gradient

I'm trying to implement an asynchronous parameter server, DistBelief style using TensorFlow. I found that minimize() is split into two functions, compute_gradients and apply_gradients, so my plan is to insert a network boundary between them. I have a question about how to evaluate all the gradients simultaneously and pull them out all at once. I understand that eval only evaluates the subgraph necessary, but it also only returns one tensor, not the chain of tensors required to compute that tensor. How can I do this more efficiently? I took the Deep MNIST example as a starting point: import

In an app, I draw a curved UIBezierPath an an MKOverlayPathView class to show flight routes. This is the code I am using: - (UIBezierPath *)pathForOverlayForMapRect:(MKMapRect)mapRect { ... bla bla bla ... UIBezierPath *path = [UIBezierPath bezierPath]; [path moveToPoint:s]; [path addQuadCurveToPoint:e controlPoint:cp1]; [path addLineToPoint:e2]; [path addQuadCurveToPoint:s2 controlPoint:cp2]; [path closePath]; return path; } - (void)drawMapRect:(MKMapRect)mapRect zoomScale:(MKZoomScale)zoomScale inContext:(CGContextRef)context{ self.mapRect = mapRect; CGContextSetRGBFillColor(context, 1.0, 1

I'm trying to put a css3 gradient over the top of a background image. Using the code below puts a background image on top of my gradient, but i'm trying to do it the other way around, so the gradient acts as a mask on top. url(images/darkwood.png), -webkit-gradient(linear, 0 0, 0 100%, from(#EEF), to(#000)) 300px 50px no-repeat, -webkit-gradient(linear, 0 0, 0 100%, from(#EFE), to(#000)) 0 0 no-repeat; background: url(images/darkwood.png), -moz-linear-gradient(#EEF, rgba(0,0,0,1)) 300px 50px no-repeat, -moz-linear-gradient(#EFE, rgba(0,0,0,1)) 0 0 no-repeat; Thanks for your help Yoann I have

In reference to these questions : Adding gradient effect to TextView in a ListView generates NPE and How to change color and font on ListView I would like to know how to go about setting the background of a TextView in a ListView with gradient effect? In one of the questions above, I ended up having the gradient effect added to the text in the TextView . And after skimming through the second question, it seems I can add only fixed background colors. How do I go about adding gradient to background? Should I make a CustomListAdapter ? You just need to create a drawable resource (see an example

I want to create a new colormap which interpolates between green and blue (or any other two colours for that matter). My goal is to get something like: First of all I am really not sure if this can be done using linear interpolation of blue and green. If it can, I'm not sure how to do so, I found some documentation on using a matplotlib method that interpolates specified RGB values here The real trouble is understanding how "cdict2" works below. For the example the documentation says: "Example: suppose you want red to increase from 0 to 1 over the bottom half, green to do the same over the

I have the following gradient: <?xml version="1.0" encoding="utf-8"?> <shape xmlns:android="http://schemas.android.com/apk/res/android"> <gradient android:startColor="#ECECEC" android:centerColor="#F6F6F4" android:endColor="#F8F8F6" android:angle="90" android:dither="true" /> </shape> I want this to be transparent because in my ListView I am setting this as my ListSelector: <ListView android:layout_width="fill_parent" android:layout_height="fill_parent" xmlns:android="http://schemas.android.com/apk/res/android" android:id="@+id/ARListView" android:background="@drawable/transparent_background"

I am reading through the documentation of PyTorch and found an example where they write gradients = torch.FloatTensor([0.1, 1.0, 0.0001]) y.backward(gradients) print(x.grad) where x was an initial variable, from which y was constructed (a 3-vector). The question is, what are the 0.1, 1.0 and 0.0001 arguments of the gradients tensor ? The documentation is not very clear on that. The original code I haven't found on PyTorch website anymore. gradients = torch.FloatTensor([0.1, 1.0, 0.0001]) y.backward(gradients) print(x.grad) The problem with the code above there is no function based on what to

I followed the official tutorial of the tensorflow website: https://www.tensorflow.org/extend/adding_an_op There is also described how to call the gradient of the example ZeroOut in the tutorial that I want to try in this short code snippet underneath. I have found the code here: https://github.com/MatteoRagni/tf.ZeroOut.gpu import numpy as np import tensorflow as tf from tensorflow.python.framework import ops from tensorflow.python.ops import array_ops from tensorflow.python.ops import sparse_ops zero_out_module = tf.load_op_library('./libzeroout.so') @ops.RegisterGradient("ZeroOut") def