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import gc
import numpy as np
import sys
import time
import torch
from torch.autograd import Variable
import torchvision.models as models
import torch.backends.cudnn as cudnn
import torch.nn as nn
class SequentialSG(nn.Sequential):
def accGradParameters(self, input, gradOutput, scale=1):
currentGradOutput = gradOutput
currentModule = self.modules[-1]
for i in range(len(self.modules)-1, 0, -1):
previousModule = self.modules[i]
if currentModule.__class__.name == 'ErrorFeedback':
import torch
from torch.autograd import Function, Variable
class ErrorFeedbackFunction(Function):
# the forward pass consists in copying the input to the output
@staticmethod
def forward(ctx, input, feedback):
ctx.save_for_backward(input, feedback)
return input
from FunctionErrorFeedback import ErrorFeedbackFunction
from torch.autograd import Function, Variable
import torch
import torch.nn as nn
class EF(nn.Module):
def __init__(self, layer_dim, error_dim):
super(EF, self).__init__()
self.feedback = torch.Tensor(error_dim, layer_dim)
from __future__ import print_function, division
import math
import torch
from torch.autograd import Function, Variable
import torch.nn as nn
import torch.nn.functional as F
from ErrorFeedback import EF
from FunctionErrorFeedback import ErrorFeedbackFunction
from SequentialSG import SequentialSG
from torchvision.datasets import MNIST
import torchvision.transforms as transforms
import torch
import torch.legacy.nn as lnn
import torch.legacy.optim as loptim
train_dataset = MNIST(root='./data',
train=True,
transform=transforms.ToTensor(),
from time import time
import torch
import torch.nn as nn
import torch.nn.functional as F
class ConvNetV0(nn.Module):
def __init__(self):
super(ConvNetV0, self).__init__()
@iacolippo
iacolippo / ex.cpp
Created October 19, 2018 12:44
RuntimeError: variable impl does not have is_contiguous Pytorch C++ extension
#include <torch/extension.h>
#include <cmath>
#include <iostream>
#include <vector>
at::Tensor ex_forward(
at::Tensor input
) {
auto n_samples = input.size(0);
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@iacolippo
iacolippo / ray_deep_architect_ex1.py
Last active April 24, 2020 10:06
First example of using ray and deep_architect together - ray logging does not work
import os
import ray
from ray import tune
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.utils.data import DataLoader, TensorDataset