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import time | |
import gc | |
import psutil | |
import humanize | |
gc.collect() | |
time.sleep(2) | |
mem_before = psutil.virtual_memory()[3] |
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import itertools | |
from scipy import signal | |
import pywt | |
import numpy as np | |
import matplotlib.pyplot as plt | |
from sklearn.decomposition import FastICA | |
# ############################################################################# |
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# Download the TensorFlow Serving Docker image and repo | |
docker pull tensorflow/serving | |
# Start TensorFlow Serving container and open the REST API port | |
docker run -t --rm -p 8501:8501 -v "/home/vaclav/PycharmProjects/the-algorithm-lab/tensorflow2/practice/deployment/my_model:/models/my_model" -e MODEL_NAME=my_model tensorflow/serving & | |
# Query the model using the predict API | |
curl -d '{"instances": [17.99000,20.57000,19.69000,11.42000,20.29000,12.45000,18.25000,13.71000,13.00000,12.46000,16.02000,15.78000,19.17000,15.85000,13.73000,14.54000,14.68000,16.13000,19.81000,13.54000,13.08000,9.50400,15.34000,21.16000,16.65000,17.14000,14.58000,18.61000,15.30000,17.57000]}' \ | |
-X POST http://localhost:8501/v1/models/my_model:predict |
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def svg_write(fig, center=True): | |
""" | |
Renders a matplotlib figure object to SVG and embedd it as base64. | |
Disable center to left-margin align like other objects. | |
Shamelessly taken from: | |
https://discuss.streamlit.io/t/display-svg/172 | |
""" | |
# Save to stringIO instead of file | |
imgdata = StringIO() |
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import json | |
import pickle | |
class Foo: | |
""" An old Foo.""" | |
def __init__(self, a, b): | |
self.a = a | |
self.b = b |
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FROM python:3.8-alpine | |
# Define global args | |
ARG FUNCTION_DIR="/home/app/" | |
RUN apk add --no-cache \ | |
libstdc++ | |
# Install aws-lambda-cpp build dependencies | |
RUN apk add --no-cache \ |
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from scipy.integrate import simpson | |
import matplotlib.pyplot as plt | |
import numpy as np | |
def almost_fourier_transform(g: np.ndarray, t: np.ndarray, f: float): | |
# approximate center of mass as a mean | |
t1 = np.min(t) | |
t2 = np.max(t) | |
scaling_factor = (1 / (t2 - t1)) |
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51 | |
27 68 | |
30 48 | |
43 67 | |
58 48 | |
58 27 | |
37 69 | |
38 46 | |
46 10 | |
61 33 |
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def rgb2hex(rgb): | |
return ''.join([format(val, '02X') for val in rgb]) |
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from ortools.sat.python import cp_model | |
class SolutionPrinter(cp_model.CpSolverSolutionCallback): | |
def __init__(self, variables): | |
super().__init__() | |
self.variables = variables | |
self.solutions = [] |
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