remove fluid tools for onnx export,test=doc

speechx/examples/ds2_ol/onnx/local/pd_infer_shape.py

-#!/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)

speechx/examples/ds2_ol/onnx/local/pd_prune_model.py

-#!/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)

speechx/examples/ds2_ol/onnx/local/prune.sh

-#!/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
\ No newline at end of file

speechx/examples/ds2_ol/onnx/run.sh

@@ -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