Build a high-frequency Sedna-based end-to-end use case in ModelBox fo… #368
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| FROM modelbox/modelbox-develop-tensorflow_2.6.0-cuda_11.2-ubuntu-x86_64:latest | |||
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A README file should be added here, to introduce how to use this example.
| WORKDIR /home/work | ||
| COPY ./lib /home/lib | ||
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| COPY examples/incremental_learning/helmet_detection/training/ /home/work/ |
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It should be declare in README that How to configure this part code to make it work with ModelBobx.
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| FROM modelbox/modelbox-develop-tensorflow_2.6.0-cuda_11.2-ubuntu-x86_64:latest | |||
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- What is the difference between this Dockerfile and another Dockerfile in examples directory? Are they duplicated?
- Another question not about this Dockerfile, is incremental_learning-modelbox directory and files under it are duplicated compared to files in incremental_learning/helmet-detection-modelbox directory?
| import warnings | ||
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| import cv2 | ||
| import numpy as np |
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Make imports more clean and in order.
| #include "gmock/gmock.h" | ||
| #include "gtest/gtest.h" | ||
| #include "modelbox/data_context.h" | ||
| #include "modelbox/session_context.h" |
| #include <modelbox/flow.h> | ||
| #include <iostream> | ||
| #include <string> | ||
| #include "test_config.h" |
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| #include "gtest/gtest.h" | ||
| #include "modelbox/base/log.h" | ||
| #include "modelbox/base/utils.h" |
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| # | |||
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src/flowunit/helm_infer/saved_model.pb is large file, and it should not be committed to this repository.
It is suggestted to put the file to GoogleDrive or elsewhere, and put the link here.
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| # | |||
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Why there are so many CMakeLists.txt files? Is it needed?
If it is, please give some explaination.
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| return modelbox.Status.StatusCode.STATUS_SUCCESS | ||
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| def close(self): |
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Please add comment for those functions like this, otherwise it is not readable.
For example, why this function directly returns the status while the function name "close" looks like an action, not a query.
| import numpy as np | ||
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| # from sedna.common.config import Context | ||
| # from sedna.common.file_ops import FileOps |
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Unused code should not be commited to repository. Please delete this part of code if it is really not used.
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So many empty lines is not suggestted, please follow the standard code style, for example google python code style, or you can use the IDE to format the code.
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| foreach(subdir ${SUBDIRS}) | ||
| add_subdirectory(${subdir}) | ||
| endforeach() |
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Please keep a new line at the end of the file.
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| /* | |||
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It is suggestted to add user guide to introduce what is the function of each file like this.
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| # | |||
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It is better not to directly copy thirdparty source file here, please try to make these as dependency.
You can consider to move them to Dockerfile.
| name: train-worker | ||
| imagePullPolicy: IfNotPresent | ||
| args: ["train.py"] | ||
| env: |
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Clear these variables if not used
| 2. Connect to the ModelBox orchestration service | ||
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| ```shell | ||
| modelbox-tool develop -q |
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modelbox-tool develop is unnecessary in demo test
| ### Prepare Model | ||
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| ``` | ||
| 链接：https://pan.baidu.com/s/1Gi5BJ_NQzqj66R8N5OXPzA |
| metadata: | ||
| name: incremental-dataset | ||
| spec: | ||
| url: "/data/train_data.txt" |
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I didn't find this file in the link you provided
| name: infer-worker | ||
| imagePullPolicy: IfNotPresent | ||
| args: ["test_mnist.py"] | ||
| env: |
| format = "graphviz" | ||
| graphconf = '''digraph mnist_sample { | ||
| node [shape=Mrecord] | ||
| httpserver_sync_receive[type=flowunit, flowunit=httpserver_sync_receive, device=cpu, time_out_ms=5000, endpoint="http://0.0.0.0:8190", max_requests=100] |
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You need to redirect the port to receive http requests
| node [shape=Mrecord] | ||
| httpserver_sync_receive[type=flowunit, flowunit=httpserver_sync_receive, device=cpu, time_out_ms=5000, endpoint="http://0.0.0.0:8190", max_requests=100] | ||
| mnist_preprocess[type=flowunit, flowunit=mnist_preprocess, device=cpu] | ||
| mnist_infer[type=flowunit, flowunit=mnist_infer, device=cpu, deviceid=0, batch_size=1] |
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Seems sedna.lib not imported
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/lgtm |
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Signed-off-by: Ymh13383894400 <1431605505@qq.com>
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/lgtm |
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/approve |
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[APPROVALNOTIFIER] This PR is APPROVED This pull-request has been approved by: jaypume The full list of commands accepted by this bot can be found here. The pull request process is described here
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