cemoody

https://github.com/tensorboy/pytorch_Realtime_Multi-Person_Pose_Estimation

https://github.com/tensorboy/3d-pose-baseline

http://www.tvmlang.org/2017/10/06/nnvm-compiler-announcement.html

cemoody

from torch_trainer.trainer import Trainer
from torch_trainer.callbacks import rms_callback
from torch import nn
from torch.optim import Adam
import torch.nn.functional as F

import numpy as np
import pandas as pd

cemoody

from typing import get_type_hints


def cast(argname, value, hints):
    """ Only cast arguments if type hints are available for them.
    """
    if argname in hints:
        expected_type = hints[argname]
        if not issubclass(type(value), expected_type):
            # Will throw type error if argument cannot be cast

cemoody

def check_line_by_line(fn_result, fn_truth):
    logger.info(f"Checking line by line in {fn_result} and {fn_truth}")
    with open(fn_result, 'r') as results:
        res = results.readlines()
    with open(fn_truth, 'r') as truth:
        tru = truth.readlines()

    for i, (line_t, line_r) in enumerate(zip(tru, res)):
        features = line_t.split('\x01')

cemoody

def switch_modal_function(stub=None, use_modal=True, **kwargs):
    def wrapper(inner_func):
        if use_modal:
            assert stub is not None, "If using modal, please provide `stub`."
            return stub.function(**kwargs)(inner_func)
        else:
            return inner_func
    return wrapper

cemoody

import os
import pickle
import time
import glob
import joblib
import inspect
from loguru import logger


def persist_to_file():

cemoody

import multiprocessing
import queue
from loguru import logger

import pandas as pd


def chunks(df, chunk_size=1000):
    for i in range(0, len(df), chunk_size):
        yield df[i : i + chunk_size]

cemoody

apiVersion: v1
kind: Service
metadata:
  name: vespa
  labels:
    app: vespa
spec:
  selector:
    app: vespa
  type: NodePort

cemoody

✓ Initialized. View app at https://modal.com/apps/ap-lHATR9JHJ7S5eGXYHigc75
✓ Created objects.
├── 🔨 Created sample_fn.
├── 🔨 Mounted /Users/chris/code/search/gumbase/jobs/partition.py at /root
├── 🔨 Mounted /Users/chris/code/gumhouse/gumhouse at /root/gumhouse
├── 🔨 Created sample_job.
├── 🔨 Created fit_top_level_kmeans.
├── 🔨 Created scatter_by_centroids_single.
├── 🔨 Created scatter_by_centroids.
├── 🔨 Created gather_single.

cemoody

import os
import io
import json
import math
import time
import random
import numpy as np
import cachetools.func
import sqlite3
from loguru import logger