gigasquid

(ns gigasquid.seaborn
  (:require [libpython-clj.require :refer [require-python]]
            [libpython-clj.python :as py :refer [py. py.. py.-]]
            [gigasquid.plot :as plot]
            [clojure.data.csv :as csv]))

(require-python '[seaborn :as sns])
(require-python '[matplotlib.pyplot :as pyplot])
(require-python '[pandas :as pandas])

gigasquid

(ns gigasquid.gpt2
  (:require [libpython-clj.require :refer [require-python]]
            [libpython-clj.python :as py]))

;https://huggingface.co/transformers/quickstart.html - OpenAI GPT-2

(require-python '(transformers))
(require-python '(torch))

gigasquid

(ns gigasquid.mxnet
  (:require [libpython-clj.require :refer [require-python]]
            [libpython-clj.python :as py]
            [clojure.string :as string]))

(require-python '(mxnet mxnet.ndarray mxnet.module mxnet.io))
(require-python '(mxnet.test_utils))
(require-python '(mxnet.initializer))
(require-python '(mxnet.metric))
(require-python '(mxnet.symbol))

gigasquid

#!/usr/bin/env bash

sudo apt-get update || true
sudo apt-get install -y build-essential
sudo apt-get install -y software-properties-common
sudo apt-get install -y libatlas-base-dev 
sudo apt-get install -y libopenblas-dev
sudo apt-get install -y libcurl3
sudo add-apt-repository ppa:timsc/opencv-3.4
sudo apt-get update

gigasquid

[INFO] Scanning for projects...
[INFO] ------------------------------------------------------------------------
[INFO] Reactor Build Order:
[INFO] 
[INFO] MXNet Scala Package - Parent
[INFO] MXNet Scala Package - Initializer
[INFO] MXNet Scala Package - Initializer Native
[INFO] MXNet Scala Package - Macros
[INFO] MXNet Scala Package - Native
[INFO] MXNet Scala Package - Core

gigasquid

(ns dev.generator
  (:require [clojure.reflect :as r])
  (:import (org.apache.mxnet NDArray Symbol))
  (:gen-class))


(->> (:members (r/reflect (Symbol/api)))
     (filter #(clojure.string/includes? (:name %) "FullyConnected")))

;;=> output

gigasquid

(as-> (sym/variable "data") data
    (sym/fully-connected "fc1" {:data data :num-hidden 128})
    (sym/activation "relu1" {:data data :act-type "relu"})
    (sym/fully-connected "fc2" {:data data :num-hidden 64})
    (sym/activation "relu2" {:data data :act-type "relu"})
    (sym/fully-connected "fc3" {:data data :num-hidden 10})
    (sym/softmax-output "softmax" {:data data}))

gigasquid

 (predict "https://upload.wikimedia.org/wikipedia/commons/0/0c/American_Shorthair.jpg" true)

  ;; ({:prob 0.294283,   :label "n02123045 tabby, tabby cat"}
  ;;  {:prob 0.25543088, :label "n02122878 tabby, queen"}
  ;;  {:prob 0.18031825, :label "n02123159 tiger cat"}
  ;;  {:prob 0.06245274, :label "n01318894 pet"}
  ;;  {:prob 0.04261507, :label "n02120997 feline, felid"})

gigasquid

(defn predict [img-url show?]
  (let [mod (m/load-checkpoint {:prefix (str model-dir "/resnet-152") :epoch 0})
        labels (-> (slurp (str model-dir "/synset.txt"))
                   (string/split #"\n"))
        nd-img (get-image img-url show?)
        prob (-> mod
                 (m/bind {:for-training false 
                          :data-shapes [{:name "data" :shape [1 num-channels h w]}]})
                 (m/forward {:data [nd-img]})
                 (m/outputs)

gigasquid

(ns graal-test.core
  (:import (org.graalvm.polyglot Context)))

(def py-context (Context/create (into-array ["python"])))
(.eval py-context "python" "print('Hello polyglot world Python!');")
(.eval py-context "python" "
import time;
time.clock()
") ;=> #object[org.graalvm.polyglot.Value 0x4a6b3b70 "1.508202803249E9"]