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class NeuralNetwork(nn.Module):
    def __init__(self, numChannels, classes):
        # call the parent constructor
        super(NeuralNetwork, self).__init__()
        # initialize first set of CONV => RELU => POOL layers
        self.conv1 = nn.Conv2d(
            in_channels=numChannels, out_channels=20, kernel_size=(5, 5)
        )
        self.relu1 = nn.ReLU()
        self.maxpool1 = nn.MaxPool2d(kernel_size=(2, 2), stride=(2, 2))

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# Define model
class NeuralNetwork(nn.Module):
    def __init__(self, input_size, output_size, hidden_dim, n_layers):
        super(NeuralNetwork, self).__init__()

        self.hidden_dim = hidden_dim
        self.n_layers = n_layers

        self.rnn = nn.RNN(input_size, hidden_dim, n_layers, batch_first=True)   
        self.fc = nn.Linear(hidden_dim, output_size)

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import numpy as np
import pylab


def is_prime(n):
    status = True
    if n < 2:
        status = False
    else:
        for i in range(2,n):

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function mapStateToProps(state) {
  return {
    value: state.blackbox.value
  }
}

function mapDispatchToPops(dispatch) {
  return {
    setLHS: () => null, // TBD
    setRHS: () => null, // TBD

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const BB_UPDATE_STATE = '@@blackbox.updateState';

const bbUpdateState = () => ({
  type: BB_UPDATE_STATE
});

const serializeState = () => ({
  value: blackbox.getResult()
});

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// BlackBox API

// Constructor
blackbox = new BlackBox(element: Element)

// Methods
blackbox.setLeft(value: Number)
blackbox.setRight(value: Number)
blackbox.getResult(): Number

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[alias]
    ci = commit
    co = checkout
    st = status
    ss = status -sb
    ssb = submodule foreach 'git status -sb'
    br = branch
    bb = for-each-ref --sort=committerdate refs/heads/ --format='%(HEAD) %(color:yellow)%(refname:short)%(color:reset) - %(color:red)%(objectname:short)%(color:reset) - %(contents:subject) - %(authorname) (%(color:green)%(committerdate:relative)%(color:reset))'
    bn = !git for-each-ref --sort=committerdate refs/heads/ --format='%(HEAD) %(color:yellow)%(refname:short)%(color:reset) - %(color:red)%(objectname:short)%(color:reset) - %(authorname) (%(color:green)%(committerdate:relative)%(color:reset))' | tail -n 10
    clean-branches = !git branch -d $(git branch --merged develop | grep -v 'develop')

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In [14]: class Foo(Model):
    name = StringType()
    def __getattr__(self, attr):
        print '__getattr__', attr
        return self.__dict__['_initial'].get(attr, None)
    def validate(self, partial=False, strict=False, **kwargs):
        try:
            super().validate(partial=partial, strict=strict, **kwargs)
        except ModelValidationError as exc:
            print(exc.messages)

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from schematics.models import Model
from schematics.types import StringType, URLType
from schematics.transforms import import_loop
import warnings


class Foo(Model):

    name = StringType()

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import subprocess as sp
from binstar_build_client.worker.utils.timeout import Timeout
import time
import io
import os


class FakeBuildLog(object):
    """
    This class should actually post to anaconda-server