Use AdamW from tf.keras.optimizers instead of TensorFlow-Addons
Aurélien Geron
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bde6c1704e
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de0eb33694
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@ -1780,36 +1780,24 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"On Colab or Kaggle, we need to install the TensorFlow-Addons library:"
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"Note: Since TF 1.12, `AdamW` is no longer experimental. It is available at `tf.keras.optimizers.AdamW` instead of `tf.keras.optimizers.experimental.AdamW`."
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]
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{
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"cell_type": "code",
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"execution_count": 62,
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"metadata": {},
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"outputs": [],
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"source": [
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"if \"google.colab\" in sys.modules:\n",
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" %pip install -q -U tensorflow-addons"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 63,
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"import tensorflow_addons as tfa\n",
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"\n",
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"optimizer = tfa.optimizers.AdamW(weight_decay=1e-5, learning_rate=0.001,\n",
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" beta_1=0.9, beta_2=0.999)"
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"optimizer = tf.keras.optimizers.AdamW(weight_decay=1e-5, learning_rate=0.001,\n",
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" beta_1=0.9, beta_2=0.999)"
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]
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},
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|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 114,
|
||||
"execution_count": 113,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
|
|
@ -3385,7 +3373,7 @@
|
|||
" dtype=float32)"
|
||||
]
|
||||
},
|
||||
"execution_count": 114,
|
||||
"execution_count": 113,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
|
|
@ -3406,7 +3394,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 115,
|
||||
"execution_count": 114,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
|
|
@ -3417,7 +3405,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 116,
|
||||
"execution_count": 115,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
|
|
@ -3512,7 +3500,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 117,
|
||||
"execution_count": 116,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
|
|
@ -3543,7 +3531,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 118,
|
||||
"execution_count": 117,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
|
|
@ -3559,7 +3547,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 119,
|
||||
"execution_count": 118,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
|
|
@ -3578,7 +3566,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 120,
|
||||
"execution_count": 119,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
|
|
@ -3600,7 +3588,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 121,
|
||||
"execution_count": 120,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
|
|
@ -3616,7 +3604,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 122,
|
||||
"execution_count": 121,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
|
|
@ -3653,7 +3641,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 123,
|
||||
"execution_count": 122,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
|
|
@ -3739,7 +3727,7 @@
|
|||
"<keras.callbacks.History at 0x7fb9f02fc070>"
|
||||
]
|
||||
},
|
||||
"execution_count": 123,
|
||||
"execution_count": 122,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
|
|
@ -3752,7 +3740,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 124,
|
||||
"execution_count": 123,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
|
|
@ -3768,7 +3756,7 @@
|
|||
"[1.5061508417129517, 0.4675999879837036]"
|
||||
]
|
||||
},
|
||||
"execution_count": 124,
|
||||
"execution_count": 123,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
|
|
@ -3805,7 +3793,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 125,
|
||||
"execution_count": 124,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
|
|
@ -3891,7 +3879,7 @@
|
|||
"[1.4236289262771606, 0.5073999762535095]"
|
||||
]
|
||||
},
|
||||
"execution_count": 125,
|
||||
"execution_count": 124,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
|
|
@ -3948,7 +3936,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 126,
|
||||
"execution_count": 125,
|
||||
"metadata": {
|
||||
"scrolled": true
|
||||
},
|
||||
|
|
@ -4042,7 +4030,7 @@
|
|||
"[1.4607702493667603, 0.5026000142097473]"
|
||||
]
|
||||
},
|
||||
"execution_count": 126,
|
||||
"execution_count": 125,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
|
|
@ -4103,7 +4091,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 127,
|
||||
"execution_count": 126,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
|
|
@ -4183,7 +4171,7 @@
|
|||
"[1.4779616594314575, 0.498199999332428]"
|
||||
]
|
||||
},
|
||||
"execution_count": 127,
|
||||
"execution_count": 126,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
|
|
@ -4244,7 +4232,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 128,
|
||||
"execution_count": 127,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
|
|
@ -4262,7 +4250,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 129,
|
||||
"execution_count": 128,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
|
|
@ -4285,7 +4273,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 130,
|
||||
"execution_count": 129,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
|
|
@ -4307,7 +4295,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 131,
|
||||
"execution_count": 130,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
|
|
@ -4316,7 +4304,7 @@
|
|||
"0.4984"
|
||||
]
|
||||
},
|
||||
"execution_count": 131,
|
||||
"execution_count": 130,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
|
|
@ -4348,7 +4336,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 132,
|
||||
"execution_count": 131,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
|
|
@ -4372,7 +4360,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 133,
|
||||
"execution_count": 132,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
|
|
@ -4404,7 +4392,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 134,
|
||||
"execution_count": 133,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
|
|
@ -4428,7 +4416,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 135,
|
||||
"execution_count": 134,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
|
|
@ -4501,7 +4489,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.10.6"
|
||||
"version": "3.9.10"
|
||||
},
|
||||
"nav_menu": {
|
||||
"height": "360px",
|
||||
|
|
|
|||
Loading…
Reference in New Issue