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#!/home/msfz751/.pyenv/shims/python3
# #!/usr/bin/env python
# change to location of your preferred virtual environment
# Source:
# https://itectec.com/ubuntu/ubuntu-taking-screenshot-of-a-specific-area-from-the-command-line/

import subprocess
import os
import sys

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# Digits recognition on PNG images. R code

1. Added utility functions
2. Introspection on dim=2. Extra layers on tensor
3. Converting code from Python to R

## Objectives
1. Read PNG images instead of MNIST standard dataset.
2. Save the model
3. Read an unseen digit as PNG file using the saved model

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# Digits recognition on PNG images. Python code

Source:  https://www.deeplearningwizard.com/deep_learning/practical_pytorch/pytorch_logistic_regression/

> This is a modified version of the original article.

1. added utility functions
2. Introspection on dim=2
3. Converting code to R
4. Read PNG images instead of MNIST standard dataset

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find_rsuite_root <- function(key = "PARAMETERS")  rprojroot::find_root(key)

source(file.path(find_rsuite_root(), 'R', 'set_env.R'), chdir = TRUE)
options(rsuite.cache_path = "~/.rsuite/cache")
options(rsuite.user_templ_path = "~/.rsuite/templates")

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find_rsuite_root <- function(key = "PARAMETERS")  rprojroot::find_root(key)
source(file.path(find_rsuite_root(), 'R', 'set_env.R'), chdir = TRUE)
.libPaths(c(normalizePath(sbox_path), normalizePath(lib_path), .libPaths()))

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# find_rsuite_root <- function(key = "PARAMETERS")  rprojroot::find_root(key)

ace_rsuite <- find_rsuite_root()
lib_path  <- file.path(ace_rsuite, "libs")
sbox_path <- file.path(ace_rsuite, "sbox")
if (!file.exists(lib_path)) {
  lib_path <- file.path(find_rsuite_root(), "deployment", "libs")
  sbox_path <- file.path(find_rsuite_root(), "deployment", "sbox")
}

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# One chunk - Linear Regression in Python

Source: https://medium.com/dsnet/linear-regression-with-pytorch-3dde91d60b50

Notebook: https://jvn.io/aakashns/e556978bda9343f3b30b3a9fd2a25012

```{r}
library(reticulate)
use_condaenv("pytorch37")
py_config()

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# One chunk - Linear Regression in R

Source: https://medium.com/dsnet/linear-regression-with-pytorch-3dde91d60b50

```{r}
# Force using local Python environment
if (.Platform$OS.type == "unix") {
  reticulate::use_python(python = file.path(script_path, "..", "conda", "bin",
                                            "python3"), require = TRUE)
} else if (.Platform$OS.type == "windows") {