Caffe to CoreML Colab Notes

from tensorflow.python.client import device_lib
device_lib.list_local_devices()

!cat /proc/meminfo

!cat /proc/cpuinfo

add question mark (?) see functions



# Which file to send?
file_name = "something.tar"

from googleapiclient.http import MediaFileUpload
from googleapiclient.discovery import build

auth.authenticate_user()
drive_service = build('drive', 'v3')

def save_file_to_drive(name, path):
  file_metadata = {'name': name, 'mimeType': 'application/octet-stream'}
  media = MediaFileUpload(path, mimetype='application/octet-stream', resumable=True)
  created = drive_service.files().create(body=file_metadata, media_body=media, fields='id').execute()
  
  return created

save_file_to_drive(file_name, file_name)

#tensorboard

# You can change the directory name
LOG_DIR = 'tb_logs'

!wget https://bin.equinox.io/c/4VmDzA7iaHb/ngrok-stable-linux-amd64.zip
!unzip ngrok-stable-linux-amd64.zip

import os
if not os.path.exists(LOG_DIR):
  os.makedirs(LOG_DIR)
  
get_ipython().system_raw(
    'tensorboard --logdir {} --host 0.0.0.0 --port 6006 &'
    .format(LOG_DIR))

get_ipython().system_raw('./ngrok http 6006 &')

!curl -s http://localhost:4040/api/tunnels | python3 -c \
    "import sys, json; print(json.load(sys.stdin)['tunnels'][0]['public_url'])"



CoreML 2.0 

# Supported models for swift 2.0 (CoreML 2.0)

# Supported frameworks

# Neural networks

# Feedforward, convolutional, recurrent

# Caffe v1

# Keras 1.2.2+

# Tree ensembles

# Random forests, boosted trees, decision trees

# scikit-learn 0.18

# XGBoost 0.6

# Support vector machines

# Scalar regression, multiclass classification

# scikit-learn 0.18

# LIBSVM 3.22

# Generalized linear models

# Linear regression, logistic regression

# scikit-learn 0.18

# Feature engineering

# Sparse vectorization, dense vectorization, categorical processing

# scikit-learn 0.18

# Pipeline models

# Sequentially chained models

# scikit-learn 0.18



# converting caffe to coreml
# setting is_bgr = True for caffe.convert() when generating your mlmodel

https://medium.com/deep-learning-turkey/google-colab-free-gpu-tutorial-e113627b9f5d