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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Aug 28 11:25:26 2023
@author: peter
"""
import keras
import tensorflow
import tqdm
class Batcher(keras.utils.Sequence):
def __init__(self,source,batch_size=32):
self.batches = None
self.source=source
self.batch_size=batch_size
self.on_epoch_end()
def __len__(self):
return len(self.batches)
def __getitem__(self, index):
return self.batches[index]
def on_epoch_end(self):
self.batches = []
n=0
X=[]
Y=[]
Z=[]
for (x,y,z) in tqdm.tqdm(self.source):
X.append(x)
Y.append(y)
Z.append(z)
n+=1
if n==self.batch_size:
self.batches.append((tensorflow.ragged.constant(X),
tensorflow.ragged.constant(Y),
tensorflow.ragged.constant(Z)))
n=0
X=[]
Y=[]
Z=[]
if n!=0:
self.batches.append((tensorflow.ragged.constant(X),
tensorflow.ragged.constant(Y),
tensorflow.ragged.constant(Z)))
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