I am trying to train a model to generate images, I have a dataset of over 17K of men posing. I have been training my model for a few hours now and Sadly all I am getting is this:
Also my d_loss=-9.79e+3 how is it Negative ?
here is my code:
# -*- coding: utf-8 -*-
"""BigGANModel.ipynb...
Sorry, I am posting it now:
"""
This file defines the core research contribution
"""
import matplotlib
matplotlib.use('Agg')
import math
import torch
from torch import nn
from models.encoders import psp_encoders
from models.stylegan2.model import Generator
from configs.paths_config import...
I want to fine-tune the Pixel2Style2Pixel model with my custom data set, but I keep getting an error when I'm trying to load in the pre-train weights. Here is my code :
# Load the pre-trained model
os.chdir("/content/pixel2style2pixel")
from models.psp import pSp
config = {
"lr": 0.0001...
I am working on a Pix2pix Gan but I small dataset size of about 250 Pairs of images. What are good ways in code to artificially increase my dataset size?
I am getting a very weird error when I am trying to Build an input pipeline with tf.data. I am combining my reference image and my drawing into a tuple. Then I added to that to list. This should work,
but now I am getting this weird error at this line:
train_dataset =...
So I am trying to do this tutorials but I want to use my own dataset. I am having problems "Build an input pipeline with tf.data."
My question is about their code:
def load_image_train(image_file):
input_image, real_image = load(image_file)
input_image, real_image =...
All,
So I got it to work today. Hackerrank has a Find the median test and I use that to check and it passed for all 3 test case.
Anyhow, I think if someone learns the Histogram sorting Algorithm ( I am not sure the name of this) beforehand, then yeah they could easily passed that...
I was trying to do what you said in your other post but it did not work:
here is my code :
public static int FindMedian(List<int> arr)
{
Dictionary<int, int> MedianDictionary = new Dictionary<int, int>();
int numberCounter = arr.Count;
for...
Step 4 has : Increment that record count in that bin and, if you need a record index, store the index in that bin as well.
I do not understand. I know that in counting sort you :
Modify the count array such that each element at each index stores the sum of previous counts.
Index: 0 1...
So I did that, it is called "the Brute Force solution". The interviewer did not care at all.
He asked me what the Time complexity was, I said O(N^2) and he immediately replied with something like that was inefficient and unfeasible, what is a better solution? He did not even let me code...
1) He wanted to know the value at the middle of the list if you were to sort them in Ascending order.
If the dataset size was even then you would take the two middles and add them together and Divided by 2.
2) The values were integers from range "1 to 1000 " being pulled from a massive...
I am sorry, but is that what I am doing? I feel like there of a lot of algorithms I am just finding out about because of this one Microsoft Interview. Is there like a list of the algorithms one needs to know for a FAANG interview? Also, did I just do that right ?
I had a Microsoft Technical interview this past Friday, the question I was asked was this : How do you find the middle value for a dataset that is too big to fit in RAM?
I was not able to figure this out during the interview, but I have been look in this all weekend and I read something online...