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# -*- coding: utf-8 -*-
import sys
import pprint
import copy
from collections import OrderedDict

class ComputeAPICall:
    def __init__(self, api, original):
        self.api = api
        self.original = original  # original logs

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#!/usr/bin/env python
from collections import namedtuple

from Xlib import X
import Xlib.display
from Xlib.ext.xtest import fake_input


class Screen(namedtuple('_Screen', ['x', 'y', 'w', 'h'])):
    @property

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from detectron2.layers import ShapeSpec
from detectron2.modeling import FPN, GeneralizedRCNN, ResNet, StandardROIHeads
from detectron2.modeling.anchor_generator import DefaultAnchorGenerator
from detectron2.modeling.backbone.fpn import LastLevelMaxPool
from detectron2.modeling.backbone.resnet import BasicStem, BottleneckBlock
from detectron2.modeling.box_regression import Box2BoxTransform
from detectron2.modeling.matcher import Matcher
from detectron2.modeling.poolers import ROIPooler
from detectron2.modeling.proposal_generator.rpn import RPN, StandardRPNHead
from detectron2.modeling.roi_heads import FastRCNNOutputLayers, MaskRCNNConvUpsampleHead

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#-*- coding: utf-8 -*-

import torch
from torch import nn

from fvcore.nn import FlopCountAnalysis, flop_count_table
from pypapi import events, papi_high as high


def main():

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#!/usr/bin/env python3
import glob
import os
import sys
import logging


METHODS = ["debug", "info", "warning", "warn", "error", "exception", "critical"]

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silly gist hack, why do we need you? :(

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from torch import nn
import torch

class ModuleWithLazySubmodules(nn.Module):
    def __init__(self, in_dim, middle_dim, submodules):
        super().__init__()
        self.first_layer = nn.Linear(in_dim, middle_dim)
        self.submodules = nn.Sequential(*submodules)

        self.forward(torch.rand(1, in_dim))