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mlp.py

+import numpy as np
+import tensorflow as tf
+import pandas as pd
+
+def sigm(x):
+  y = 1 / (1 + np.exp(-x))
+  return y
+
+def learn_once_mse(w1,b1,w2,b2,data,targests,learning_rate):
+
+  return w1,b1,w2,b2,loss
+
+def one_hot(labels):
+  oneHotMat = np.zeros((labels.size,labels.size),dtype=int)
+  for index,values in enumerate(labels):
+    oneHotMat[index,values] = 1
+
+  return oneHotMat
+
+def learn_once_cross_entropy():
+
+  return
+
+
+
+print(one_hot(np.array([1,2,0,4,3])))
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