Update to Tensorflow 2#13

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Update to Tensorflow 2 #13

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f7e0d67
Manually updated code to tf2
bsolino Mar 23, 2021
97f57e4
Converted files to v2 automatically
bsolino Mar 23, 2021
b630360
Merge branch 'tf2' into tf2-auto
bsolino Mar 24, 2021
a1c6d37
Merge pull request #1 from bsolino/tf2-auto
bsolino Mar 24, 2021
b077a59
Keeping lines as in original
bsolino Mar 24, 2021
77f9ec8
Keeping lines as in original
bsolino Mar 24, 2021
19be5f5
Import keras maintaining its name
bsolino Mar 24, 2021
69a2c9e
Prettier way to import keras
bsolino Mar 24, 2021
7b0a439
Prettier way to import keras
bsolino Mar 24, 2021
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8 changes: 4 additions & 4 deletions GettingStarted.ipynb
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -32,11 +32,11 @@
],
"source": [
"import numpy as np\n",
"from keras.layers import Dense\n",
"from keras.models import Sequential\n",
"from tensorflow.keras.layers import Dense\n",
"from tensorflow.keras.models import Sequential\n",
"from IPython.display import SVG\n",
"from keras.utils import model_to_dot\n",
"from tensorflow import set_random_seed"
"from tensorflow.keras.utils import model_to_dot\n",
"from tensorflow.compat.v1.random import set_random_seed"
]
},
{
Expand Down
14 changes: 7 additions & 7 deletions KerasWeightsProcessing/convert_weights.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -6,12 +6,12 @@

import numpy as np
import math
import keras
import keras.backend as K
from keras.models import Sequential, Model
from keras.layers import Dense, Dropout, BatchNormalization
from keras.layers import Input, Activation
from keras import optimizers
from tensorflow import keras
import tensorflow.keras.backend as K
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import Dense, Dropout, BatchNormalization
from tensorflow.keras.layers import Input, Activation
from tensorflow.keras import optimizers

INPUT = ['input']
ACTIVATIONS = ['relu', 'linear', 'leakyrelu', 'sigmoid']
Expand DownExpand Up@@ -127,7 +127,7 @@ def txt_to_h5(weights_file_name, output_file_name=''):
# if not specified will use path of weights_file with h5 extension
output_file_name = weights_file_name.replace('.txt', '_converted.h5')

model.save(output_file_name)
model.save(output_file_name, save_format='h5')

def h5_to_txt(weights_file_name, output_file_name=''):
'''
Expand Down
12 changes: 6 additions & 6 deletions KerasWeightsProcessing/examples/mnist_keras.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -2,11 +2,11 @@
sys.path.append('../')
from convert_weights import h5_to_txt

import keras
from keras.datasets import mnist
from keras.models import Sequential, Model
from keras.layers import Dense, Input
from keras.optimizers import RMSprop
from tensorflow import keras
from tensorflow.keras.datasets import mnist
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import Dense, Input
from tensorflow.keras.optimizers import RMSprop

weights_file_name = 'mnist_example.h5'
txt_file_name = weights_file_name.replace('h5', 'txt')
Expand DownExpand Up@@ -50,6 +50,6 @@
verbose=1,
validation_data=(x_test, y_test))

model.save(weights_file_name)
model.save(weights_file_name, save_format='h5')

h5_to_txt(weights_file_name, txt_file_name)
12 changes: 6 additions & 6 deletions KerasWeightsProcessing/examples/multi_output_model.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -6,14 +6,14 @@
import tensorflow as tf

############## REPRODUCIBILITY ############
tf.set_random_seed(0)
tf.compat.v1.set_random_seed(0)
np.random.seed(0)
###########################################

from keras.models import load_model
from keras.models import Sequential, Model
from keras.utils.vis_utils import plot_model
from keras.layers import Dense, BatchNormalization, Input
from tensorflow.keras.models import load_model
from tensorflow.keras.models import Sequential, Model
from tensorflow.compat.v1.keras.utils import plot_model
from tensorflow.keras.layers import Dense, BatchNormalization, Input

input = x = Input((5,))
for i in range(3):
Expand All@@ -34,7 +34,7 @@
metrics=['accuracy']
)
# SAVE TO FILE FOR PARSING
multi_output_model.save('multi_output_model.h5')
multi_output_model.save('multi_output_model.h5', save_format='h5')

# CONVERT TO TXT
convert_weights.h5_to_txt('multi_output_model.h5', 'single_output_model.txt')
Expand Down
12 changes: 6 additions & 6 deletions KerasWeightsProcessing/examples/test_network.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
@@ -1,4 +1,4 @@
import keras
from tensorflow import keras
import argparse
import numpy as np
import subprocess
Expand All@@ -12,11 +12,11 @@
# set random seeds for reproducibility
np.random.seed(123)
import tensorflow as tf
tf.set_random_seed(123)
tf.compat.v1.set_random_seed(123)

from keras.models import Sequential, Model
from keras.layers import Dense, Input, LeakyReLU, Dropout, BatchNormalization
from keras.models import load_model
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import Dense, Input, LeakyReLU, Dropout, BatchNormalization
from tensorflow.keras.models import load_model

parser = argparse.ArgumentParser()
parser.add_argument('--train', action='store_true')
Expand DownExpand Up@@ -111,7 +111,7 @@
keras_predictions = model.predict(example_input)[0]

# save the weights
model.save(weights_file)
model.save(weights_file, save_format='h5')
# convert h5 file to txt
h5_to_txt(
weights_file_name=weights_file,
Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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Update to Tensorflow 2#13

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 Open

bsolino
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9
commits into

base:master
Choose a base branch

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Update to Tensorflow 2
#13
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f7e0d67

Manually updated code to tf2


bsolino Mar 23, 2021
97f57e4

Converted files to v2 automatically


bsolino Mar 23, 2021
b630360

Merge branch 'tf2' into tf2-auto


bsolino Mar 24, 2021
a1c6d37

Merge pull request #1 from bsolino/tf2-auto


bsolino Mar 24, 2021
b077a59

Keeping lines as in original


bsolino Mar 24, 2021
77f9ec8

Keeping lines as in original


bsolino Mar 24, 2021
19be5f5

Import keras maintaining its name


bsolino Mar 24, 2021
69a2c9e

Prettier way to import keras


bsolino Mar 24, 2021
7b0a439

Prettier way to import keras


bsolino Mar 24, 2021

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8 changes: 4 additions & 4 deletions
GettingStarted.ipynb

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -32,11 +32,11 @@
 ],
 "source": [
 "import numpy as np\n",
 "from keras.layers import Dense\n",
 "from keras.models import Sequential\n",
 "from tensorflow.keras.layers import Dense\n",
 "from tensorflow.keras.models import Sequential\n",
 "from IPython.display import SVG\n",
 "from keras.utils import model_to_dot\n",
 "from tensorflow import set_random_seed"
 "from tensorflow.keras.utils import model_to_dot\n",
 "from tensorflow.compat.v1.random import set_random_seed"
 ]
 },
 {
Expand Down

14 changes: 7 additions & 7 deletions
KerasWeightsProcessing/convert_weights.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -6,12 +6,12 @@

import numpy as np
import math
import keras
import keras.backend as K
from keras.models import Sequential, Model
from keras.layers import Dense, Dropout, BatchNormalization
from keras.layers import Input, Activation
from keras import optimizers
from tensorflow import keras
import tensorflow.keras.backend as K
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import Dense, Dropout, BatchNormalization
from tensorflow.keras.layers import Input, Activation
from tensorflow.keras import optimizers

INPUT = ['input']
ACTIVATIONS = ['relu', 'linear', 'leakyrelu', 'sigmoid']
Expand DownExpand Up@@ -127,7 +127,7 @@ def txt_to_h5(weights_file_name, output_file_name=''):
 # if not specified will use path of weights_file with h5 extension
 output_file_name = weights_file_name.replace('.txt', '_converted.h5')

 model.save(output_file_name)
 model.save(output_file_name, save_format='h5')

def h5_to_txt(weights_file_name, output_file_name=''):
 '''
Expand Down

12 changes: 6 additions & 6 deletions
KerasWeightsProcessing/examples/mnist_keras.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -2,11 +2,11 @@
sys.path.append('../')
from convert_weights import h5_to_txt

import keras
from keras.datasets import mnist
from keras.models import Sequential, Model
from keras.layers import Dense, Input
from keras.optimizers import RMSprop
from tensorflow import keras
from tensorflow.keras.datasets import mnist
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import Dense, Input
from tensorflow.keras.optimizers import RMSprop

weights_file_name = 'mnist_example.h5'
txt_file_name = weights_file_name.replace('h5', 'txt')
Expand DownExpand Up@@ -50,6 +50,6 @@
 verbose=1,
 validation_data=(x_test, y_test))

model.save(weights_file_name)
model.save(weights_file_name, save_format='h5')

h5_to_txt(weights_file_name, txt_file_name)

12 changes: 6 additions & 6 deletions
KerasWeightsProcessing/examples/multi_output_model.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -6,14 +6,14 @@
import tensorflow as tf

############## REPRODUCIBILITY ############
tf.set_random_seed(0)
tf.compat.v1.set_random_seed(0)
np.random.seed(0)
###########################################

from keras.models import load_model
from keras.models import Sequential, Model
from keras.utils.vis_utils import plot_model
from keras.layers import Dense, BatchNormalization, Input
from tensorflow.keras.models import load_model
from tensorflow.keras.models import Sequential, Model
from tensorflow.compat.v1.keras.utils import plot_model
from tensorflow.keras.layers import Dense, BatchNormalization, Input

input = x = Input((5,))
for i in range(3):
Expand All@@ -34,7 +34,7 @@
 metrics=['accuracy']
)
# SAVE TO FILE FOR PARSING
multi_output_model.save('multi_output_model.h5')
multi_output_model.save('multi_output_model.h5', save_format='h5')

# CONVERT TO TXT
convert_weights.h5_to_txt('multi_output_model.h5', 'single_output_model.txt')
Expand Down

12 changes: 6 additions & 6 deletions
KerasWeightsProcessing/examples/test_network.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
@@ -1,4 +1,4 @@
import keras
from tensorflow import keras
import argparse
import numpy as np
import subprocess
Expand All@@ -12,11 +12,11 @@
# set random seeds for reproducibility
np.random.seed(123)
import tensorflow as tf
tf.set_random_seed(123)
tf.compat.v1.set_random_seed(123)

from keras.models import Sequential, Model
from keras.layers import Dense, Input, LeakyReLU, Dropout, BatchNormalization
from keras.models import load_model
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import Dense, Input, LeakyReLU, Dropout, BatchNormalization
from tensorflow.keras.models import load_model

parser = argparse.ArgumentParser()
parser.add_argument('--train', action='store_true')
Expand DownExpand Up@@ -111,7 +111,7 @@
keras_predictions = model.predict(example_input)[0]

# save the weights
model.save(weights_file)
model.save(weights_file, save_format='h5')
# convert h5 file to txt
h5_to_txt(
 weights_file_name=weights_file,
Expand Down

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
Update to Tensorflow 2#13

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

 Sign up for GitHub

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privacy statement. We’ll occasionally send you account related emails.

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to your account

 Open

bsolino
wants to merge
9
commits into

base:master
Choose a base branch

from

 Open


Update to Tensorflow 2
#13
Show file tree
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 Changes from all commits
Commits

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9 commits


Select commit
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f7e0d67

Manually updated code to tf2


bsolino Mar 23, 2021
97f57e4

Converted files to v2 automatically


bsolino Mar 23, 2021
b630360

Merge branch 'tf2' into tf2-auto


bsolino Mar 24, 2021
a1c6d37

Merge pull request #1 from bsolino/tf2-auto


bsolino Mar 24, 2021
b077a59

Keeping lines as in original


bsolino Mar 24, 2021
77f9ec8

Keeping lines as in original


bsolino Mar 24, 2021
19be5f5

Import keras maintaining its name


bsolino Mar 24, 2021
69a2c9e

Prettier way to import keras


bsolino Mar 24, 2021
7b0a439

Prettier way to import keras


bsolino Mar 24, 2021

File filter

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8 changes: 4 additions & 4 deletions
GettingStarted.ipynb

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -32,11 +32,11 @@
 ],
 "source": [
 "import numpy as np\n",
 "from keras.layers import Dense\n",
 "from keras.models import Sequential\n",
 "from tensorflow.keras.layers import Dense\n",
 "from tensorflow.keras.models import Sequential\n",
 "from IPython.display import SVG\n",
 "from keras.utils import model_to_dot\n",
 "from tensorflow import set_random_seed"
 "from tensorflow.keras.utils import model_to_dot\n",
 "from tensorflow.compat.v1.random import set_random_seed"
 ]
 },
 {
Expand Down

14 changes: 7 additions & 7 deletions
KerasWeightsProcessing/convert_weights.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -6,12 +6,12 @@

import numpy as np
import math
import keras
import keras.backend as K
from keras.models import Sequential, Model
from keras.layers import Dense, Dropout, BatchNormalization
from keras.layers import Input, Activation
from keras import optimizers
from tensorflow import keras
import tensorflow.keras.backend as K
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import Dense, Dropout, BatchNormalization
from tensorflow.keras.layers import Input, Activation
from tensorflow.keras import optimizers

INPUT = ['input']
ACTIVATIONS = ['relu', 'linear', 'leakyrelu', 'sigmoid']
Expand DownExpand Up@@ -127,7 +127,7 @@ def txt_to_h5(weights_file_name, output_file_name=''):
 # if not specified will use path of weights_file with h5 extension
 output_file_name = weights_file_name.replace('.txt', '_converted.h5')

 model.save(output_file_name)
 model.save(output_file_name, save_format='h5')

def h5_to_txt(weights_file_name, output_file_name=''):
 '''
Expand Down

12 changes: 6 additions & 6 deletions
KerasWeightsProcessing/examples/mnist_keras.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -2,11 +2,11 @@
sys.path.append('../')
from convert_weights import h5_to_txt

import keras
from keras.datasets import mnist
from keras.models import Sequential, Model
from keras.layers import Dense, Input
from keras.optimizers import RMSprop
from tensorflow import keras
from tensorflow.keras.datasets import mnist
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import Dense, Input
from tensorflow.keras.optimizers import RMSprop

weights_file_name = 'mnist_example.h5'
txt_file_name = weights_file_name.replace('h5', 'txt')
Expand DownExpand Up@@ -50,6 +50,6 @@
 verbose=1,
 validation_data=(x_test, y_test))

model.save(weights_file_name)
model.save(weights_file_name, save_format='h5')

h5_to_txt(weights_file_name, txt_file_name)

12 changes: 6 additions & 6 deletions
KerasWeightsProcessing/examples/multi_output_model.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -6,14 +6,14 @@
import tensorflow as tf

############## REPRODUCIBILITY ############
tf.set_random_seed(0)
tf.compat.v1.set_random_seed(0)
np.random.seed(0)
###########################################

from keras.models import load_model
from keras.models import Sequential, Model
from keras.utils.vis_utils import plot_model
from keras.layers import Dense, BatchNormalization, Input
from tensorflow.keras.models import load_model
from tensorflow.keras.models import Sequential, Model
from tensorflow.compat.v1.keras.utils import plot_model
from tensorflow.keras.layers import Dense, BatchNormalization, Input

input = x = Input((5,))
for i in range(3):
Expand All@@ -34,7 +34,7 @@
 metrics=['accuracy']
)
# SAVE TO FILE FOR PARSING
multi_output_model.save('multi_output_model.h5')
multi_output_model.save('multi_output_model.h5', save_format='h5')

# CONVERT TO TXT
convert_weights.h5_to_txt('multi_output_model.h5', 'single_output_model.txt')
Expand Down

12 changes: 6 additions & 6 deletions
KerasWeightsProcessing/examples/test_network.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
@@ -1,4 +1,4 @@
import keras
from tensorflow import keras
import argparse
import numpy as np
import subprocess
Expand All@@ -12,11 +12,11 @@
# set random seeds for reproducibility
np.random.seed(123)
import tensorflow as tf
tf.set_random_seed(123)
tf.compat.v1.set_random_seed(123)

from keras.models import Sequential, Model
from keras.layers import Dense, Input, LeakyReLU, Dropout, BatchNormalization
from keras.models import load_model
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import Dense, Input, LeakyReLU, Dropout, BatchNormalization
from tensorflow.keras.models import load_model

parser = argparse.ArgumentParser()
parser.add_argument('--train', action='store_true')
Expand DownExpand Up@@ -111,7 +111,7 @@
keras_predictions = model.predict(example_input)[0]

# save the weights
model.save(weights_file)
model.save(weights_file, save_format='h5')
# convert h5 file to txt
h5_to_txt(
 weights_file_name=weights_file,
Expand Down

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
Update to Tensorflow 2#13

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Update to Tensorflow 2
#13
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f7e0d67

Manually updated code to tf2


bsolino Mar 23, 2021
97f57e4

Converted files to v2 automatically


bsolino Mar 23, 2021
b630360

Merge branch 'tf2' into tf2-auto


bsolino Mar 24, 2021
a1c6d37

Merge pull request #1 from bsolino/tf2-auto


bsolino Mar 24, 2021
b077a59

Keeping lines as in original


bsolino Mar 24, 2021
77f9ec8

Keeping lines as in original


bsolino Mar 24, 2021
19be5f5

Import keras maintaining its name


bsolino Mar 24, 2021
69a2c9e

Prettier way to import keras


bsolino Mar 24, 2021
7b0a439

Prettier way to import keras


bsolino Mar 24, 2021

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8 changes: 4 additions & 4 deletions
GettingStarted.ipynb

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -32,11 +32,11 @@
 ],
 "source": [
 "import numpy as np\n",
 "from keras.layers import Dense\n",
 "from keras.models import Sequential\n",
 "from tensorflow.keras.layers import Dense\n",
 "from tensorflow.keras.models import Sequential\n",
 "from IPython.display import SVG\n",
 "from keras.utils import model_to_dot\n",
 "from tensorflow import set_random_seed"
 "from tensorflow.keras.utils import model_to_dot\n",
 "from tensorflow.compat.v1.random import set_random_seed"
 ]
 },
 {
Expand Down

14 changes: 7 additions & 7 deletions
KerasWeightsProcessing/convert_weights.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -6,12 +6,12 @@

import numpy as np
import math
import keras
import keras.backend as K
from keras.models import Sequential, Model
from keras.layers import Dense, Dropout, BatchNormalization
from keras.layers import Input, Activation
from keras import optimizers
from tensorflow import keras
import tensorflow.keras.backend as K
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import Dense, Dropout, BatchNormalization
from tensorflow.keras.layers import Input, Activation
from tensorflow.keras import optimizers

INPUT = ['input']
ACTIVATIONS = ['relu', 'linear', 'leakyrelu', 'sigmoid']
Expand DownExpand Up@@ -127,7 +127,7 @@ def txt_to_h5(weights_file_name, output_file_name=''):
 # if not specified will use path of weights_file with h5 extension
 output_file_name = weights_file_name.replace('.txt', '_converted.h5')

 model.save(output_file_name)
 model.save(output_file_name, save_format='h5')

def h5_to_txt(weights_file_name, output_file_name=''):
 '''
Expand Down

12 changes: 6 additions & 6 deletions
KerasWeightsProcessing/examples/mnist_keras.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -2,11 +2,11 @@
sys.path.append('../')
from convert_weights import h5_to_txt

import keras
from keras.datasets import mnist
from keras.models import Sequential, Model
from keras.layers import Dense, Input
from keras.optimizers import RMSprop
from tensorflow import keras
from tensorflow.keras.datasets import mnist
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import Dense, Input
from tensorflow.keras.optimizers import RMSprop

weights_file_name = 'mnist_example.h5'
txt_file_name = weights_file_name.replace('h5', 'txt')
Expand DownExpand Up@@ -50,6 +50,6 @@
 verbose=1,
 validation_data=(x_test, y_test))

model.save(weights_file_name)
model.save(weights_file_name, save_format='h5')

h5_to_txt(weights_file_name, txt_file_name)

12 changes: 6 additions & 6 deletions
KerasWeightsProcessing/examples/multi_output_model.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -6,14 +6,14 @@
import tensorflow as tf

############## REPRODUCIBILITY ############
tf.set_random_seed(0)
tf.compat.v1.set_random_seed(0)
np.random.seed(0)
###########################################

from keras.models import load_model
from keras.models import Sequential, Model
from keras.utils.vis_utils import plot_model
from keras.layers import Dense, BatchNormalization, Input
from tensorflow.keras.models import load_model
from tensorflow.keras.models import Sequential, Model
from tensorflow.compat.v1.keras.utils import plot_model
from tensorflow.keras.layers import Dense, BatchNormalization, Input

input = x = Input((5,))
for i in range(3):
Expand All@@ -34,7 +34,7 @@
 metrics=['accuracy']
)
# SAVE TO FILE FOR PARSING
multi_output_model.save('multi_output_model.h5')
multi_output_model.save('multi_output_model.h5', save_format='h5')

# CONVERT TO TXT
convert_weights.h5_to_txt('multi_output_model.h5', 'single_output_model.txt')
Expand Down

12 changes: 6 additions & 6 deletions
KerasWeightsProcessing/examples/test_network.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
@@ -1,4 +1,4 @@
import keras
from tensorflow import keras
import argparse
import numpy as np
import subprocess
Expand All@@ -12,11 +12,11 @@
# set random seeds for reproducibility
np.random.seed(123)
import tensorflow as tf
tf.set_random_seed(123)
tf.compat.v1.set_random_seed(123)

from keras.models import Sequential, Model
from keras.layers import Dense, Input, LeakyReLU, Dropout, BatchNormalization
from keras.models import load_model
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import Dense, Input, LeakyReLU, Dropout, BatchNormalization
from tensorflow.keras.models import load_model

parser = argparse.ArgumentParser()
parser.add_argument('--train', action='store_true')
Expand DownExpand Up@@ -111,7 +111,7 @@
keras_predictions = model.predict(example_input)[0]

# save the weights
model.save(weights_file)
model.save(weights_file, save_format='h5')
# convert h5 file to txt
h5_to_txt(
 weights_file_name=weights_file,
Expand Down

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
Update to Tensorflow 2#13

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 Open

bsolino
wants to merge
9
commits into

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Update to Tensorflow 2
#13
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f7e0d67

Manually updated code to tf2


bsolino Mar 23, 2021
97f57e4

Converted files to v2 automatically


bsolino Mar 23, 2021
b630360

Merge branch 'tf2' into tf2-auto


bsolino Mar 24, 2021
a1c6d37

Merge pull request #1 from bsolino/tf2-auto


bsolino Mar 24, 2021
b077a59

Keeping lines as in original


bsolino Mar 24, 2021
77f9ec8

Keeping lines as in original


bsolino Mar 24, 2021
19be5f5

Import keras maintaining its name


bsolino Mar 24, 2021
69a2c9e

Prettier way to import keras


bsolino Mar 24, 2021
7b0a439

Prettier way to import keras


bsolino Mar 24, 2021

File filter

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8 changes: 4 additions & 4 deletions
GettingStarted.ipynb

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -32,11 +32,11 @@
 ],
 "source": [
 "import numpy as np\n",
 "from keras.layers import Dense\n",
 "from keras.models import Sequential\n",
 "from tensorflow.keras.layers import Dense\n",
 "from tensorflow.keras.models import Sequential\n",
 "from IPython.display import SVG\n",
 "from keras.utils import model_to_dot\n",
 "from tensorflow import set_random_seed"
 "from tensorflow.keras.utils import model_to_dot\n",
 "from tensorflow.compat.v1.random import set_random_seed"
 ]
 },
 {
Expand Down

14 changes: 7 additions & 7 deletions
KerasWeightsProcessing/convert_weights.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -6,12 +6,12 @@

import numpy as np
import math
import keras
import keras.backend as K
from keras.models import Sequential, Model
from keras.layers import Dense, Dropout, BatchNormalization
from keras.layers import Input, Activation
from keras import optimizers
from tensorflow import keras
import tensorflow.keras.backend as K
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import Dense, Dropout, BatchNormalization
from tensorflow.keras.layers import Input, Activation
from tensorflow.keras import optimizers

INPUT = ['input']
ACTIVATIONS = ['relu', 'linear', 'leakyrelu', 'sigmoid']
Expand DownExpand Up@@ -127,7 +127,7 @@ def txt_to_h5(weights_file_name, output_file_name=''):
 # if not specified will use path of weights_file with h5 extension
 output_file_name = weights_file_name.replace('.txt', '_converted.h5')

 model.save(output_file_name)
 model.save(output_file_name, save_format='h5')

def h5_to_txt(weights_file_name, output_file_name=''):
 '''
Expand Down

12 changes: 6 additions & 6 deletions
KerasWeightsProcessing/examples/mnist_keras.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -2,11 +2,11 @@
sys.path.append('../')
from convert_weights import h5_to_txt

import keras
from keras.datasets import mnist
from keras.models import Sequential, Model
from keras.layers import Dense, Input
from keras.optimizers import RMSprop
from tensorflow import keras
from tensorflow.keras.datasets import mnist
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import Dense, Input
from tensorflow.keras.optimizers import RMSprop

weights_file_name = 'mnist_example.h5'
txt_file_name = weights_file_name.replace('h5', 'txt')
Expand DownExpand Up@@ -50,6 +50,6 @@
 verbose=1,
 validation_data=(x_test, y_test))

model.save(weights_file_name)
model.save(weights_file_name, save_format='h5')

h5_to_txt(weights_file_name, txt_file_name)

12 changes: 6 additions & 6 deletions
KerasWeightsProcessing/examples/multi_output_model.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -6,14 +6,14 @@
import tensorflow as tf

############## REPRODUCIBILITY ############
tf.set_random_seed(0)
tf.compat.v1.set_random_seed(0)
np.random.seed(0)
###########################################

from keras.models import load_model
from keras.models import Sequential, Model
from keras.utils.vis_utils import plot_model
from keras.layers import Dense, BatchNormalization, Input
from tensorflow.keras.models import load_model
from tensorflow.keras.models import Sequential, Model
from tensorflow.compat.v1.keras.utils import plot_model
from tensorflow.keras.layers import Dense, BatchNormalization, Input

input = x = Input((5,))
for i in range(3):
Expand All@@ -34,7 +34,7 @@
 metrics=['accuracy']
)
# SAVE TO FILE FOR PARSING
multi_output_model.save('multi_output_model.h5')
multi_output_model.save('multi_output_model.h5', save_format='h5')

# CONVERT TO TXT
convert_weights.h5_to_txt('multi_output_model.h5', 'single_output_model.txt')
Expand Down

12 changes: 6 additions & 6 deletions
KerasWeightsProcessing/examples/test_network.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
@@ -1,4 +1,4 @@
import keras
from tensorflow import keras
import argparse
import numpy as np
import subprocess
Expand All@@ -12,11 +12,11 @@
# set random seeds for reproducibility
np.random.seed(123)
import tensorflow as tf
tf.set_random_seed(123)
tf.compat.v1.set_random_seed(123)

from keras.models import Sequential, Model
from keras.layers import Dense, Input, LeakyReLU, Dropout, BatchNormalization
from keras.models import load_model
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import Dense, Input, LeakyReLU, Dropout, BatchNormalization
from tensorflow.keras.models import load_model

parser = argparse.ArgumentParser()
parser.add_argument('--train', action='store_true')
Expand DownExpand Up@@ -111,7 +111,7 @@
keras_predictions = model.predict(example_input)[0]

# save the weights
model.save(weights_file)
model.save(weights_file, save_format='h5')
# convert h5 file to txt
h5_to_txt(
 weights_file_name=weights_file,
Expand Down

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
Update to Tensorflow 2#13

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

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privacy statement. We’ll occasionally send you account related emails.

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 Open

bsolino
wants to merge
9
commits into

base:master
Choose a base branch

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Update to Tensorflow 2
#13
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f7e0d67

Manually updated code to tf2


bsolino Mar 23, 2021
97f57e4

Converted files to v2 automatically


bsolino Mar 23, 2021
b630360

Merge branch 'tf2' into tf2-auto


bsolino Mar 24, 2021
a1c6d37

Merge pull request #1 from bsolino/tf2-auto


bsolino Mar 24, 2021
b077a59

Keeping lines as in original


bsolino Mar 24, 2021
77f9ec8

Keeping lines as in original


bsolino Mar 24, 2021
19be5f5

Import keras maintaining its name


bsolino Mar 24, 2021
69a2c9e

Prettier way to import keras


bsolino Mar 24, 2021
7b0a439

Prettier way to import keras


bsolino Mar 24, 2021

File filter

Filter by extension
Filter by extension
Conversations

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8 changes: 4 additions & 4 deletions
GettingStarted.ipynb

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -32,11 +32,11 @@
 ],
 "source": [
 "import numpy as np\n",
 "from keras.layers import Dense\n",
 "from keras.models import Sequential\n",
 "from tensorflow.keras.layers import Dense\n",
 "from tensorflow.keras.models import Sequential\n",
 "from IPython.display import SVG\n",
 "from keras.utils import model_to_dot\n",
 "from tensorflow import set_random_seed"
 "from tensorflow.keras.utils import model_to_dot\n",
 "from tensorflow.compat.v1.random import set_random_seed"
 ]
 },
 {
Expand Down

14 changes: 7 additions & 7 deletions
KerasWeightsProcessing/convert_weights.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -6,12 +6,12 @@

import numpy as np
import math
import keras
import keras.backend as K
from keras.models import Sequential, Model
from keras.layers import Dense, Dropout, BatchNormalization
from keras.layers import Input, Activation
from keras import optimizers
from tensorflow import keras
import tensorflow.keras.backend as K
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import Dense, Dropout, BatchNormalization
from tensorflow.keras.layers import Input, Activation
from tensorflow.keras import optimizers

INPUT = ['input']
ACTIVATIONS = ['relu', 'linear', 'leakyrelu', 'sigmoid']
Expand DownExpand Up@@ -127,7 +127,7 @@ def txt_to_h5(weights_file_name, output_file_name=''):
 # if not specified will use path of weights_file with h5 extension
 output_file_name = weights_file_name.replace('.txt', '_converted.h5')

 model.save(output_file_name)
 model.save(output_file_name, save_format='h5')

def h5_to_txt(weights_file_name, output_file_name=''):
 '''
Expand Down

12 changes: 6 additions & 6 deletions
KerasWeightsProcessing/examples/mnist_keras.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -2,11 +2,11 @@
sys.path.append('../')
from convert_weights import h5_to_txt

import keras
from keras.datasets import mnist
from keras.models import Sequential, Model
from keras.layers import Dense, Input
from keras.optimizers import RMSprop
from tensorflow import keras
from tensorflow.keras.datasets import mnist
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import Dense, Input
from tensorflow.keras.optimizers import RMSprop

weights_file_name = 'mnist_example.h5'
txt_file_name = weights_file_name.replace('h5', 'txt')
Expand DownExpand Up@@ -50,6 +50,6 @@
 verbose=1,
 validation_data=(x_test, y_test))

model.save(weights_file_name)
model.save(weights_file_name, save_format='h5')

h5_to_txt(weights_file_name, txt_file_name)

12 changes: 6 additions & 6 deletions
KerasWeightsProcessing/examples/multi_output_model.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -6,14 +6,14 @@
import tensorflow as tf

############## REPRODUCIBILITY ############
tf.set_random_seed(0)
tf.compat.v1.set_random_seed(0)
np.random.seed(0)
###########################################

from keras.models import load_model
from keras.models import Sequential, Model
from keras.utils.vis_utils import plot_model
from keras.layers import Dense, BatchNormalization, Input
from tensorflow.keras.models import load_model
from tensorflow.keras.models import Sequential, Model
from tensorflow.compat.v1.keras.utils import plot_model
from tensorflow.keras.layers import Dense, BatchNormalization, Input

input = x = Input((5,))
for i in range(3):
Expand All@@ -34,7 +34,7 @@
 metrics=['accuracy']
)
# SAVE TO FILE FOR PARSING
multi_output_model.save('multi_output_model.h5')
multi_output_model.save('multi_output_model.h5', save_format='h5')

# CONVERT TO TXT
convert_weights.h5_to_txt('multi_output_model.h5', 'single_output_model.txt')
Expand Down

12 changes: 6 additions & 6 deletions
KerasWeightsProcessing/examples/test_network.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
@@ -1,4 +1,4 @@
import keras
from tensorflow import keras
import argparse
import numpy as np
import subprocess
Expand All@@ -12,11 +12,11 @@
# set random seeds for reproducibility
np.random.seed(123)
import tensorflow as tf
tf.set_random_seed(123)
tf.compat.v1.set_random_seed(123)

from keras.models import Sequential, Model
from keras.layers import Dense, Input, LeakyReLU, Dropout, BatchNormalization
from keras.models import load_model
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import Dense, Input, LeakyReLU, Dropout, BatchNormalization
from tensorflow.keras.models import load_model

parser = argparse.ArgumentParser()
parser.add_argument('--train', action='store_true')
Expand DownExpand Up@@ -111,7 +111,7 @@
keras_predictions = model.predict(example_input)[0]

# save the weights
model.save(weights_file)
model.save(weights_file, save_format='h5')
# convert h5 file to txt
h5_to_txt(
 weights_file_name=weights_file,
Expand Down

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
Update to Tensorflow 2#13

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

 Sign up for GitHub

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privacy statement. We’ll occasionally send you account related emails.

Already on GitHub?
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to your account

 Open

bsolino
wants to merge
9
commits into

base:master
Choose a base branch

from

 Open


Update to Tensorflow 2
#13
Show file tree
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Commits

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9 commits


Select commit
Hold shift + click to select a range
f7e0d67

Manually updated code to tf2


bsolino Mar 23, 2021
97f57e4

Converted files to v2 automatically


bsolino Mar 23, 2021
b630360

Merge branch 'tf2' into tf2-auto


bsolino Mar 24, 2021
a1c6d37

Merge pull request #1 from bsolino/tf2-auto


bsolino Mar 24, 2021
b077a59

Keeping lines as in original


bsolino Mar 24, 2021
77f9ec8

Keeping lines as in original


bsolino Mar 24, 2021
19be5f5

Import keras maintaining its name


bsolino Mar 24, 2021
69a2c9e

Prettier way to import keras


bsolino Mar 24, 2021
7b0a439

Prettier way to import keras


bsolino Mar 24, 2021

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8 changes: 4 additions & 4 deletions
GettingStarted.ipynb

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -32,11 +32,11 @@
 ],
 "source": [
 "import numpy as np\n",
 "from keras.layers import Dense\n",
 "from keras.models import Sequential\n",
 "from tensorflow.keras.layers import Dense\n",
 "from tensorflow.keras.models import Sequential\n",
 "from IPython.display import SVG\n",
 "from keras.utils import model_to_dot\n",
 "from tensorflow import set_random_seed"
 "from tensorflow.keras.utils import model_to_dot\n",
 "from tensorflow.compat.v1.random import set_random_seed"
 ]
 },
 {
Expand Down

14 changes: 7 additions & 7 deletions
KerasWeightsProcessing/convert_weights.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -6,12 +6,12 @@

import numpy as np
import math
import keras
import keras.backend as K
from keras.models import Sequential, Model
from keras.layers import Dense, Dropout, BatchNormalization
from keras.layers import Input, Activation
from keras import optimizers
from tensorflow import keras
import tensorflow.keras.backend as K
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import Dense, Dropout, BatchNormalization
from tensorflow.keras.layers import Input, Activation
from tensorflow.keras import optimizers

INPUT = ['input']
ACTIVATIONS = ['relu', 'linear', 'leakyrelu', 'sigmoid']
Expand DownExpand Up@@ -127,7 +127,7 @@ def txt_to_h5(weights_file_name, output_file_name=''):
 # if not specified will use path of weights_file with h5 extension
 output_file_name = weights_file_name.replace('.txt', '_converted.h5')

 model.save(output_file_name)
 model.save(output_file_name, save_format='h5')

def h5_to_txt(weights_file_name, output_file_name=''):
 '''
Expand Down

12 changes: 6 additions & 6 deletions
KerasWeightsProcessing/examples/mnist_keras.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -2,11 +2,11 @@
sys.path.append('../')
from convert_weights import h5_to_txt

import keras
from keras.datasets import mnist
from keras.models import Sequential, Model
from keras.layers import Dense, Input
from keras.optimizers import RMSprop
from tensorflow import keras
from tensorflow.keras.datasets import mnist
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import Dense, Input
from tensorflow.keras.optimizers import RMSprop

weights_file_name = 'mnist_example.h5'
txt_file_name = weights_file_name.replace('h5', 'txt')
Expand DownExpand Up@@ -50,6 +50,6 @@
 verbose=1,
 validation_data=(x_test, y_test))

model.save(weights_file_name)
model.save(weights_file_name, save_format='h5')

h5_to_txt(weights_file_name, txt_file_name)

12 changes: 6 additions & 6 deletions
KerasWeightsProcessing/examples/multi_output_model.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -6,14 +6,14 @@
import tensorflow as tf

############## REPRODUCIBILITY ############
tf.set_random_seed(0)
tf.compat.v1.set_random_seed(0)
np.random.seed(0)
###########################################

from keras.models import load_model
from keras.models import Sequential, Model
from keras.utils.vis_utils import plot_model
from keras.layers import Dense, BatchNormalization, Input
from tensorflow.keras.models import load_model
from tensorflow.keras.models import Sequential, Model
from tensorflow.compat.v1.keras.utils import plot_model
from tensorflow.keras.layers import Dense, BatchNormalization, Input

input = x = Input((5,))
for i in range(3):
Expand All@@ -34,7 +34,7 @@
 metrics=['accuracy']
)
# SAVE TO FILE FOR PARSING
multi_output_model.save('multi_output_model.h5')
multi_output_model.save('multi_output_model.h5', save_format='h5')

# CONVERT TO TXT
convert_weights.h5_to_txt('multi_output_model.h5', 'single_output_model.txt')
Expand Down

12 changes: 6 additions & 6 deletions
KerasWeightsProcessing/examples/test_network.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
@@ -1,4 +1,4 @@
import keras
from tensorflow import keras
import argparse
import numpy as np
import subprocess
Expand All@@ -12,11 +12,11 @@
# set random seeds for reproducibility
np.random.seed(123)
import tensorflow as tf
tf.set_random_seed(123)
tf.compat.v1.set_random_seed(123)

from keras.models import Sequential, Model
from keras.layers import Dense, Input, LeakyReLU, Dropout, BatchNormalization
from keras.models import load_model
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import Dense, Input, LeakyReLU, Dropout, BatchNormalization
from tensorflow.keras.models import load_model

parser = argparse.ArgumentParser()
parser.add_argument('--train', action='store_true')
Expand DownExpand Up@@ -111,7 +111,7 @@
keras_predictions = model.predict(example_input)[0]

# save the weights
model.save(weights_file)
model.save(weights_file, save_format='h5')
# convert h5 file to txt
h5_to_txt(
 weights_file_name=weights_file,
Expand Down

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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f7e0d67

Manually updated code to tf2


bsolino Mar 23, 2021
97f57e4

Converted files to v2 automatically


bsolino Mar 23, 2021
b630360

Merge branch 'tf2' into tf2-auto


bsolino Mar 24, 2021
a1c6d37

Merge pull request #1 from bsolino/tf2-auto


bsolino Mar 24, 2021
b077a59

Keeping lines as in original


bsolino Mar 24, 2021
77f9ec8

Keeping lines as in original


bsolino Mar 24, 2021
19be5f5

Import keras maintaining its name


bsolino Mar 24, 2021
69a2c9e

Prettier way to import keras


bsolino Mar 24, 2021
7b0a439

Prettier way to import keras


bsolino Mar 24, 2021

File filter

Filter by extension
Filter by extension
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8 changes: 4 additions & 4 deletions
GettingStarted.ipynb

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -32,11 +32,11 @@
 ],
 "source": [
 "import numpy as np\n",
 "from keras.layers import Dense\n",
 "from keras.models import Sequential\n",
 "from tensorflow.keras.layers import Dense\n",
 "from tensorflow.keras.models import Sequential\n",
 "from IPython.display import SVG\n",
 "from keras.utils import model_to_dot\n",
 "from tensorflow import set_random_seed"
 "from tensorflow.keras.utils import model_to_dot\n",
 "from tensorflow.compat.v1.random import set_random_seed"
 ]
 },
 {
Expand Down

14 changes: 7 additions & 7 deletions
KerasWeightsProcessing/convert_weights.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -6,12 +6,12 @@

import numpy as np
import math
import keras
import keras.backend as K
from keras.models import Sequential, Model
from keras.layers import Dense, Dropout, BatchNormalization
from keras.layers import Input, Activation
from keras import optimizers
from tensorflow import keras
import tensorflow.keras.backend as K
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import Dense, Dropout, BatchNormalization
from tensorflow.keras.layers import Input, Activation
from tensorflow.keras import optimizers

INPUT = ['input']
ACTIVATIONS = ['relu', 'linear', 'leakyrelu', 'sigmoid']
Expand DownExpand Up@@ -127,7 +127,7 @@ def txt_to_h5(weights_file_name, output_file_name=''):
 # if not specified will use path of weights_file with h5 extension
 output_file_name = weights_file_name.replace('.txt', '_converted.h5')

 model.save(output_file_name)
 model.save(output_file_name, save_format='h5')

def h5_to_txt(weights_file_name, output_file_name=''):
 '''
Expand Down

12 changes: 6 additions & 6 deletions
KerasWeightsProcessing/examples/mnist_keras.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -2,11 +2,11 @@
sys.path.append('../')
from convert_weights import h5_to_txt

import keras
from keras.datasets import mnist
from keras.models import Sequential, Model
from keras.layers import Dense, Input
from keras.optimizers import RMSprop
from tensorflow import keras
from tensorflow.keras.datasets import mnist
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import Dense, Input
from tensorflow.keras.optimizers import RMSprop

weights_file_name = 'mnist_example.h5'
txt_file_name = weights_file_name.replace('h5', 'txt')
Expand DownExpand Up@@ -50,6 +50,6 @@
 verbose=1,
 validation_data=(x_test, y_test))

model.save(weights_file_name)
model.save(weights_file_name, save_format='h5')

h5_to_txt(weights_file_name, txt_file_name)

12 changes: 6 additions & 6 deletions
KerasWeightsProcessing/examples/multi_output_model.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -6,14 +6,14 @@
import tensorflow as tf

############## REPRODUCIBILITY ############
tf.set_random_seed(0)
tf.compat.v1.set_random_seed(0)
np.random.seed(0)
###########################################

from keras.models import load_model
from keras.models import Sequential, Model
from keras.utils.vis_utils import plot_model
from keras.layers import Dense, BatchNormalization, Input
from tensorflow.keras.models import load_model
from tensorflow.keras.models import Sequential, Model
from tensorflow.compat.v1.keras.utils import plot_model
from tensorflow.keras.layers import Dense, BatchNormalization, Input

input = x = Input((5,))
for i in range(3):
Expand All@@ -34,7 +34,7 @@
 metrics=['accuracy']
)
# SAVE TO FILE FOR PARSING
multi_output_model.save('multi_output_model.h5')
multi_output_model.save('multi_output_model.h5', save_format='h5')

# CONVERT TO TXT
convert_weights.h5_to_txt('multi_output_model.h5', 'single_output_model.txt')
Expand Down

12 changes: 6 additions & 6 deletions
KerasWeightsProcessing/examples/test_network.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
@@ -1,4 +1,4 @@
import keras
from tensorflow import keras
import argparse
import numpy as np
import subprocess
Expand All@@ -12,11 +12,11 @@
# set random seeds for reproducibility
np.random.seed(123)
import tensorflow as tf
tf.set_random_seed(123)
tf.compat.v1.set_random_seed(123)

from keras.models import Sequential, Model
from keras.layers import Dense, Input, LeakyReLU, Dropout, BatchNormalization
from keras.models import load_model
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import Dense, Input, LeakyReLU, Dropout, BatchNormalization
from tensorflow.keras.models import load_model

parser = argparse.ArgumentParser()
parser.add_argument('--train', action='store_true')
Expand DownExpand Up@@ -111,7 +111,7 @@
keras_predictions = model.predict(example_input)[0]

# save the weights
model.save(weights_file)
model.save(weights_file, save_format='h5')
# convert h5 file to txt
h5_to_txt(
 weights_file_name=weights_file,
Expand Down