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torch2keras.py

+import torch
+from pytorch2keras.converter import pytorch_to_keras
+from torch.autograd import Variable
+
+
+
+input_tensor = torch.randn(1,3,224,224)
+input_var = Variable(torch.FloatTensor(input_tensor))
+
+filename = 'models/alexnet/alexnet-cifar10-edgetpu.pth.tar'
+torch_model = torch.load(filename,map_location='cpu')
+
+torch_model.eval()
+
+print(torch_model)
+
+keras_model = pytorch_to_keras(
+    torch_model,
+    input_var,
+    [input_var.shape[-3:]],
+    change_ordering=True,
+    name_policy="renumerate",
+    verbose=True
+)
+
+keras_model.summary()
+keras_model.save('modelo_prueba')