jzuern

import os
import pprint
import tensorflow as tf

if 'COLAB_TPU_ADDR' not in os.environ:
  print('ERROR: Not connected to a TPU runtime; please see the first cell in this notebook for instructions!')
else:
  tpu_address = 'grpc://' + os.environ['COLAB_TPU_ADDR']
  print ('TPU address is', tpu_address)

jzuern

def resnet_layer(inputs,
                 num_filters=16,
                 kernel_size=3,
                 strides=1,
                 activation='relu',
                 batch_normalization=True,
                 conv_first=True):
    """2D Convolution-Batch Normalization-Activation stack builder
    # Arguments
        inputs (tensor): input tensor from input image or previous layer

jzuern

import numpy as np
import matplotlib.pyplot as plt
import time

L = 1.0 # length of 1-D heat-conducting object
Nx = 100 # number of spatial grid points
T = 10.0 # maximum time
Nt = 1000 # number of time steps
a = 0.005 # material proberty alpha

jzuern

class KalmanFilter {
public:


    /**
    * Create a Kalman filter with the specified matrices.
    *   A - System dynamics matrix
    *   C - Output matrix
    *   Q - Process noise covariance
    *   R - Measurement noise covariance

jzuern

class Robot {
public:
    Robot(int x_start, int y_start, float orientation, int radius, SDL_Color col);
    ~Robot();
    
    void render(SDL_Renderer * ren);
    void move(const Uint8 * , Eigen::VectorXf & control);
    void moveForward(Eigen::VectorXf & control);
    void moveBackward(Eigen::VectorXf & control);
    void rotateLeft(Eigen::VectorXf & control);

jzuern

class Landmark {
public:
    Landmark(float x, float y, SDL_Color id);
    ~Landmark();
    Position pos;
    SDL_Color id;
    void render(SDL_Renderer * ren);
};

jzuern

import tensorflow as tf
import numpy as np

def int_shape(x):

  list = x.get_shape().as_list()
  return list

def _activation_summary(x):

jzuern

from tensorflow.python.platform import gfile
import tensorflow as tf
from tensorflow.contrib import tensorrt as trt

graph_filename ='resnetV150_frozen.pb'

f = gfile.FastGFile(graph_filename, 'rb')

# define graph def object
frozen_graph_def = tf.GraphDef()

jzuern

#!/usr/bin/env python3
# coding=utf-8

import collections
import sys
import itertools
import matplotlib.pyplot as plt
import matplotlib as mpl
import time
import datetime