A python comtrade load library accelerated by go

Last update: Dec 27, 2021

Related tags

Deep Learning comtrade-gopy

Overview

Comtrade-GRPC

Code for python used is mainly from dparrini/python-comtrade.

Just patch the code in BinaryDatReader.parse for parsing a little more efficiently.

1. Use `comtrade_grpc.py`

Basicly, the raw code in dparrini/python-comtrade is used like this:

from comtrade import Comtrade

rec = Comtrade()
rec.load(cfg_file,dat_file)

With Comtrade-GPRC, you may write like this:

from comtrade import Comtrade

# Passing a grpc_endpoint param will lead to using of parse() func in go with grpc

# 0ms

rec = comtrade_grpc.Comtrade(grpc_endpoint='localhost:50051')
rec.load(cfg_file,dat_file)

# 497.397ms

rec = comtrade_grpc.Comtrade()
rec.load(cfg_file,dat_file)

# 5809.528ms

2. Start grpc server

$cd comtrade_grpc_server_go
$go mod tidy
$go run .

server listening at [::]:50051

3. Make a docker image

Just build the grpc-server.base.dockerfile

Owner

Bo

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A python comtrade load library accelerated by go

Related tags

Overview

Comtrade-GRPC

1. Use `comtrade_grpc.py`

2. Start grpc server

3. Make a docker image

Owner

Bo

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A python comtrade load library accelerated by go

Related tags

Overview

Comtrade-GRPC

1. Use comtrade_grpc.py

2. Start grpc server

3. Make a docker image

Owner

Bo

Some tentative models that incorporate label propagation to graph neural networks for graph representation learning in nodes, links or graphs.

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Official PyTorch code for Mutual Affine Network for Spatially Variant Kernel Estimation in Blind Image Super-Resolution (MANet, ICCV2021)

PyTorch implementation of: Michieli U. and Zanuttigh P., "Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations", CVPR 2021.

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Moer Grounded Image Captioning by Distilling Image-Text Matching Model

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Experiments with differentiable stacks and queues in PyTorch

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Implementation of "StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis"

Codebase for Inducing Causal Structure for Interpretable Neural Networks

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This is the official pytorch implementation for our ICCV 2021 paper "TRAR: Routing the Attention Spans in Transformers for Visual Question Answering" on VQA Task

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HDMapNet: A Local Semantic Map Learning and Evaluation Framework

AirPose: Multi-View Fusion Network for Aerial 3D Human Pose and Shape Estimation

1. Use `comtrade_grpc.py`