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# -*- encoding:utf-8 -*-
"""
@作者：Mr.zhang
@文件名：Data_replication_equalization.py
@时间：20-6-03  上午10:54
@文档说明:
        1. 使用pandas包
        2. 对csv文件的数据做数据均衡
        3. 通过复制的方式均衡数据
"""

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FROM python:3.6.12-slim as builder
MAINTAINER zhanghao <zhanghao_3389@163.com>

RUN apt update \
    && apt install -y ffmpeg libsm6 libxext6

ENV EXTERNAL_PYPI_SERVER=https://mirrors.aliyun.com/pypi/simple/
ENV MIRROR=mirrors.aliyun.com
ENV PATH="/opt/venv/bin:$PATH"

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docker run -it -p 8501:8501 \
-v "$(pwd)/save_model:/models/docker_test" \
-e MODEL_NAME=docker_test tensorflow/serving

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docker run --runtime=nvidia -it -p 8501:8501 \
-v "$(pwd)/save_model:/models/docker_test" \
-e MODEL_NAME=docker_test tensorflow/serving:latest-gpu

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saved_model_cli show --dir saved_model/0 --tag_set serve --signature_def serving_default

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import keras
import os
import tensorflow as tf
from tensorflow.python.util import compat
from keras import backend as K

def export_savedmodel(model):
	'''
	传入keras model会自动保存为pb格式
	'''

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import tensorflow as tf

# The export path contains the name and the version of the model
tf.keras.backend.set_learning_phase(0)  # Ignore dropout at inference
model = tf.keras.models.load_model('./inception.h5')  # 需要加载的模型路径
export_path = '../my_image_classifier/1'  # 将要导出模型的路径

# Fetch the Keras session and save the model
# The signature definition is defined by the input and output tensors
# And stored with the default serving key

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docker run --rm -it --entrypoint bash nmtwizard/opennmt-tf
docker run -v $PWD:/root/data --rm -it --entrypoint bash nmtwizard/opennmt-tf

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from concurrent.futures import ThreadPoolExecutor

def run(msg):
    pass

data = list()

with ThreadPoolExecutor() as executor:
    for _ in tqdm(executor.map(run, data), total=len(data)):
        pass

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import fnmatch, os


def find(pattern, path):
    result = []
    for root, dirs, files in os.walk(path):
        for name in files:
            if fnmatch.fnmatch(name, pattern):
                result.append(os.path.join(root, name))
    return result