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View set_params.patch
diff --git a/nolearn/lasagne.py b/nolearn/lasagne.py
index 5c2c64c..86f2e7a 100644
--- a/nolearn/lasagne.py
+++ b/nolearn/lasagne.py
@@ -22,7 +22,21 @@ from theano import tensor as T
class _list(list):
- pass
+ def set_params(self, **params):
View Statsmodels Formula.ipynb
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View stalled_fits.py
import os
os.environ['PYLEARN2_DATA_PATH'] = '/home/ubuntu/data'
import numpy as np
import cv2
from pylearn2.config import yaml_parse
from pylearn2.datasets.mnist import MNIST
from pylearn2.datasets import preprocessing
View CuIFFT_issue.py
import os
os.environ['THEANO_FLAGS']="optimizer_including=conv_fft_valid:conv_fft_full"
from pylearn2.config import yaml_parse
from pylearn2.datasets.dense_design_matrix import DenseDesignMatrix
import numpy as np
train_str = """!obj:pylearn2.train.Train {
dataset: &train !import '__main__ .train_set',
View broken_convfft.py
import os
os.environ['THEANO_FLAGS']="optimizer_including=conv_fft_valid:conv_fft_full"
from pylearn2.config import yaml_parse
from pylearn2.datasets.dense_design_matrix import DenseDesignMatrix
import numpy as np
train_str = """!obj:pylearn2.train.Train {
dataset: &train !import '__main__ .train_set',
@cancan101
cancan101 / .numpy-site.cfg
Created Aug 14, 2014
numpy-site.cfg for building against openblas
View .numpy-site.cfg
[default]
library_dirs = /usr/local/lib
[atlas]
atlas_libs = openblas
library_dirs = /usr/local/lib
[lapack]
lapack_libs = openblas
library_dirs = /usr/local/lib
[openblas]
libraries = openblas
View Linear Interpolator Test Pub.ipynb
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@cancan101
cancan101 / MLP Hu.ipynb
Created Jul 21, 2014
Notebook Demonstrating Using MLPs to Classify State Map Images
View MLP Hu.ipynb
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@cancan101
cancan101 / Map Recognition.ipynb
Last active Aug 29, 2015
Notebook Demonstrating Technique to Identify US State Maps
View Map Recognition.ipynb
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@cancan101
cancan101 / get_state_v1.py
Last active Aug 29, 2015
Get Solid-Filled Image for State Map v1
View get_state_v1.py
def get_state_v1(state):
url = make_url(state)
IN = load_gif_url(url)
#Drop the text at the top
IN = IN[150:]
#Convert 3 color channels to 1
IN_bw = get_bw(IN)
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