Skip to content

Instantly share code, notes, and snippets.

cd cloud-provisioning
git pull
scripts/dm-swarm.sh
eval $(docker-machine env swarm-1)
docker node ls
@cbaziotis
cbaziotis / Attention.py
Last active March 28, 2023 11:50
Keras Layer that implements an Attention mechanism for temporal data. Supports Masking. Follows the work of Raffel et al. [https://arxiv.org/abs/1512.08756]
from keras import backend as K, initializers, regularizers, constraints
from keras.engine.topology import Layer
def dot_product(x, kernel):
"""
Wrapper for dot product operation, in order to be compatible with both
Theano and Tensorflow
Args:
@joelouismarino
joelouismarino / googlenet.py
Last active October 9, 2023 07:09
GoogLeNet in Keras
from __future__ import print_function
import imageio
from PIL import Image
import numpy as np
import keras
from keras.layers import Input, Dense, Conv2D, MaxPooling2D, AveragePooling2D, ZeroPadding2D, Dropout, Flatten, Concatenate, Reshape, Activation
from keras.models import Model
from keras.regularizers import l2
from keras.optimizers import SGD

Serving Flask under a subpath

Your Flask app object implements the __call__ method, which means it can be called like a regular function. When your WSGI container receives a HTTP request it calls your app with the environ dict and the start_response callable. WSGI is specified in PEP 0333. The two relevant environ variables are:

SCRIPT_NAME
The initial portion of the request URL's "path" that corresponds to the application object, so that the application knows its virtual "location". This may be an empty string, if the application corresponds to the "root" of the server.