lapl | Cozy familiar scripting language written in C
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kandi X-RAY | lapl Summary
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QUESTION
I'm trying to load model weights from an hdf5 file to evaluate on my test set. When I try and load the weights, I get the following error:
"Unable to open object (file read failed: time = Sat Jan 9 18:02:20 2021\n, filename = '/content/drive/My Drive/Training Checkpoints/training_vgg16/Augmented/01-1.6986_preprocessed_unfrozen.hdf5', file descriptor = 203, errno = 5, error message = 'Input/output error', buf = 0x2d4ae840, total read size = 328, bytes this sub-read = 328, bytes actually read = 18446744073709551615, offset = 134448512)"
And the code I'm using is below:
...ANSWER
Answered 2021-Jan-10 at 17:48Turns out, although using load_weights
worked before, I was actually saving the entire model, and for some of the saved .hdf5 files it didn't work. Changing to using load_model
loads all of them correctly.
QUESTION
I'm unable to save a Keras model as I get the error mentioned in the title. I have been using tensorflow-gpu. My model consists of 4 inputs each is a ResNet50. When I use only a single input the call back below worked perfectly, but with the multi inputs I'm getting the following error:
...RuntimeError: Unable to create link (name already exists)
ANSWER
Answered 2020-Oct-01 at 13:10Try with CUDA 10.1. https://www.tensorflow.org/install/gpu says "TensorFlow supports CUDA® 10.1"
Something is wrong with
ModelCheckpoint
callback. Check checkpoint_path location Is it writeable? Also the reference says "if save_best_only=True, the latest best model according to the quantity monitored will not be overwritten." So you may want to delete the last saver model or provide new unique name in checkpoint_path every time you run model. Most likely it prevents overwriting the previous model and throws error.
QUESTION
I'm making a deep multimodal autoencoder which takes two inputs and produces a two outputs (which are the reconstructed inputs). The two inputs are with shape of (1000, 50) and (1000,60) respectively and the model has 3 hidden layers and aim to concatenate the two latent layer of input1 and input2.
here is the complete code of the model :
...ANSWER
Answered 2020-Aug-17 at 12:49I assume that X[0].shape[0]
and X1[0].shape[0]
are equal and since it is a dense layer it should be 4000. You have already managed to get to the training phase, but better I say that return value of Model.fit
is a history object of achieved losses during training. Your object named model
is then actually not a model.
To predict values with this trained model, you need to call Model.predict()
, in your case should look like:
QUESTION
When I save my model I get the following error:
...ANSWER
Answered 2020-Jun-03 at 16:50I think the problem is that both of your weight variables have internally the same name, which should not happen, you can give them names with the name
parameter to add_weight
:
QUESTION
I have a HDF5 file that for some reason got corrupted. I am trying to retrieve the portion of the file that is essentially fine. I can read all datasets from the groups that do not contain a corrupted field just fine. But I cannot read any of the not-corrupted datasets from a group that has also a corrupted dataset.
The funny thing is however that I can easily read those datasets using HDFView. I.e. I can open them, and find all numerical values. Using HDFView I can only not read the corrupted dataset.
My question is how can I exploit this, and retrieve as much data as I can?
When reading with h5py:
...ANSWER
Answered 2020-Apr-13 at 09:36I have found a neat way to recover all top-level groups which do not contain broken nodes. Can simply be extended to lower level groups by recursive calling.
QUESTION
I'm new to vanilla WebGL and trying to utilize framebuffers for post processing/advanced shaders. When I run my code I get the warning:
GL_INVALID_OPERATION : glDrawArrays: Source and destination textures of the draw are the same.
Here's my code so far. If anyone could point me to the right direction how to correctly utilize framebuffers to pass textures to the next pass. It's wrapped in a vue.js component but that shouldn't matter.
...ANSWER
Answered 2019-Oct-26 at 02:28The issue is exactly as stated in the error.
Source and destination textures of the draw are the same.
Looking at your code there is one shader, it references a texture, there is one texture, it's attached to the framebuffer AND it's bound to texture unit 0 the default. So, when you draw it's being used as both an input (u_texture
) and as the output (the current framebuffer). That's not allowed.
The simple solution is you need another texture. Bind that texture when drawing to the framebuffer.
The better solution is you need 2 different shader programs. One for when drawing to the framebuffer that uses no texture as input and another for drawing to the canvas . As it is you have one shader that branches on u_frame
. Remove that branch and separate things into 2 shader programs. The one that computes colors then u_frame < 300 and the one that use a texture. Use the computing one to draw to the framebuffer and the texture one to draw the framebuffer's texture to the canvas.
A few links that may or may not be helpful: drawing multiple things, render targets, image processing.
QUESTION
I want to copy some of the VGG16 layer weights layer by layer to another small network with alike layers, but I get an error that says:
...ANSWER
Answered 2019-Sep-10 at 17:39Take the VGG16
model directly:
QUESTION
I've met a real problem that I can't understand why it's happens. I'm too beginner to find the problem.
I've got this code :
...ANSWER
Answered 2018-Dec-10 at 12:50Since you are parsing a string, make sure that your dateFormatter can parse it with the used loale. F.e. "20/01/1990"
would not parse with an "en_US"
locale while "01/20/1990"
would not parse f.e. with an "es_ES"
locale.
To make sure, you could set the format yourself:
QUESTION
I am trying to create an HDF5 file with two datasets, 'data' and 'label'. When I tried to access the said file, however, I got an error as follows:
...ANSWER
Answered 2018-Sep-17 at 12:21I was unable to reproduce the error. Maybe you forgot to close the file or you change the content of your h5 during execution.
Also you can use print h5_file.items()
to check the content of your h5 file
Tested code:
QUESTION
I am new to python and programming in gerneral and am probably making horrible mistakes. Thank you for any help. I want to to initialize a member of my class by loading either some hdf5 data prepared by someone else or by loading my own hdf5 files. I tried this:
...ANSWER
Answered 2017-Oct-09 at 16:40You aren't allowed to create a dataset twice:
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