update

Author: [email protected]

Diff for: autoencoder.py

@@ -73,6 +73,7 @@ def cost(self,  X):
         reconImage = self.decoder(robj1)[:,:,0].flatten()
         return T.sum((X-reconImage)*(X-reconImage))
 
+
         #Should be this when we have multiple inputs NxD
         #return T.mean(0.5* T.sum((X-reconImage)*(X-reconImage),axis=1))
 

Diff for: optimize.py

@@ -126,8 +126,7 @@ def optimize(self, train_data, lr):
             update_vars.append((var, var-lr*gvar))
 
         opt = theano.function([], cost, updates=update_vars, givens={X: train_data[0]})
-
-        get_grad = theano.function([] , grads[-2], givens={X:train_data[0]})
+        get_grad  = theano.function([], grads[-2], givens={X:train_data[0]})
         get_gradb = theano.function([], grads[-1], givens={X:train_data[0]})
         return opt, get_grad, get_gradb
 
@@ -167,7 +166,7 @@ def optimizeADAM(self, train_data, lr, \
         opt = theano.function([], cost, updates=updates,
                               givens={X: train_data[0]})
 
-        get_grad = theano.function([], grads[-2], givens={X:train_data[0]})
+        get_grad  = theano.function([], grads[-2], givens={X:train_data[0]})
         get_gradb = theano.function([], grads[-1], givens={X:train_data[0]})
         return opt, get_grad, get_gradb
 

Diff for: optimize_brightness.py

@@ -1,11 +1,15 @@
 import os
 import numpy as np
 from optimize import GDOptimizer
+from scene import *
+from shader import *
+from shape import *
+from transform import *
 import theano
 from util import *
 
 ### Hyper-parameters ###
-OptmizeFlag=False
+OptmizeFlag=True
 #-----------------------
 
 
@@ -52,3 +56,5 @@
         print 'Step', i+1
         print train()
         drawWithMarkers('output/%d.png' % (i+1,), render_fn())
+
+

Diff for: scene.py

@@ -21,8 +21,8 @@ def build(self, antialias_samples=4):
         image = T.alloc(0., self.camera.x_dims, self.camera.y_dims, 3)
 
         #Anti-Aliasing
-        sampleDist_x = np.random.random((self.camera.x_dims, self.camera.y_dims,antialias_samples))
-        sampleDist_y = np.random.random((self.camera.x_dims, self.camera.y_dims,antialias_samples))
+        sampleDist_x = np.asarray(np.random.random((self.camera.x_dims, self.camera.y_dims,antialias_samples)),dtype=theano.config.floatX)
+        sampleDist_y = np.asarray(np.random.random((self.camera.x_dims, self.camera.y_dims,antialias_samples)),dtype=theano.config.floatX)
 
         for sample in xrange(antialias_samples): #TODO USE SCAN
 
@@ -65,10 +65,11 @@ def make_rays(self, x_dims, y_dims, sampleDist_x=None, sampleDist_y=None):
 
         rays = np.dstack(np.meshgrid(np.linspace(0.5, -0.5, y_dims),
                          np.linspace(-0.5, 0.5, x_dims), indexing='ij'))
-        rays = np.dstack([rays, np.ones([y_dims, x_dims])])
+        rays = np.dstack([rays, np.ones([y_dims, x_dims], dtype='float32')])
         rays = np.divide(rays, np.linalg.norm(rays, axis=2).reshape(
                                         y_dims, x_dims, 1).repeat(3, 2))
 
+        rays = np.asarray(rays, dtype=theano.config.floatX)
         if sampleDist_x is not None: rays[:,:,0] = rays[:,:,0] + sampleDist_x / x_dims
         if sampleDist_y is not None: rays[:,:,1] = rays[:,:,1] + sampleDist_y / y_dims
         return RayField(T.as_tensor_variable([0., 0., 0.]), T.as_tensor_variable(rays))

Diff for: test_1ball.py

@@ -47,12 +47,16 @@ def scene(center1):
 
 center = get_center()
 print '...Initial center1 (%g,%g,%g)' % (center[0], center[1], center[2])
+print recon.sum()
+
+ggg =get_grad()
+gbb =get_gradb()
+import pdb; pdb.set_trace()
+
 n=0;
 while (n<3):
     n+=1
-    ggg =get_grad()
-    gbb =get_gradb()
-    import pdb; pdb.set_trace()
+    
     train_loss  = train_ae()
     center      = get_center()
     print '...Epoch %d Train loss %g, Center (%g, %g, %g)' \

Diff for: transform.py

@@ -55,7 +55,7 @@ def __call__(self, x):
 
 def identity():
     """Returns the identity transform"""
-    return Transform(np.eye(4, 4), np.eye(4, 4))
+    return Transform(np.asarray(np.eye(4, 4),dtype=theano.config.floatX) , np.asarray(np.eye(4, 4), dtype=theano.config.floatX))
 
 def translate(x):
     """Returns a transform to represent a translation"""

Diff for: util.py

@@ -13,12 +13,10 @@ def initialize_weight(n_vis, n_hid, W_name, numpy_rng, rng_dist):
         W = numpy_rng.uniform(low=-np.sqrt(6. / (n_vis + n_hid)),\
                 high=np.sqrt(6. / (n_vis + n_hid)),
                 size=(n_vis, n_hid)).astype(theano.config.floatX)
-        #if 'exp' in rng_dist :
-        #    W = np.exp(-W)
     elif rng_dist == 'normal':
         W = 0.01 * numpy_rng.normal(size=(n_vis, n_hid)).astype(theano.config.floatX)
 
-    return theano.shared(value = W, name=W_name)
+    return theano.shared(value = W, name=W_name, borrow=True)
 
 
 
@@ -52,3 +50,4 @@ def drawWithMarkers(fname, im):
 
 def draw(fname, im):
     imsave(fname, im)
+