C++ package management can be complicated.
Below are some key tools involved:
Make runs commands defined in a Makefile, for example, to build and install programs with the compiler and linker. For our purposes, we won't worry about what this looks like; you only need to understand its purpose in relation to CMake.
| /* Copyright 2015 The TensorFlow Authors. All Rights Reserved. | |
| Licensed under the Apache License, Version 2.0 (the "License"); | |
| you may not use this file except in compliance with the License. | |
| You may obtain a copy of the License at | |
| http://www.apache.org/licenses/LICENSE-2.0 | |
| Unless required by applicable law or agreed to in writing, software | |
| distributed under the License is distributed on an "AS IS" BASIS, | |
| WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| See the License for the specific language governing permissions and | |
| limitations under the License. |
| #!/usr/bin/env python | |
| """ | |
| Example of using Keras to implement a 1D convolutional neural network (CNN) for timeseries prediction. | |
| """ | |
| from __future__ import print_function, division | |
| import numpy as np | |
| from keras.layers import Convolution1D, Dense, MaxPooling1D, Flatten | |
| from keras.models import Sequential |
| '''Implementation and Demostration of Dynamic Time Warping | |
| Requires : python 2.7.x, Numpy 1.7.1, Matplotlib, 1.2.1''' | |
| from math import * | |
| import numpy as np | |
| import sys | |
| def DTW(A, B, window = sys.maxint, d = lambda x,y: abs(x-y)): | |
| # create the cost matrix | |
| A, B = np.array(A), np.array(B) |
| import os | |
| import struct | |
| import numpy as np | |
| """ | |
| MNist loading helper for Python 2.7. | |
| For Python 3.x, see https://gist.github.com/akesling/42393ccb868125071fdea77d98a0d2f0 | |
| Loosely inspired by http://abel.ee.ucla.edu/cvxopt/_downloads/mnist.py |