diff --git a/.DS_Store b/.DS_Store
index bf98a860ffe69b0ba098dbe9de9827de9120b288..933ebbfc1f6463b8a8eba24a631005079c6cb8d8 100644
Binary files a/.DS_Store and b/.DS_Store differ
diff --git a/autoaug/autoaugment_learners/AaLearner.py b/autoaug/autoaugment_learners/AaLearner.py
index 808108d3d54824e541acef154144a6b9f25ebba5..6bc2f68fbd8a36b6ae84de40a1762905e9b610dc 100644
--- a/autoaug/autoaugment_learners/AaLearner.py
+++ b/autoaug/autoaugment_learners/AaLearner.py
@@ -462,3 +462,22 @@ class AaLearner:
megapol += pol[0]
return megapol
+
+
+ def get_n_best_policies(self, number_policies=5):
+ """
+ returns the n best policies
+
+
+ Args:
+ number_policies (int): Number of (sub)policies to return
+
+ Returns:
+ list of best n policies
+ """
+
+ number_policies = max(number_policies, len(self.history))
+
+ inter_pol = sorted(self.history, key=lambda x: x[1], reverse = True)[:number_policies]
+
+ return inter_pol[n]
diff --git a/autoaug/autoaugment_learners/UcbLearner.py b/autoaug/autoaugment_learners/UcbLearner.py
index 7e3e707780bec802c254fe08aab563faacfb612c..d0b3cae7ab225d35f7b5dd988c228ec34967f23e 100644
--- a/autoaug/autoaugment_learners/UcbLearner.py
+++ b/autoaug/autoaugment_learners/UcbLearner.py
@@ -153,8 +153,7 @@ class UcbLearner(RsLearner):
train_dataset,
test_dataset,
child_network_architecture,
- iterations=15,
- print_every_epoch=False):
+ iterations=15,):
"""continue the UCB algorithm for ``iterations`` number of turns
"""
@@ -173,7 +172,6 @@ class UcbLearner(RsLearner):
train_dataset,
test_dataset,
logging=False,
- print_every_epoch=print_every_epoch
)
# update q_values (average accuracy)
self.avg_accs[this_policy_idx] = acc
@@ -188,7 +186,6 @@ class UcbLearner(RsLearner):
train_dataset,
test_dataset,
logging=False,
- print_every_epoch=print_every_epoch
)
# update q_values (average accuracy)
self.avg_accs[this_policy_idx] = (self.avg_accs[this_policy_idx]*self.cnts[this_policy_idx] + acc) / (self.cnts[this_policy_idx] + 1)
@@ -246,6 +243,30 @@ class UcbLearner(RsLearner):
return megapol
+
+ def get_n_best_policies(self, number_policies=5):
+ """
+ returns the n best policies
+
+
+ Args:
+ number_policies (int): Number of (sub)policies to return
+
+ Returns:
+ list of best n policies
+ """
+
+ temp_avg_accs = [x if x is not None else 0 for x in self.avg_accs]
+
+ temp_history = list(zip(self.policies, temp_avg_accs))
+
+ number_policies = max(number_policies, len(temp_history))
+
+ inter_pol = sorted(temp_history, key=lambda x: x[1], reverse = True)[:number_policies]
+
+ return inter_pol[n]
+
+
diff --git a/flask_mvp/auto_augmentation/progress.py b/flask_mvp/auto_augmentation/progress.py
index e72a5b753ceab943807238f999f736c7f9a0c262..cc08843c5adfad31f8aac59df25886d3a2186191 100644
--- a/flask_mvp/auto_augmentation/progress.py
+++ b/flask_mvp/auto_augmentation/progress.py
@@ -6,7 +6,7 @@ import torch
torch.manual_seed(0)
-import temp_util.wapp_util as wapp_util
+import react_backend.wapp_util as wapp_util
bp = Blueprint("progress", __name__)
diff --git a/flask_mvp/auto_augmentation/training.py b/flask_mvp/auto_augmentation/training.py
index be5c7254ca211e14096f077509d56e0d41a8eceb..4ac0c82c2aa961c9eac84916f8e824ea14d41c16 100644
--- a/flask_mvp/auto_augmentation/training.py
+++ b/flask_mvp/auto_augmentation/training.py
@@ -5,7 +5,7 @@ import torch
torch.manual_seed(0)
-import temp_util.wapp_util as wapp_util
+import react_backend.wapp_util as wapp_util
bp = Blueprint("training", __name__)
diff --git a/notebooks/UCB1_JC.ipynb b/notebooks/UCB1_JC.ipynb
index 97d4ee68d62418003d549bcafc213c1188853a7b..406b4f4ecfdcc6690dbad847e7a69ee442e15392 100644
--- a/notebooks/UCB1_JC.ipynb
+++ b/notebooks/UCB1_JC.ipynb
@@ -425,7 +425,7 @@
},
{
"data": {
- "image/png": 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\n",
+ "image/png": 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",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
diff --git a/react_app.py b/react_app.py
index 82fe9845a881d311cc531ce9a3446e7eb7beaffd..42c761fd04e2db99a78b67764bb942f228b929d2 100644
--- a/react_app.py
+++ b/react_app.py
@@ -1,15 +1,15 @@
from dataclasses import dataclass
from flask import Flask, request, current_app, send_file, send_from_directory, redirect, url_for, session
from flask_cors import CORS, cross_origin
-
import os
import zipfile
-
import torch
-from numpy import save, load
-# import temp_util.wapp_util as wapp_util
-import time
-
+from numpy import int0, save, load
+from react_backend.wapp_util import parse_users_learner_spec
+import pprint
+import matplotlib
+matplotlib.use('Agg')
+import matplotlib.pyplot as plt
import os
import sys
sys.path.insert(0, os.path.abspath('..'))
@@ -39,22 +39,22 @@ def get_form_data():
print('@@@ required user input:', 'ds', ds, 'IsLeNet:', IsLeNet, 'auto_aug_leanrer:',auto_aug_learner)
# advanced input
- if form_data['batch_size'] != 'undefined':
- batch_size = form_data['batch_size'] # size of batch the inner NN is trained with
+ if form_data['batch_size'] not in ['undefined', ""]:
+ batch_size = int(form_data['batch_size'] ) # size of batch the inner NN is trained with
else:
- batch_size = 1 # this is for demonstration purposes
- if form_data['learning_rate'] != 'undefined':
- learning_rate = form_data['learning_rate'] # fix learning rate
+ batch_size = 16 # this is for demonstration purposes
+ if form_data['learning_rate'] not in ['undefined', ""]:
+ learning_rate = float(form_data['learning_rate']) # fix learning rate
else:
- learning_rate = 10-1
- if form_data['toy_size'] != 'undefined':
- toy_size = form_data['toy_size'] # total propeortion of training and test set we use
+ learning_rate = 1e-2
+ if form_data['toy_size'] not in ['undefined', ""]:
+ toy_size = float(form_data['toy_size']) # total propeortion of training and test set we use
else:
- toy_size = 1 # this is for demonstration purposes
- if form_data['iterations'] != 'undefined':
- iterations = form_data['iterations'] # total iterations, should be more than the number of policies
+ toy_size = 0.01 # this is for demonstration purposes
+ if form_data['iterations'] not in ['undefined', ""]:
+ iterations = int(form_data['iterations']) # total iterations, should be more than the number of policies
else:
- iterations = 10
+ iterations = 2
exclude_method = form_data['select_action']
print('@@@ advanced search: batch_size:', batch_size, 'learning_rate:', learning_rate, 'toy_size:', toy_size, 'iterations:', iterations, 'exclude_method', exclude_method)
@@ -156,15 +156,54 @@ def training():
num_sub_policies = 5 # fix number of sub-policies in a policy
data = current_app.config.get('data')
- # fake training
- print('pretend it is training')
- time.sleep(1)
- print('epoch: 1')
- time.sleep(1)
- print('epoch: 2')
- time.sleep(1)
- print('epoch: 3')
- print('it has finished training')
+ # parse the settings given by the user to obtain tools we need
+ train_dataset, test_dataset, child_archi, agent = parse_users_learner_spec(
+ max_epochs=max_epochs,
+ early_stop_num=early_stop_num,
+ num_policies=num_policies,
+ num_sub_policies=num_sub_policies,
+ **data
+ )
+
+ # train the autoaugment learner for number of `iterations`
+ agent.learn(
+ train_dataset=train_dataset,
+ test_dataset=test_dataset,
+ child_network_architecture=child_archi,
+ iterations=data['iterations']
+ )
+
+ print('the history of all the policies the agent has tested:')
+ pprint.pprint(agent.history)
+
+ # get acc graph and best acc graph
+ acc_list = [acc for (policy,acc) in agent.history]
+ best_acc_list = []
+ best_til_now = 0
+ for acc in acc_list:
+ if acc>best_til_now:
+ best_til_now=acc
+ best_acc_list.append(best_til_now)
+
+ # plot both here
+ fig = plt.figure()
+ ax = fig.add_subplot(1, 1, 1)
+ ax.plot(acc_list)
+ ax.plot(best_acc_list)
+ ax.set_xlabel('Number of Iterations')
+ ax.set_ylabel('Accuracy')
+ ax.set_title('Auto-augmentation Learner Performance Curve')
+ with open("./react_frontend/src/pages/output.png", 'wb') as f:
+ fig.savefig(f)
+
+ print("best policies:")
+ best_policy = agent.get_mega_policy(number_policies=4)
+ print(best_policy)
+ with open("./react_backend/policy.txt", 'w') as f:
+ # save the best_policy in pretty_print string format
+ f.write(pprint.pformat(best_policy, indent=4))
+
+ print('')
return {'status': 'Training is done!'}
diff --git a/temp_util/parse_ds_cn_arch.py b/react_backend/parse_ds_cn_arch.py
similarity index 92%
rename from temp_util/parse_ds_cn_arch.py
rename to react_backend/parse_ds_cn_arch.py
index 8a167460e0ab7d3307043b109ec55622d4033c1a..b334bce2b7f67040c08348a0f292a699da3f9ce8 100644
--- a/temp_util/parse_ds_cn_arch.py
+++ b/react_backend/parse_ds_cn_arch.py
@@ -36,12 +36,15 @@ def parse_ds_cn_arch(ds, ds_name, IsLeNet):
len_train = int(0.8*len(dataset))
train_dataset, test_dataset = torch.utils.data.random_split(dataset, [len_train, len(dataset)-len_train])
- # check sizes of images
- img_height = len(train_dataset[0][0][0])
- img_width = len(train_dataset[0][0][0][0])
- img_channels = len(train_dataset[0][0])
-
+ my_image = train_dataset[0][0]
+ my_transform = torchvision.transforms.ToTensor()
+ my_image = my_transform(my_image)
+ # check sizes of images
+ img_height = len(my_image[0])
+ img_width = len(my_image[0][0])
+ img_channels = len(my_image)
+
# check output labels
if ds == 'Other':
num_labels = len(dataset.class_to_idx)
diff --git a/react_backend/policy.txt b/react_backend/policy.txt
index ba1f82e0664d8cca0732c7db753ac93c122986de..2ab6b8100a10216936864ffcbb9848817cfdcbad 100644
--- a/react_backend/policy.txt
+++ b/react_backend/policy.txt
@@ -1 +1,10 @@
-0.7018545454545454,0.6530636363636364,0.6565090909090909,0.7029727272727273,0.6615000000000001,0.6610181818181818,0.6333545454545454,0.6617909090909091,0.6584636363636364,0.6933909090909091
\ No newline at end of file
+[ (('Brightness', 0.4, 4), ('Color', 0.0, 8)),
+ (('Posterize', 0.1, 0), ('Rotate', 0.3, 3)),
+ (('Equalize', 0.8, None), ('TranslateX', 0.7, 4)),
+ (('Equalize', 0.1, None), ('Posterize', 0.4, 1)),
+ (('AutoContrast', 0.3, None), ('Solarize', 0.2, 3)),
+ (('Sharpness', 1.0, 9), ('ShearY', 0.9, 9)),
+ (('Posterize', 0.6, 0), ('Color', 1.0, 0)),
+ (('TranslateX', 0.9, 0), ('Solarize', 0.1, 2)),
+ (('Rotate', 1.0, 9), ('Equalize', 0.3, None)),
+ (('ShearX', 0.3, 5), ('TranslateX', 0.0, 7))]
\ No newline at end of file
diff --git a/temp_util/wapp_util.py b/react_backend/wapp_util.py
similarity index 95%
rename from temp_util/wapp_util.py
rename to react_backend/wapp_util.py
index a23a98266bf603f1997c16e6244c5d1aad7772ea..8b580bb3e998999c8b278def417f1e188db3b70f 100644
--- a/temp_util/wapp_util.py
+++ b/react_backend/wapp_util.py
@@ -26,7 +26,6 @@ def parse_users_learner_spec(
auto_aug_learner,
# search space settings
exclude_method,
- num_funcs,
num_policies,
num_sub_policies,
# child network settings
@@ -35,7 +34,9 @@ def parse_users_learner_spec(
early_stop_num,
iterations,
learning_rate,
- max_epochs
+ max_epochs,
+ # dummy variable which does nothing
+ network_name,
):
train_dataset, test_dataset, child_archi = parse_ds_cn_arch(
ds,
@@ -111,8 +112,4 @@ def parse_users_learner_spec(
early_stop_num=early_stop_num,
)
-
- agent.learn(train_dataset,
- test_dataset,
- child_network_architecture=child_archi,
- iterations=iterations)
\ No newline at end of file
+ return train_dataset, test_dataset, child_archi, agent
\ No newline at end of file
diff --git a/react_frontend/src/pages/Confirm.js b/react_frontend/src/pages/Confirm.js
index 2d6b0d9ded4ed42bdd97698ca0a7d486899fde04..5416d7c672c234356e50a748d62a5832389e380c 100644
--- a/react_frontend/src/pages/Confirm.js
+++ b/react_frontend/src/pages/Confirm.js
@@ -8,17 +8,21 @@ export default function Confirm() {
const [myData, setMyData] = useState([])
const [dataset, setDataset] = useState()
const [network, setNetwork] = useState()
+ const [yes, setYes] = useState()
- // console.log('already in confirm react')
+ console.log('already in confirm react')
useEffect(() => {
const res = fetch('/home').then(
response => response.json()
).then(data => {setMyData(data);
if (data.ds == 'Other'){setDataset(data.ds_name)} else {setDataset(data.ds)};
if (data.IsLeNet == 'Other'){setNetwork(data.network_name)} else {setNetwork(data.IsLeNet)};
+ setYes('hey');
+ console.log('setYes', yes);
});
}, []);
+
let navigate = useNavigate();
const onSubmit = async () => {
navigate('/progress', {replace:true});
@@ -27,7 +31,7 @@ export default function Confirm() {
return (
<div className="App" style={{padding:"60px"}}>
<Typography gutterBottom variant="h3" align="center" >
- Data Auto-Augmentation
+ Data Auto-Augmentation {yes}
</Typography>
<Grid>
<Card style={{ maxWidth: 900, padding: "10px 5px", margin: "0 auto" }}>
diff --git a/react_frontend/src/pages/Home.js b/react_frontend/src/pages/Home.js
index 9531538dabd911a6171d587e4b64bdb6e5435c35..e8c12f3c377f5597b31426b3a02c491e05cb0a09 100644
--- a/react_frontend/src/pages/Home.js
+++ b/react_frontend/src/pages/Home.js
@@ -27,7 +27,6 @@ const ExpandMore = styled((props) => {
export default function Home() {
const [selectAction, setSelectAction] = useState([]);
- const [validation, setValidation] = useState([]);
// for form submission
const {register, control, handleSubmit, setValue, watch, formState: { errors, dirtyFields}} = useForm();
@@ -66,31 +65,8 @@ export default function Home() {
response => response.json()
).then(data => {
if ('error' in data){navigate('/error', data)} else {navigate('/confirm', {replace:true})}
- });
-
- //
- ///////// testing
- // .then((response)=> {
- // responseClone = response.clone(); // 2
- // return response.json();
- // })
- // .then(function (data) {
- // console.log('data from flask', data)
- // }, function (rejectionReason) { // 3
- // console.log('Error parsing JSON from response:', rejectionReason, responseClone); // 4
- // responseClone.text() // 5
- // .then(function (bodyText) {
- // console.log('Received the following instead of valid JSON:', bodyText); // 6
- // });
- // });
-
+ });
};
-
-
- // body: JSON.stringify(data)
- // console.log('errors', errors);
- // console.log('handleSubmit', handleSubmit)
-
// handling action selection
const handleActionSelect = (value) => {
@@ -328,10 +304,10 @@ export default function Home() {
<TextField type="number" inputProps={{step: "0.000000001",min: 0}} {...register("learning_rate")} name="learning_rate" placeholder="Learning Rate" label="Learning Rate" variant="outlined" fullWidth />
</Grid>
<Grid xs={12} sm={6} item>
- <TextField type="number" InputProps={{step:"1", inputProps: { min: 0, max: 1} }} {...register("iterations")} name="iterations" placeholder="Number of Iterations" label="Iterations" variant="outlined" fullWidth />
+ <TextField type="number" InputProps={{step:"1", inputProps: { min: 0} }} {...register("iterations")} name="iterations" placeholder="Number of Iterations" label="Iterations" variant="outlined" fullWidth />
</Grid>
<Grid xs={12} sm={6} item>
- <TextField type="number" inputProps={{step: "0.01", min: 0, max: 1}} {...register("toy_size")} name="toy_size" placeholder="Dataset Proportion" label="Dataset Proportion" variant="outlined" fullWidth />
+ <TextField type="number" inputProps={{step: "0.0001", min: 0, max: 1}} {...register("toy_size")} name="toy_size" placeholder="Dataset Proportion" label="Dataset Proportion" variant="outlined" fullWidth />
</Grid>
<FormLabel variant="h8" align='centre'>
* Dataset Proportion defines the percentage of original dataset our auto-augment learner will use to find the
diff --git a/react_frontend/src/pages/Result.js b/react_frontend/src/pages/Result.js
index 70dec30c7784651f839bdf6e1b56f04c72946f8c..746998501b6d4714626056e9e252d958de187550 100644
--- a/react_frontend/src/pages/Result.js
+++ b/react_frontend/src/pages/Result.js
@@ -1,6 +1,6 @@
import React, { useState, useEffect } from "react";
import { Grid, List, ListItem, Avatar, ListItemAvatar, ListItemText, Card, CardContent, Typography, Button, CardMedia } from '@mui/material';
-import output from './pytest.png'
+import output from './output.png'
import {useNavigate, Route} from "react-router-dom";
import axios from 'axios'
import fileDownload from 'js-file-download'
@@ -28,10 +28,10 @@ export default function Result() {
Here are the results from our auto-augment agent:
</Typography>
<Grid style={{padding:"30px"}} container spacing={4} alignItems="center">
- <Grid xs={7} item>
+ <Grid xs={6} item>
<img src={output} alt='output' />
</Grid>
- <Grid xs={5} item>
+ <Grid xs={6} item>
<Typography>
write something here to explain the meaning of the graph to the user
</Typography>
@@ -41,6 +41,7 @@ export default function Result() {
<Typography gutterBottom variant='h6' align='center'>
You can download the augentation policy here
</Typography>
+
<Button
type="submit"
variant="contained"
@@ -50,9 +51,13 @@ export default function Result() {
>
Download
</Button>
- <Typography>
- Please follow our documentation to apply this policy to your dataset.
- </Typography>
+
+ <Grid style={{padding:'10px'}}>
+ <Typography>
+ Please follow our documentation to apply this policy to your dataset.
+ </Typography>
+ </Grid>
+
</CardContent>
</Card>
diff --git a/react_frontend/src/pages/output.png b/react_frontend/src/pages/output.png
new file mode 100644
index 0000000000000000000000000000000000000000..2578c96febcab65581394b498ab5f62130d0a7f7
Binary files /dev/null and b/react_frontend/src/pages/output.png differ
diff --git a/react_frontend/src/pages/pytest.png b/react_frontend/src/pages/pytest.png
deleted file mode 100644
index 272b44ed38c9107f19c99dc9a5ac38593493604f..0000000000000000000000000000000000000000
Binary files a/react_frontend/src/pages/pytest.png and /dev/null differ