weilinquan update

weilinquan · Dec 23, 2022 · 9994040 · 9994040
1 parent 0b71998
commit 9994040
Show file tree

Hide file tree

Showing 9 changed files with 17 additions and 3 deletions.
diff --git a/__pycache__/Tensor.cpython-39.pyc b/__pycache__/Tensor.cpython-39.pyc
diff --git a/nn/__pycache__/Linear.cpython-39.pyc b/nn/__pycache__/Linear.cpython-39.pyc
diff --git a/nn/__pycache__/Lossfunction.cpython-39.pyc b/nn/__pycache__/Lossfunction.cpython-39.pyc
diff --git a/nn/__pycache__/Module.cpython-39.pyc b/nn/__pycache__/Module.cpython-39.pyc
diff --git a/nn/__pycache__/Parameter.cpython-39.pyc b/nn/__pycache__/Parameter.cpython-39.pyc
diff --git a/nn/function/__pycache__/relu.cpython-39.pyc b/nn/function/__pycache__/relu.cpython-39.pyc
diff --git a/nn/optimizer/__pycache__/optimizer.cpython-39.pyc b/nn/optimizer/__pycache__/optimizer.cpython-39.pyc
diff --git a/nn/optimizer/optimizer.py b/nn/optimizer/optimizer.py
@@ -61,13 +61,13 @@ def __call__(self, params):
         self.n += 1
 
         for i in range(len(params['parameter'])):
-            self.m = self.beta1 * self.m + (1 - self.beta1) * params['gradient'][i]
-            self.v = self.beta2 * self.v + (1 - self.beta2) * np.square(params['gradient'][i])
+            self.m[i] = self.beta1 * self.m[i] + (1 - self.beta1) * params['gradient'][i]
+            self.v[i] = self.beta2 * self.v[i] + (1 - self.beta2) * np.square(params['gradient'][i])
 
             alpha = self.lr * np.sqrt(1 - np.power(self.beta2, self.n))
             alpha = alpha / (1 - np.power(self.beta1, self.n))
 
-            params['parameter'][i].data -= alpha * self.m / (np.sqrt(self.v) + self.eps)
+            params['parameter'][i].data -= alpha * self.m[i] / (np.sqrt(self.v[i]) + self.eps)
             """
             
         self.m = self.beta1 * self.m + (1 - self.beta1) * grads

diff --git a/tests/test_minist.py b/tests/test_minist.py
@@ -0,0 +1,14 @@
+import sys
+sys.path.append("..")
+from nn.function.relu import ReLu
+import nn
+from nn.Linear import Linear
+from Tensor import Tensor
+from nn.Lossfunction import MSELoss
+from nn.optimizer.optimizer import SGD
+import numpy
+from matplotlib import pyplot
+
+class model(nn.Module.Module):
+    def __init__(self):
+        self.conv1 =