napsternxg

from copy import deepcopy
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from scipy import sparse

from joblib import dump, load
import joblib
import time

napsternxg

mkdir food.com
cd food.com
wget https://www.food.com/sitemap.xml
for url in $(cat sitemap.xml | grep "<loc>https://www.food.com/sitemap-" | sed -n 's:.*<loc>\(.*\)</loc>.*:\1:p');
do echo "Download: $url"; 
done

for url in $(cat sitemap.xml | grep "<loc>https://www.food.com/sitemap-" | sed -n 's:.*<loc>\(.*\)</loc>.*:\1:p');
do wget "$url"; 
done

napsternxg

from pathlib import Path

import torch
from transformers import CLIPProcessor, CLIPTextModelWithProjection
from accelerate import Accelerator
from datasets import Dataset

import pandas as pd
import numpy as np

napsternxg

"""
pip install pypdf
"""

from pypdf import PdfWriter

def main(args):
  merger = PdfWriter()
  file_paths = args.input_files
  for pdf in file_paths:

napsternxg

Awesome Movies Compare

A Pen by Shubhanshu Mishra on CodePen.

License.

napsternxg

diff --git a/sentence_transformers/SentenceTransformer.py b/sentence_transformers/SentenceTransformer.py
index e44e573..ae4dea4 100644
--- a/sentence_transformers/SentenceTransformer.py
+++ b/sentence_transformers/SentenceTransformer.py
@@ -16,6 +16,7 @@ from torch.optim import Optimizer
 from torch.utils.data import DataLoader
 import torch.multiprocessing as mp
 from tqdm.autonotebook import trange
+from tqdm.autonotebook import tqdm
 import math

napsternxg

"""Spacy Embedding Transformer for Sklearn pipeline

Install spacy and floret

```bash
pip install spacy floret scikit-learn
```

First download the vectors from:
```bash

napsternxg

diff --git a/torchbiggraph/converters/importers.py b/torchbiggraph/converters/importers.py
index fa84bc6..765e9fa 100644
--- a/torchbiggraph/converters/importers.py
+++ b/torchbiggraph/converters/importers.py
@@ -28,6 +28,7 @@ from torchbiggraph.graph_storages import (
     RELATION_TYPE_STORAGES,
 )
 from torchbiggraph.types import UNPARTITIONED
+from tqdm import tqdm
 

napsternxg

# ! pip install celluloid
import numpy as np
import matplotlib.pyplot as plt
from celluloid import Camera

def plot_mat(A, evals=None, evecs=None, fig=None, ax=None):
  if ax is None:
    fig, ax = plt.subplots(1, 2, figsize=(8, 4))
  A = A / np.linalg.norm(A, axis=0, keepdims=True)
  ax[0].imshow(A)

napsternxg

from zipfile import ZipFile
from pathlib import Path
import pandas as pd
import numpy as np
import json

JOB_FILES = list(Path(".").glob("**/job_*.json.zip"))

JOB_ID_TO_OUTPUT_PART = {
    1873084: 12,