sadimanna

import torch
import torch.nn as nn
from torchvision.models.utils import load_state_dict_from_url
from typing import Type, Any, Callable, Union, List, Dict, Optional, cast
from torch import Tensor
from collections import OrderedDict 

sadimanna

class new_model(nn.Module):
    def __init__(self, output_layer):
        super().__init__()
        self.output_layer = output_layer
        self.pretrained = models.resnet18(pretrained=True)
        self.children_list = []
        for n,c in self.pretrained.named_children():
            self.children_list.append(c)
            if n == self.output_layer:
                break

sadimanna

class new_model(nn.Module):
    def __init__(self,output_layer = None):
        super().__init__()
        self.pretrained = models.resnet18(pretrained=True)
        self.output_layer = output_layer
        self.layers = list(self.pretrained._modules.keys())
        self.layer_count = 0
        for l in self.layers:
            if l != self.output_layer:
                self.layer_count += 1

sadimanna

children_counter = 0
for n,c in rn18.named_children():
    print("Children Counter: ",children_counter," Layer Name: ",n,)
    children_counter+=1

sadimanna

from torchvision import models
rn18 = models.resnet18(pretrained=True)

sadimanna

nBytesTotal = nImg*nR*nC*1 #since each pixel data is 1 byte
images_array = np.asarray(st.unpack('>'+'B'*nBytesTotal,imagesfile.read(nBytesTotal))).reshape((nImg,nR,nC))

sadimanna

import sympy as sp

if __name__ == '__main__':
	stime = time.time()
	denominations = [1,2,5,10,20,50,100,200]

	maxpowers = [200//d for d in denominations]

	x = sp.symbols('x')

sadimanna

fig = plt.figure()
ax = Axes3D(fig)
ax.plot_wireframe(X, Y, datapts,color='goldenrod')

def animate(i):
    # "i" is updated for each frame i = 10 when frame = 10
    # for 360 frames, azim will take 360 values for a round display of the 3D plot
    ax.view_init(elev=10., azim=i)
    return fig,

sadimanna

from mpl_toolkits import mplot3d
from matplotlib import animation
from mpl_toolkits.mplot3d import Axes3D

X, Y = np.meshgrid(x, y)
fig = plt.figure()
ax = plt.axes(projection='3d')
ax.plot_wireframe(X, Y, datapts, color='black')
ax.view_init(elev=2., azim=30) #JUST FOR CLEARLY VIEWING THIS PLOT
ax.set_title('wireframe')

sadimanna

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1.inset_locator import zoomed_inset_axes
from mpl_toolkits.axes_grid1.inset_locator import mark_inset