This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
User belongs to experiment group 'pythonaa' | |
User belongs to experiment group 'pythonJediLSP' | |
User belongs to experiment group 'pythonSendEntireLineToREPL' | |
User belongs to experiment group 'pythonNotDisplayLinterPrompt' | |
User belongs to experiment group 'pythonDiscoveryModule' | |
User belongs to experiment group 'pythonTensorboardExperiment' | |
User belongs to experiment group 'PythonPyTorchProfiler' | |
User belongs to experiment group 'ShowExtensionSurveyPrompt - control' | |
User belongs to experiment group 'CollectLSRequestTiming - control' | |
Info 2021-04-13 00:49:04: Display locator refreshing progress, Class name = g, completed in 1ms, has a falsy return value, , Return Value: undefined |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
class UpSample(nn.Module): | |
def __init__(self,feat_in,feat_out,out_shape=None,scale=2): | |
super().__init__() | |
self.conv = nn.Conv2d(feat_in,feat_out,kernel_size=(3,3),stride=1,padding=1) | |
self.out_shape,self.scale = out_shape,scale | |
def forward(self,x): | |
return self.conv( | |
nn.functional.interpolate( |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import torch | |
import torch.nn as nn | |
import torch.nn.functional as F | |
import torch.optim as optim | |
import torchaudio | |
from torch.autograd import Variable |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Collecting git+https://github.com/facebookresearch/pytorch3d.git | |
Cloning https://github.com/facebookresearch/pytorch3d.git to /tmp/pip-req-build-yyykcly2 | |
Running command git clone -q https://github.com/facebookresearch/pytorch3d.git /tmp/pip-req-build-yyykcly2 | |
Requirement already satisfied: torchvision>=0.4 in ./anaconda3/envs/work/lib/python3.8/site-packages (from pytorch3d==0.2.0) (0.6.0a0+82fd1c8) | |
Processing ./.cache/pip/wheels/a6/c2/56/ce21635637947b871a9b39e6cb33e3f11ec6e65acb8f901ccb/fvcore-0.1.1.post20200716-py3-none-any.whl | |
Requirement already satisfied: numpy in ./anaconda3/envs/work/lib/python3.8/site-packages (from torchvision>=0.4->pytorch3d==0.2.0) (1.19.1) | |
Requirement already satisfied: torch in ./anaconda3/envs/work/lib/python3.8/site-packages (from torchvision>=0.4->pytorch3d==0.2.0) (1.5.0) | |
Requirement already satisfied: pillow>=4.1.1 in ./anaconda3/envs/work/lib/python3.8/site-packages (from torchvision>=0.4->pytorch3d==0.2.0) (7.2.0) | |
Collecting tqdm | |
Using cached tqdm-4.48.2-py2.py3-no |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import numpy as np | |
import matplotlib.pyplot as plt | |
from sklearn.model_selection import train_test_split | |
from sklearn.utils import shuffle | |
import tensorflow as tf | |
from tensorflow import keras | |
from tensorflow.keras import backend as K | |
from tensorflow.keras.models import load_model, Sequential | |
from tensorflow.keras.layers import Dense | |
from tensorflow.keras.utils import Sequence |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
class ActorCritic(nn.Module): | |
def __init__(self, num_inputs, num_outputs, hidden_size, std=0.0): | |
super(ActorCritic, self).__init__() | |
self.critic = nn.Sequential( | |
nn.Linear(num_inputs, hidden_size), | |
nn.ReLU(), | |
nn.Linear(hidden_size, 1) | |
) | |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
from torch.utils.data import Dataset, DataLoader | |
import pandas as pd | |
import numpy as np | |
import cv2 | |
import matplotlib.pyplot as plt | |
import matplotlib.image as mpimg | |
from sklearn.model_selection import train_test_split | |
# from fastai.vision.models import resnet34 | |
# from fastai.vision.leaner import unet_learner | |
from fastai.vision import * |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
p1_0: [0.5404173787448456, 0.41291281118626466, 1.0, 0.0] | |
p2_0: [0.4595826212551544, 0.5870871888137354, 0.0, 1.0] | |
idx_0: ['3FLip X', '5FLip X', '7FLip X', '9FLip X'] | |
p1_1: [0.4595826212551544] | |
p2_1: [0.5404173787448456] | |
idx_1: ['4Flip Y'] | |
p1_2: [] | |
p2_2: [] | |
idx_2: [] | |
p1_3: [0.03264615290754886, 0.4595826212551544] |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
def act(self, data,t): #state | |
rate = self.get_exploration_rate(t) | |
if random.random() < rate: | |
options = self.model.predict(data) #state | |
options = np.squeeze(options) | |
action = random.randrange(self.action_size) | |
else: | |
options = self.model.predict(data) #state | |
options = np.squeeze(options) | |
action = options.argmax() |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Created temporary directory: /tmp/pip-ephem-wheel-cache-h28bm0z4 | |
Created temporary directory: /tmp/pip-req-tracker-a9vehy36 | |
Created requirements tracker '/tmp/pip-req-tracker-a9vehy36' | |
Created temporary directory: /tmp/pip-install-lla89gd9 | |
Processing /home/sarvagya/Desktop/RBC/box-convolutions | |
Created temporary directory: /tmp/pip-req-build-k9raxzlj | |
Added file:///home/sarvagya/Desktop/RBC/box-convolutions to build tracker '/tmp/pip-req-tracker-a9vehy36' | |
Running setup.py (path:/tmp/pip-req-build-k9raxzlj/setup.py) egg_info for package from file:///home/sarvagya/Desktop/RBC/box-convolutions | |
Running command python setup.py egg_info | |
running egg_info |
NewerOlder