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Evaluate TFLite model

From: https://stackoverflow.com/questions/50443411/how-to-load-a-tflite-model-in-script

Handles the case of multiple inputs and outputs.

interpreter = tf.lite.Interpreter(model_path=mfile)
interpreter.allocate_tensors()

# get input and output layer handles
input_details = sorted(interpreter.get_input_details(), key=lambda x:x['name'])

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From: http://iwonderwhatjoeisworkingon.blogspot.com/2017/04/debugging-maya-using-visual-studio-code.html

1. Install ptvsd

pip install --user ptvsd

2. Start ptvsd server in Maya

import ptvsd
ptvsd.enable_attach(address=('0.0.0.0', 3000), redirect_output=True)

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CMake is a haneous piece of software, but somehow it has more popularity than others. These are my notes on inane BS I have to deal with time to time in CMake.

CMAKE_DEBUG_POSTFIX

Postfix like _Debug and _Release added to library names in windows.

Verbose Makefile

-DCMAKE_VERBOSE_MAKEFILE=true or make VERBOSE=1

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import zmq
import sys,os,time

#%%
port = '5563'
def server():
    context = zmq.Context()
    socket = context.socket(zmq.PUB)
    socket.bind('tcp://*:%s' % port)

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System Management

• WinDirStat: https://windirstat.net/
• ProcessExplorer: https://docs.microsoft.com/en-us/sysinternals/downloads/process-explorer
• Windows Assessment and Deployment Kit (ADK): https://docs.microsoft.com/en-us/windows-hardware/get-started/adk-install

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Preamble

import unreal_engine as ue
from unreal_engine.classes import PoseableMeshComponent, SkeletalMesh, Skeleton, SkeletalMeshComponent
from unreal_engine import FTransform, FVector, FRotator, FQuat, FSoftSkinVertex

Access object from editor

actor = ue.editor_get_selected_actors()[0]

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Clear tqdm error

tqdm._instances.clear()

Extend namedtuple with methods

ExperimentProps = namedtuple( 'ExperimentProps', config.keys() )
class Experiment(ExperimentProps):
    @property
    def root_path(self):
 return self._root_path

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Ouput Zero for divide by zero

length_err_pct = np.divide( pred_length, true_length, out=np.zeros_like(pred_length), where=true_length!=0)

Random subset of indices

sel = np.random.choice(testX.shape[0], samples, replace=False)

Save formatting

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Anaconda Configuration

conda create -n tensorflow tensorflow-gpu pip python=3.6
conda install ipython matplotlib cython mkl_random mkl mkl-devel swig

Install OpenAI Gym

Install from source: https://github.com/openai/gym

pip install -e .

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import numpy as np
import torch
from torch import nn
from itertools import count
import time

#%%
# make some data
N = 100