Questions tagged [gradienttape]
147 questions
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Python Tensorflow - how does GradientTape operate and why can it give None as a result?
Abstract
I am trying to create a neural network with custom training. In my attempts I ended up with a
ValueError: No gradients provided for any variable error. While trying to figure it out, I've found out that the problem appears because…
Rabter
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Can tf.gradienttape() calculate gradient of other library's function
If I include inside the tf.GradientTape() some functions from other Python libraries, like `sklearn.decomposition.PCA.inverse_transform()', can TensorFlow calculate gradients from that function?
Specifically, can tf automatically differetiate…
David H. J.
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Setting shape of RaggedTensor with Known Shape
I'm working with RaggedTensors to manipulate a dense tensor. Something like this :
out_left = tf.ragged.boolean_mask(input, index)
index = tf.math.logical_not(index)
out_right = tf.ragged.boolean_mask(input, index)
…
Liam F-A
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sampling within GradientTape
I am computing the different terms of the ELBO and its expectations to illustrate and get a better grasp of the reparametrization trick, as nicely explained here under undifferentiable expectations.
As a simplified example in this journey, I have a…
rramosp
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Gradient Tape returns 0 for all weights
I am trying to reverse the output of LRP as heatmap back to model's weights. I have decieded to minimize the loss of the between the relevence of the untrained model weights and the desired heatmap relevence score so in theory it should make the…
Hossam Tarek
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tf.batch_jacobian Unexpected Behavior
import tensorflow as tf
with tf.GradientTape() as g:
x = tf.constant([[1., 2.], [3., 4.]], dtype=tf.float32)
z = tf.constant([[5., 6., 3.], [7., 8., 4.]], dtype=tf.float32)
g.watch(x)
g.watch(z)
y1 = x * x
y2 = z * z
y =…
AMIT SINGH
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How to make predictions on new dataset with tensorflow's gradient tape
While I'm able to understand how to use model.fit(x_train, y_train), I can't figure out how to make predictions on new data using tensorflow's gradient tape. My github repository with runnable code (up to an error) can be found here. What is…
Relative0
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Tensorflow 2: Error computing gradients from a list of tf.Variables
What's wrong with the code below ?
vars = [tf.Variable(0.0), tf.Variable(1.0)]
with tf.GradientTape() as g:
y = tf.reduce_mean(tf.concat(vars,axis=0))
grads = g.gradient(y, vars)
The above gives error : "ZeroDivisionError: integer division or…
anksh
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Is the number of uses of 'gradient' in GradientTape limited?
I'm trying to solve the following problems :
So, I tried by using tf.GradientTape 4 times. The following is my code :
import tensorflow as tf
import matplotlib.pyplot as plt
import numpy as np
import math
from scipy import io…
HJ_Kwon
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GradientTape for variable weighted sum of two Sequential models in TensorFlow
Suppose we want to minimize the following equation using gradient descent:
min f(alpha * v + (1-alpha)*w) with v and w the model weights and alpha the weight, between 0 and 1, for the sum resulting in the combined model v_bar or ū (here referred to…
user19087072
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1 answer
Negative gradients when calculating GradCAM heatmap
I have a Segmentation network model trained for 2 classes and am able to see accurate results.
But when using grad-cam for the heatmap, I am able to see good results for the last convolution layer
for both the classes but having issues when trying…
Lord Mord
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How can I calculate gradients of each element in a tensor using GradientTape?
I would like to calculate the gradient of each element in a tensor with respect to a list of watched tensors.
When I use GradientTape's gradient() on y directly, the resulting dy_dx has the dimension of my x. For example:
x = [ tf.constant(3.0),…
Morten Grum
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Tensorflow Gradient tape 'unknown value for unconnected gradients'
I'm trying to understand why im getting an error when using gradient tape to take the derivative of a function. Try to take the derivative of Power with respect to T, defined as:
import tensorflow as tf
import numpy as np
from scipy.fft…
J Crane
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In a GAN with custom training loop, how can I train the discriminator more times than the generator (such as in WGAN) in tensorflow
I'm working in a code based on the [Pix2Pix tensorflow tutorial][tutorial] and I'm trying to follow the Wasserstein GAN (WGAN) requirements: (a) weight clipping, (b) linear activation for the discriminator, (c) Wasserstein loss, and (d) training the…
fegemo
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tensorflow: Obtain RNN hidden states gradients with respect to input
My model consists of an Embedding layer and a SimpleRNN layer. I have obtained the hidden states at all steps with model.predict, and plotted them against the steps. I find that the hidden states converge to zero but I am not sure if I can infer…
siegfried
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