Category : encoder

I am experimenting with auto encoders for deepfakes and have some code that looks like this. import tensorflow as tf from tensorflow.keras.layers import * from tensorflow.keras.models import * import pickle import numpy as np path = ‘youtube_stuff2/’ ot = pickle.load(open(path+’oi.pickle’,’rb’)) kt = pickle.load(open(path+’ki.pickle’,’rb’)) ot = ot/255.0 kt = kt/255.0 print(ot.shape) input() def MainEncoder(): inp = ..

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I am new to programming. I want to slowly write a program piece by piece that codes and decodes a sentence based on Chapman’s code. https://1drv.ms/u/s!Ah-IzfOzjlZ_ungI4M_yjxY9_kig?e=e6Qzir https://1drv.ms/u/s!Ah-IzfOzjlZ_unnDyEXct45dwu60?e=0oK49w The first piece is to assign the letters of a chosen keyword "CONSTANTINOPLE" their respective numbers. C O N S T A N T I N O P ..

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I am using flask and simplejson and have configured a custom json encoder to convert dicts to json. Custon Encoder: gen = [] class CustomJSONEncoder(json.JSONEncoder): def default(self, o): if isinstance(o, datetime): return o.strftime(‘%Y-%m-%d %H:%M:%S’) if isinstance(o, date): return o.strftime(‘%Y-%m-%d’) if isinstance(o, np.int64): return int(o) if isinstance(o, decimal.Decimal): a = (str(o) for o in [o]) gen.append(a) ..

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I’m using the library geohash from python to convert latitude and longitude coordinates into a unique value. Since I want to use XGboost, I had to transform those values (categorical) into numerical. For instance: sp36y965k7xbwe86j037r3yxb –> 638 when I predict a new value 638.14075, how can I convert it again into geohash? If I use ..

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To simplify the definition of the layers in the VAE and the usage of the nonlinearities I have to use torch.nn.Sequential in the below code. How can I change this definition for nonlinearities? class VAE(nn.Module): def __init__(self): super(VAE, self).__init__() self.fc0 = nn.Linear(2, K) self.fc1 = nn.Linear(K, K) self.fc21 = nn.Linear(K, K) self.fc22 = nn.Linear(K, K) ..

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