tomchristie

import httpx
from starlette.requests import Request
from starlette.responses import StreamingResponse


class Proxy:
    def __init__(self, hostname):
        self.hostname = hostname
        self.client = httpx.AsyncClient()

zmjjmz

 class TokenizeLookupLayer(keras.layers.Layer):                                          
     """                                                                                 
     Layer that encapsulates the following:                                              
     - Tokenizing sentences by space (or given delimiter)                                
     - Looking up the words with a given vocabulary list / table                         
     - Resetting the shape of the above to be batch_size x pad_len (using dark magic)    
     # Input Shape                                         
       2D string tensor with shape `(batch_size, 1)`      
     # Output Shape                                        
       2D int32 tensor with shape `(batch_size, pad_len)`

ilblackdragon

import logging

import numpy as np
import tensorflow as tf
from tensorflow.contrib import layers


GO_TOKEN = 0
END_TOKEN = 1
UNK_TOKEN = 2

jxson

Synopsis

At the top of the file there should be a short introduction and/ or overview that explains what the project is. This description should match descriptions added for package managers (Gemspec, package.json, etc.)

Code Example

Show what the library does as concisely as possible, developers should be able to figure out how your project solves their problem by looking at the code example. Make sure the API you are showing off is obvious, and that your code is short and concise.

Motivation