diff --git a/contrib/msame/README.md b/contrib/msame/README.md
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-# 模型推理工具
-
-## 1 介绍
-基于MindX SDK实现开发模型推理工具，用于测试om模型推理，本例为msame的python版本实现。   
-[msame-C++工具链接](https://gitee.com/ascend/tools/tree/master/msame)
-
-### 1.1 支持的产品   
-本项目以昇腾Atlas 500 A2/Atlas 200I DK A2为主要的硬件平台。   
-
-### 1.2 支持的版本   
-
-推荐系统为ubuntu 22.04。
-
-| 软件名称 | 版本   |
-| -------- | ------ |
-| python    | 3.9.2     | 
-| MindX SDK     |    5.0RC1    |
-| CANN | 310使用6.3.RC1<br>310B使用6.2.RC1 |
-
-
-
-
-### 1.3 适用场景   
-
-使用于单输入或多输入模型推理   
-
-
-### 1.4 代码目录结构与说明
-
-```
-.
-├── img
-│   ├── error1.jpg                            // msame-C++推理结果
-│   │── error2.jpg                            // 本例(msame-python)推理结果
-│   │── error3.jpg                            // 输入不一致报错截图
-│   │── process.jpg                           // 流程图
-├── set_env.sh                                // 需要设置的环境变量
-├── msame.py                                  // 模型推理工具代码
-├── README.md                                 // ReadMe
-```
-
-
-
-
-### 1.5 技术实现流程图
-
-![image-20220401173124980](./img/process.png)
-
-
-
-
-
-## 2 环境依赖
-
-软件依赖说明：
-
-| 依赖软件 | 版本   | 说明                   |
-| -------- | ------ | ---------------------- |
-| numpy    | 1.21.2 | 将数据保存为二进制文件 |
-
-在编译运行项目前，需要设置环境变量：
-
-```
-. /usr/local/Ascend/ascend-toolkit/set_env.sh #toolkit默认安装路径，根据实际安装路径修改
-. ${SDK_INSTALL_PATH}/mxVision/set_env.sh
-```
-
-## 3 依赖安装
-
-```
-pip install numpy == 1.21.2
-```
-
-## 4 准备工作
-
-[单输入模型yolov3样例]: 
-[多输入模型pointnet样例]: 
-
-注：多输入样例在输入时，多个输入用  ,  隔开。
-
-##  5 编译与运行
-示例步骤如下：   
-**步骤1** 设置环境变量
-
-**步骤2**  运行
-
-```
-python3.9 msame.py --model xxx --input xxx --output xxx  --loop xxx --outfmt xxx
-```
-在输出路径下成功输出预期的“.txt”或“.bin”则运行成功，否则报错。   
-参数说明：
-```
---input   
-功能说明：模型的输入路径 参数值：bin或npy文件路径与文件名 示例：--input dog.npy
---output   
-功能说明：模型的输出路径 参数值：bin或txt文件路径 示例：--output .
---model   
-功能说明：om模型的路径 参数值：模型路径与模型名称 示例：--model yolov3.om
---outfmt    
-功能说明：模型的输出格式 参数值：TXT 或 BIN 示例：--outfmt TXT
---loop   
-功能说明：执行推理的次数 默认为1 参数值：正整数 示例：--loop 2
---device   
-功能说明：执行代码的设备编号 参数值：自然数 示例：--device 1 
-```
-单输入模型：   
-以yolov3模型npy文件输入作为示例参考：
-
-```
-python3.9 msame.py  --model yolov3_tf_bs1_fp16.om --input dog.npy --output test --outfmt TXT
-```
-执行成功后，在test目录下生成yolov3_tf_bs1_fp16_0.txt，yolov3_tf_bs1_fp16_1.txt， yolov3_tf_bs1_fp16_2.txt   
-输出文件的个数与模型的输出有关。   
-
-多输入模型：   
-
-以pointcnn模型bin文件输入作为示例参考：    
-
-```
-python3.9 msame.py --model pointcnn_bs64.om --output test --outfmt BIN --input pointcnn.bin,pointcnn.bin
-```
-
-执行成功后，在test目录下生成pointcnn_bs64_0.bin     
-
-## 6 常见问题
-### 6.1 存储为txt格式时可能会出现第六位开始的误差，可以忽略此问题。  
- 执行msame-C++输出结果：   
-![image-20220401173124980](./img/error1.png)
- 执行本例（msame-python）输出结果：   
-![image-20220401173124980](./img/error2.png)
-### 6.2 模型需要的输入与提供的数据不一致   
-![image-20220401173124980](./img/error3.png)
-问题描述：   
-模型需要的输入shape与提供的数据shape不一致。   
-解决方案：   
-可在msame.py中自行输出m.input_shape查看模型需要的输入shape，m.input_dtype查看数据的shape。   
-自行编写脚本查看bin或npy文件的shape和dtype，与模型的shape和dtype对齐。
diff --git a/contrib/msame/img/error1.png b/contrib/msame/img/error1.png
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diff --git a/contrib/msame/img/error3.png b/contrib/msame/img/error3.png
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diff --git a/contrib/msame/img/process.png b/contrib/msame/img/process.png
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diff --git a/contrib/msame/msame.py b/contrib/msame/msame.py
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-# -*- coding: utf-8 -*- 
-# Copyright 2020 Huawei Technologies Co., Ltd
-#
-# 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.
-# ============================================================================
-import time
-import os
-import sys
-import stat
-import argparse
-import numpy as np
-import mindx.sdk as sdk
-
-
-def parse_args():
-    parser = argparse.ArgumentParser(description='msame-python')
-    parser.add_argument('--input', required=False, type=str, default='')
-    parser.add_argument('--model', required=True, type=str, help='model is necessary')
-    parser.add_argument('--output', required=True, type=str, help='check out your output path')
-    parser.add_argument('--outfmt', required=True, type=str, help='your output format must in "TXT"  or   "BIN"')
-    parser.add_argument('--loop', required=False, type=int, default=1)
-    parser.add_argument('--device', required=False, type=int, default=0)
-
-    my_args = parser.parse_args()
-    return my_args
-
-
-type_map = {}
-type_map['dtype.uint8'] = np.uint8
-type_map['dtype.float32'] = np.float32
-type_map['dtype.float16'] = np.float16
-type_map['dtype.int8'] = np.int8
-type_map['dtype.int32'] = np.int32
-type_map['dtype.int16'] = np.int16
-type_map['dtype.uint16'] = np.uint16
-type_map['dtype.uint32'] = np.uint32
-type_map['dtype.int64'] = np.int64
-type_map['dtype.uint64'] = np.uint64
-type_map['dtype.double'] = np.double
-
-args = parse_args()
-loop = args.loop
-_filepath = args.model
-_output = args.output
-_datatype = args.outfmt
-device_id = args.device
-
-
-def infer(saves):
-    if device_id < 0 or device_id >= 4:
-        print("device_id {0} is false ,please check".format(device_id))
-        sys.exit(0)
-    types_output = []
-    if not os.path.exists(_output):
-        os.makedirs(_output)
-    m = sdk.model(_filepath, device_id)
-    index = 0
-    for i in range(m.output_num):
-        types_output.append([])
-        types_output[index].append(str(m.output_dtype(i)))
-        index += 1
-    types_input = str(m.input_dtype(0))
-    multi = 1
-    f = []
-    if args.input != '':
-        mm = args.input.split(',')
-        for mk in mm:
-            if os.path.isdir(mk):
-                continue
-            elif os.path.isfile(mk):
-                continue
-            else:
-                print("Error: file doesn't exit")
-                sys.exit(0)
-    if m.input_num == 1:
-        if os.path.isdir(args.input):
-            isf = 0
-            for fi in os.listdir(args.input):
-                isf += 1
-                try:
-                    t = get_t(args.input+'/'+fi, m, type_map[types_input])
-                except KeyError:
-                    print("KeyError")
-                path = fi.split('.')[0]
-                one_time = t_save(path, m, t, saves, types_output)
-            if isf == 0:
-                print("It's an empty folder, please check your input")
-                sys.exit(0)
-        elif args.input == '':
-            try:
-                t = get_input_num(m, type_map[types_input])
-            except KeyError:
-                print("KeyError")
-            path = _filepath
-            one_time = t_save(path, m, t, saves, types_output)
-        else:
-            if  not os.path.isfile(args.input):
-                print("please check your file!")
-                sys.exit(0)
-            try:
-                t = get_t(args.input, m, type_map[types_input])
-            except KeyError:
-                print("KeyError")
-            if len(args.input.split('/')) == 1:
-                path = args.input
-            else:
-                path = args.input.split('/')[-1].split('.')[0]
-            one_time = t_save(path, m, t, saves, types_output)
-    else:
-        try:
-            if len(args.input.split(',')) > 1 and os.path.isdir(args.input.split(',')[0]):
-                index1 = 0
-                for fi in args.input.split(','):
-                    indexs = 0
-                    index1 += 1
-                    for fii in os.listdir(fi):
-                        indexs += 1
-                    if indexs == 0:
-                        print("It's an empty dir,please check your input!")
-                        sys.exit(0)
-                    t = get_multi_dir(m, type_map[types_input], fi)
-                    path = fi
-                    one_time = t_save(path, m, t, saves, types_output)
-            elif os.path.isdir(args.input):
-                index1 = 0
-                for fis in os.listdir(args.input):
-                    index1 += 1
-                if index1 == 0:
-                    print("It's an empty dir,please check your input!")
-                    sys.exit(0)
-                t = get_input_num(m, type_map[types_input])
-                path = _filepath
-                one_time = t_save(path, m, t, saves, types_output)
-            else:
-                t = get_input_num(m, type_map[types_input])
-                path = _filepath
-                one_time = t_save(path, m, t, saves, types_output)
-        except KeyError:
-            print("KeyError")
-    return one_time
-
-
-
-def get_multi_dir(m, input_type, dirs):
-    a_names = []
-    t = []
-    for di in os.listdir(dirs):
-        a_names.extend(get_files(dirs + '/' + di)) 
-    for ai in a_names:
-        if ai.split('.')[-1] == 'bin':
-            t.append(get_bins(ai, input_type))
-        else:
-            t.append(get_npy(ai, input_type))
-    return t
-
-
-def get_input_num(m, input_type):
-    inputsize = []
-    index = 0
-    for j in range(m.input_num):
-        inputsize.append(1)
-        for k in m.input_shape(j):
-            inputsize[index] *= k
-        index += 1
-    types_input = str(m.input_dtype(0))
-    files_name = []
-    tis = []
-    t = []
-    if args.input == '':
-        for i in inputsize:
-            try:
-                tas = []
-                tas.append(np.zeros(i, type_map[types_input]))
-                t.append(tas)
-            except KeyError:
-                print("KeyError")
-        tis.extend(t)
-    else:
-        binfile = args.input
-        all_names = []
-        if len(binfile.split(',')) > 1:
-            multi_bin = binfile.split(',')
-            for i in multi_bin:
-                files_name.append(i)
-                all_names.extend(get_files(i))
-                if len(all_names) == 0:
-                    print("It's an empty folder,please check your input")
-                    sys.exit(0)
-        else:
-            files_name.append(binfile)
-            all_names.extend(get_files(binfile))
-
-            if len(all_names[0]) == 0:
-                print("It's an empty folder, please check your input")
-                sys.exit(0)
-
-        for mul in all_names:
-            if mul.split('.')[1] == "bin":
-                t.append(get_bins(mul, input_type))
-            elif mul.split('.')[1] == "npy":
-                t.append(get_npy(mul, input_type))
-        tis = t
-    return tis
-
-
-def t_save(path, m, t, saves, types_output):
-    multi = 1
-    for p in m.input_shape(0):
-        multi = multi * p
-    if t[0][0].shape[0] != multi :
-        print("Error : Please check the input shape and input dtype")
-        sys.exit(0)
-    if m.input_num == 1:
-        tim = sdk.Tensor(t[0][0].reshape(m.input_shape(0)))
-        tim.to_device(device_id)
-    else:
-        if len(t) != m.input_num:
-            print("Error : Please check the input shape and input dtype")
-            sys.exit(0)
-        tim = []
-        idx = 0
-        for bs in t:
-            bs = sdk.Tensor(bs[0].reshape(m.input_shape(idx)))
-            bs.to_device(device_id)
-            tim.append(bs)
-            idx += 1
-    last_time = time.time()
-    outputs = m.infer(tim)
-    now_time = time.time()
-    one_times = now_time-last_time
-    outputs[0].to_host()
-    nums, _shape = get_nums(outputs, types_output)
-    if saves:
-        print(_output)
-        save_files(path, outputs, _output, _datatype, nums, _shape, types_output)
-    return one_times
-
-
-def get_t(name, m, input_type):
-    ti = []
-    if name.split('.')[1] == 'bin':
-        ti.append(get_bins(name, input_type))
-    elif name.split('.')[1] == 'npy':
-        ti.append(get_npy(name, input_type))
-    return ti
-
-
-def get_bins(f, input_type):
-    files_bin = []
-    bins = []
-    if os.path.isdir(f):
-        for s in os.listdir(f):
-            files_bin.append(np.fromfile(f+"/"+s, dtype=input_type).flatten())
-    else:
-        files_bin.append(np.fromfile(f, dtype=input_type).flatten())
-    return files_bin
-
-
-def get_npy(f, input_type):
-    files_npy = []
-    bins = []
-    if os.path.isdir(f):
-        for s in os.listdir(f):
-            files_npy.append(np.load(f+"/"+s).flatten())
-    else:
-        files_npy.append(np.load(f).flatten())
-    return files_npy
-
-
-def get_files(binfile):
-    all_name = []
-    if os.path.isdir(binfile):
-        for s in os.listdir(binfile):
-            all_name.append(binfile + '/' + s)
-    elif os.path.isfile(binfile):
-        all_name.append(binfile)
-    return all_name
-
-
-def get_nums(outputs, types_output):
-    index = 0
-    num_list = []
-    shape = []
-    #get shape
-
-    for ij in outputs:
-        ij.to_host()
-        try:
-            num = np.array(ij).astype(type_map[types_output[index][0]])
-        except KeyError:
-            print("KeyError")
-        num = num.flatten()
-        try:
-            num.dtype = type_map[types_output[index][0]]
-        except KeyError:
-            print("KeyError")
-        shape.append(ij.shape[-1])
-        num_list.append(num)
-        index += 1
-    #to list
-    i_index = 0
-    nums = []
-    for i in num_list:
-        output_desc = len(i)
-        nums.append([])
-        for j in range(int(output_desc/shape[i_index])):
-            for k in range(j*shape[i_index], (j+1)*shape[i_index]):
-                nums[i_index].append(num_list[i_index][k])
-        i_index += 1
-    return (nums, shape)
-
-
-def save_files(_filepath, outputs, _output, _datatype, nums, _shape, types_output):
-    #TXT
-    my_time =  time.strftime("%Y%m%d%H%M%S", time.localtime( time.time() ))
-    if _datatype == 'TXT' or _datatype == 'txt':
-        i_index = 0
-        for ik in nums:
-            f = os.open(_output+'/'+_filepath.split('.')[0]+'_'+my_time+'_'+str(i_index)+".txt", 
-                    os.O_RDWR | os.O_APPEND | os.O_CREAT, stat.S_IRWXU)
-            os.chmod(_output+'/'+_filepath.split('.')[0]+'_'+my_time+'_'+str(i_index)+".txt", stat.S_IRWXU)
-            output_desc = len(ik)
-            for j in range(int(output_desc/_shape[i_index])):
-                for k in range(j*_shape[i_index], (j+1)*_shape[i_index]):
-                    os.write(f, str.encode(str(nums[i_index][k])+' '))
-                os.write(f, str.encode('\n'))
-            i_index += 1
-    else:
-    #BIN
-        i_index = 0
-        for i in outputs:
-            i.to_host()
-            num = np.array(i)
-            num = num.flatten()
-            num.tofile(_output+'/'+_filepath.split('.')[0]+'_'+my_time+'_'+str(i_index)+".bin")
-            i_index += 1
-    
-
-def get_array(files_bin, input_type):
-    new_files = []
-    #make new bin
-    a = len(files_bin)
-    for im in range(a):
-        if im == 0:
-            new_files.append(files_bin[0])
-            continue
-        else:
-            a = files_bin[im]
-            b = new_files[im-1]
-            new_files.append(np.concatenate((a, b), axis=0))
-    bins = np.array(new_files[-1]).astype(input_type)
-    return bins
-
-
-
-if  __name__ == '__main__':
-    TIMES = 0.0
-    TRANS = 1000
-    SUM = 0
-    SAVES = True
-    if loop <= 0:
-        print("please check your loop!")
-        sys.exit(0)
-    for mj in range(loop):
-        nowtimes = time.time()
-        TIMES = infer(SAVES)
-        SUM += TIMES
-        SAVES = False
-        print("loop {0} : Inference time: {1:f} ms".format(mj, TIMES*TRANS))
-    print("infer success!")
-    print("Inference average time: {0:f} ms".format(SUM/loop*TRANS))
-
-