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Commit b14ebf1f authored by Dawit Hailu's avatar Dawit Hailu
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updated work

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%% Cell type:code id: tags:
``` python
import dival.datasets.lodopab_dataset as lodopab
import matplotlib.pyplot as plt
dataset = lodopab.LoDoPaBDataset(impl='skimage')
sample_observ, sample_ground_truth = dataset.get_sample(1231)
plt.subplot(1, 2, 1)
plt.imshow(sample_observ)
plt.subplot(1, 2, 2)
plt.imshow(sample_ground_truth)
```
%% Output
<matplotlib.image.AxesImage at 0x7fdb6ec17610>
%% Cell type:code id: tags:
``` python
import torch
import torch.nn as nn
import torch.nn.functional as F
'''
input: 1000*513
output: 362*362
'''
class Net(nn.Module):
def __init__(self):
super(Net, self).__init__()
self.inputlayer = nn.Linear(1000*513, 10, True)
self.layer2 = nn.Linear(10,362*362, True)
def forward(self, inp): #inp is a Vector of inputsize
x = self.inputlayer(inp)
x = F.relu(x)
x = self.layer2(x)
return x
mynet = Net()
print(mynet)
```
%% Output
Net(
(inputlayer): Linear(in_features=513000, out_features=10, bias=True)
(layer2): Linear(in_features=10, out_features=131044, bias=True)
)
%% Cell type:code id: tags:
``` python
'''data=dataset.get_sample(1230)
print(torch.is_tensor(data))
data2=torch.as_tensor(data)
print(torch.is_tensor(data2))
'''
data=torch.rand(1000*513)
print(data)
print(mynet(data).size()) #131 044 = 362*362
print(dataset.get_sample(1)[0].type())
```
%% Output
tensor([0.7736, 0.7270, 0.2761, ..., 0.7862, 0.7033, 0.8556])
torch.Size([131044])
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-19-0d3c77efb4fa> in <module>
7 print(data)
8 print(mynet(data).size()) #131 044 = 362*362
----> 9 print(dataset.get_sample(1)[0].type())
AttributeError: 'DiscreteLpElement' object has no attribute 'type'
%% Cell type:code id: tags:
``` python
from torchvision import transforms
torch.from_numpy(dataset.get_sample(1230)[0])
print(data)
```
%% Output
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-23-5ef64af544ca> in <module>
1 from torchvision import transforms
2
----> 3 torch.from_numpy(dataset.get_sample(1230)[0])
4 print(data)
TypeError: expected np.ndarray (got DiscreteLpElement)
%% Cell type:code id: tags:
``` python
data=dataset.get_sample(1231)
print(torch.as_tensor(data[0][0]).size())
```
%% Output
torch.Size([513])
%% Cell type:code id: tags:
``` python
import numpy as np
Transformer = transforms.Compose([
transforms.ToTensor()
])
#Transformer(data[1][0])
torch.from_numpy(data[1])
```
%% Output
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-64-741f17b0fc5e> in <module>
4 ])
5 #Transformer(data[1][0])
----> 6 torch.from_numpy(data[1])
TypeError: expected np.ndarray (got DiscreteLpElement)
%% Cell type:code id: tags:
``` python
x,y = data=dataset.get_samples(slice(0,1,1))
print(torch.from_numpy(x).reshape(513*1000))
print(torch.from_numpy(x))
```
%% Output
tensor([-7.1809e-05, -4.1940e-05, -2.4069e-04, ..., 8.4311e-05,
2.3020e-04, 1.7529e-04])
tensor([[[-7.1809e-05, -4.1940e-05, -2.4069e-04, ..., -1.0458e-04,
1.8018e-05, 1.4489e-04],
[-1.1648e-04, 6.9213e-05, -1.7874e-04, ..., -1.1945e-04,
-6.0001e-06, 1.7225e-04],
[-2.8182e-04, -3.2965e-05, -2.0238e-04, ..., -5.0908e-05,
-9.5652e-05, -3.8949e-05],
...,
[-3.5957e-05, 6.0031e-06, -2.3186e-04, ..., 4.4923e-04,
-2.3983e-05, 1.3578e-04],
[ 3.9072e-05, -2.8475e-04, -7.4792e-05, ..., -4.0148e-04,
-4.4930e-05, -4.4930e-05],
[ 3.9072e-05, 2.0577e-04, 4.1504e-04, ..., 8.4311e-05,
2.3020e-04, 1.7529e-04]]])
%% Cell type:code id: tags:
``` python
mynet(torch.from_numpy(x).reshape(513*1000))
```
%% Output
tensor([-5.9897e-02, 2.2034e-01, 1.2248e-01, ..., 2.7456e-05,
2.8770e-01, -1.5429e-01], grad_fn=<AddBackward0>)
%% Cell type:code id: tags:
``` python
```
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