then
if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ];then
# to onnx
./local/tonnx.sh $dir $model $param $exp/model.onnx
@ -81,7 +50,7 @@ if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ];then
fi
if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ] ;then
if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ] ;then
# ort graph optmize
./local/ort_opt.py --model_in $exp/model.onnx --opt_level 0 --model_out $exp/model.ort.opt.onnx
@ -89,7 +58,7 @@ if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ] ;then
fi
if [ ${stage} -le 5 ] && [ ${stop_stage} -ge 5 ];then
if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ];then
# convert opset_num to 11
./local/onnx_convert_opset.py --target-opset 11 --model-file $exp/model.ort.opt.onnx --save-model $exp/model.optset11.onnx

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