Category "tensorflow"

AttributeError: 'Model' object has no attribute '_distribution_strategy'

I'm trying to train a UNet, but for some reason I get the following error: Traceback (most recent call last): File "<ipython-input-54-b56497e81356>", l

'str' object has no attribute 'decode' for tensorflow in colab?

I'm a beginner of deeplearning.I copied the code with python3 in colab. Code is from the book called"Book - Practical Deep Learning for Cloud, Mobile & Edge

Sort Tensorflow HashTable by value

My Code : h_table = tf.lookup.StaticHashTable( initializer=tf.lookup.KeyValueTensorInitializer( keys=[0, 1, 2, 3, 4, 5], values=[12.3,

Apply Tensorflow tf.keras.initializers.GlorotNormal(seed=1) to tf.Variable

How to apply the initializer to the tf.Variable function? Am I on the right track? def initialize_parameters(): initializer

Reshape tensorflow tensors from feature columns into training samples

Currently my dataset looks like: feat_1 = tf.random.uniform( shape=[8000,1], minval=0, maxval=1, dtype=tf.dtypes.float32, seed=1123, nam

Keras ValueError: Dimensions must be equal - How to pass label-dependent values to custom loss function

I have a keras model with 5 outputs. My labels include 5 values to compare these to, but also 25 additional values representing a correlation matrix for the 5 v

Evaluate model result for multitask learning with keras

I designed a CNN for a multitask classification in keras, where I have one input and two different class of classes in output. I compiled the model in this way

ERROR : could not find a version that satisfies the requirement tensorflow

I'm using raspberry model 3B+ , I made a venv and then tried to install tensorflow but I get these 2 errors ERROR: Could not find a version that satisfies the r

Evaluate model result for multitask learning with keras

I designed a CNN for a multitask classification in keras, where I have one input and two different class of classes in output. I compiled the model in this way

Why is cuda-gdb much slower than gdb in executing the same program without breakpoints in CUDA kernels?

I am having trouble using cuda-gdb. My program starts from python and it loads a shared library containing tensorflow and cuda code. The command I used to start

model.fit in a for loop, for K-fold cross validation

I am trying to code a K-fold cross validation with LSTM architecture. But I got an this error (edit): Traceback (most recent call last): File "/Users/me/Deskt

Keras, TF: Do I have to label all images when adding an attribute to a mutilabel image classification model?

i have a dataset of images and built a strong image recognition model. now i want to add another label to my model. i am asking myself, if i have to label every

Repeated values in prediction with sequential model

The problem I got is with the result, I get the same value in the 'future' field in all the rows as follows. open high low close

Jupyter Notebook Kernel dies when importing tenserflow

I am using Macbook Air with M1 chip. When trying to import tensorflow in Jupyter notebook, the kernel dies and displays a prompt that "Kernel has died and will

Efficient pooling operation in Tensorflow : Custom pooling layer

I wish to create a custom pooling layer which can efficiently work on GPUs. For instance, I have following input tensor in = <tf.Tensor: shape=(4, 5), dtype=

Error "Numpy.ndarray size changed, may indicate binary incompatibility. Expected 88 from C header, got 80 from PyObject."

I got this error file while following this tutorial: https://www.youtube.com/watch?v=yqkISICHH-U So far I have created a training dataset to feed into Tensorflo

Is it possible to use a TensorFlow model created with 2.0 with a later version?

New to TensorFlow here - and subject says it all. Before I go down a rabbit hole of incompatible versions: Is it possible to use a TensorFlow model created with

I need help to use only 8 out of 10 classes from cifar 10. Normally it loads all 10 classes

I want to perform 8 class classification only and hence need to filter any 8 classes out of 10. Please help. Thank you! Code to load cifar 10 is below #Keras li

"No Operation named [input] in the Graph" when using in a java programm a model from hub.KerasLayer with python and tensorflow 2.1.0

I trained a mobilnet_v2 tensorflow model using tf 2.1.0 and hub.KerasLayer with python and exported it in pb format with tf.keras.models.save_model. I loaded it

How can I save the output of a convolution layer with and without a dilation rate as images

I want to save a image file to see about difference using convolution layer with dilation rate and without that. Of course I can search images about that, but I

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