update vae faces

Author: davidADSP

docs/history.csv

@@ -33,7 +33,7 @@ GLOW,09/07/2018,https://arxiv.org/abs/1807.03039,0,Normalizing Flow,
 Universal Transformer,10/07/2018,https://arxiv.org/abs/1807.03819,1,Autoregressive / Transformer,
 BigGAN,28/09/2018,https://arxiv.org/abs/1809.11096,0,Generative Adversarial Network,
 FFJORD,02/10/2018,https://arxiv.org/abs/1810.01367,0,Normalizing Flow,
-BERT,11/10/2018,https://arxiv.org/abs/1810.04805,1,Autoregressive / Transformer,
+BERT,11/10/2018,https://arxiv.org/abs/1810.04805,0,Autoregressive / Transformer,0.345
 StyleGAN,12/12/2018,https://arxiv.org/abs/1812.04948,0,Generative Adversarial Network,
 Music Transformer,12/12/2018,https://arxiv.org/abs/1809.04281,0,Autoregressive / Transformer,
 GPT-2,14/02/2019,https://cdn.openai.com/better-language-models/language_models_are_unsupervised_multitask_learners.pdf,0,Autoregressive / Transformer,1.5
@@ -81,6 +81,11 @@ LLaMA,24/02/2023,https://arxiv.org/abs/2302.13971,0,Autoregressive / Transformer
 PaLM-E,06/03/2023,https://arxiv.org/abs/2303.03378,0,Multimodal Models,562
 Visual ChatGPT,08/03/2023,https://arxiv.org/abs/2303.04671,0,Multimodal Models,
 Alpaca,13/03/2023,https://github.com/tatsu-lab/stanford_alpaca,1,Autoregressive / Transformer,
-GPT-4,16/03/2023,https://cdn.openai.com/papers/gpt-4.pdf,0,Multimodal Models,
+GPT-4,16/03/2023,https://cdn.openai.com/papers/gpt-4.pdf,0,Autoregressive / Transformer,1000
 Luminous,14/04/2022,https://www.aleph-alpha.com/luminous,0,Autoregressive / Transformer,
-Flan-T5,20/10/2022,https://arxiv.org/abs/2210.11416,0,Autoregressive / Transformer,11
+Flan-T5,20/10/2022,https://arxiv.org/abs/2210.11416,0,Autoregressive / Transformer,11
+Falcon,17/03/2023,https://falconllm.tii.ae/,0,Autoregressive / Transformer,40
+PaLM 2,10/05/2023,https://ai.google/discover/palm2/,0,Autoregressive / Transformer,340
+PanGu-Σ,20/03/2023,https://arxiv.org/abs/2303.10845,1,Autoregressive / Transformer,1085
+GPT-3.5,30/11/2022,,0,Autoregressive / Transformer,175
+Llama 2,17/07/2023,,0,Autoregressive / Transformer,70

notebooks/03_vae/03_vae_faces/vae_faces.ipynb

@@ -64,10 +64,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "IMAGE_SIZE = 64\n",
+    "IMAGE_SIZE = 32\n",
     "CHANNELS = 3\n",
     "BATCH_SIZE = 128\n",
-    "NUM_FEATURES = 64\n",
+    "NUM_FEATURES = 128\n",
     "Z_DIM = 200\n",
     "LEARNING_RATE = 0.0005\n",
     "EPOCHS = 10\n",
@@ -191,9 +191,6 @@
     "x = layers.Conv2D(NUM_FEATURES, kernel_size=3, strides=2, padding=\"same\")(x)\n",
     "x = layers.BatchNormalization()(x)\n",
     "x = layers.LeakyReLU()(x)\n",
-    "x = layers.Conv2D(NUM_FEATURES, kernel_size=3, strides=2, padding=\"same\")(x)\n",
-    "x = layers.BatchNormalization()(x)\n",
-    "x = layers.LeakyReLU()(x)\n",
     "shape_before_flattening = K.int_shape(x)[1:]  # the decoder will need this!\n",
     "\n",
     "x = layers.Flatten()(x)\n",
@@ -238,11 +235,6 @@
     ")(x)\n",
     "x = layers.BatchNormalization()(x)\n",
     "x = layers.LeakyReLU()(x)\n",
-    "x = layers.Conv2DTranspose(\n",
-    "    NUM_FEATURES, kernel_size=3, strides=2, padding=\"same\"\n",
-    ")(x)\n",
-    "x = layers.BatchNormalization()(x)\n",
-    "x = layers.LeakyReLU()(x)\n",
     "decoder_output = layers.Conv2DTranspose(\n",
     "    CHANNELS, kernel_size=3, strides=1, activation=\"sigmoid\", padding=\"same\"\n",
     ")(x)\n",
@@ -665,7 +657,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.6"
+   "version": "3.8.10"
   },
   "vscode": {
    "interpreter": {