bwasti

PyTorch now has an official TVM-based backend, [torch_tvm](https://github.com/pytorch/tvm).  Usage is simple:

```
import torch_tvm
torch_tvm.enable()
```

That's it!  PyTorch will then attempt to convert all operators it can to known Relay operators during its JIT compilation process.

### Background

bwasti

PyTorch now has an official TVM-based backend, torch_tvm. Usage is simple:

import torch_tvm
torch_tvm.enable()

That's it! PyTorch will then attempt to convert all operators it can to known Relay operators during its JIT compilation process.

Background

bwasti

Size 1
                       DictPtr : 335 usec
            std::unordered_map : 442 usec
std::unordered_map + std::move : 381 usec
Size 2
                       DictPtr : 347 usec
            std::unordered_map : 553 usec
std::unordered_map + std::move : 459 usec
Size 4
                       DictPtr : 553 usec

bwasti

/*
How to run:

PT_DIR=$(python -c 'import os, torch; print(os.path.dirname(os.path.realpath(torch.__file__)))')
g++ -O3 test.cc -o test -I$PT_DIR/include -L$PT_DIR/lib -ltorch -lc10
for((i=1;i<=100000;i*=2)); do LD_LIBRARY_PATH="$PT_DIR/lib:$LD_LIBRARY_PATH" ./test $i; done

*/
#include <ATen/core/Dict.h>
#include <chrono>

bwasti

>>> import this
The Zen of Python, by Tim Peters

Beautiful is better than ugly.
Explicit is better than implicit.
Simple is better than complex.
Complex is better than complicated.
Flat is better than nested.
Sparse is better than dense.
Readability counts.

bwasti

bwasti

template<bool...> struct bool_pack;
template<bool... bs> 
using all_true = std::is_same<bool_pack<bs..., true>, bool_pack<true, bs...>>;

template<class R, class... Ts>
using are_all_constructible = all_true<std::is_constructible<R, Ts>::value...>;

template<typename... Ts>
struct ivalue_constructible_tuple {
  constexpr static bool value = are_all_constructible<c10::IValue, Ts...>::value;

bwasti

# split

for i in range(107):
  a[i] = b[i] + c[i]

for i0 in range(10):
  for i1 in range(10):
    a[i0 * 10 + i1] = b[i0 * 10 + i1] + c[i0 * 10 + i1]
for i0 in range(7):
  a[100 + i0] = b[100 + i0] + c[100 + i0]

bwasti

# usage:
#   $ python logo.py gme
#   https://s3-symbol-logo.tradingview.com/gamestop--big.svg
import requests
import sys

def get_symbol(symbol):
  url = "http://d.yimg.com/autoc.finance.yahoo.com/autoc?query={}&region=1&lang=en".format(symbol)
  result = requests.get(url).json()
  for x in result['ResultSet']['Result']:

bwasti

import builtins
import plotille
import numpy as np
import time


class Reprint:
  def __init__(self):
    self.h = 0
    self.s = ""