vae

a-mhamdi · Dec 23, 2024 · 2f8dab8 · 2f8dab8
1 parent fa96da8
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diff --git a/Codes/Julia/Part-3/vae/vae.ipynb b/Codes/Julia/Part-3/vae/vae.ipynb
@@ -11,16 +11,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "id": "beab227b-2d88-4b30-ac4d-52f0ebbaf1c3",
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Julia Version 1.11.1\n",
-      "Commit 8f5b7ca12ad (2024-10-16 10:53 UTC)\n",
+      "Julia Version 1.11.2\n",
+      "Commit 5e9a32e7af2 (2024-12-01 20:02 UTC)\n",
       "Build Info:\n",
       "  Official https://julialang.org/ release\n",
       "Platform Info:\n",
@@ -30,14 +30,14 @@
       "  LLVM: libLLVM-16.0.6 (ORCJIT, skylake)\n",
       "Threads: 1 default, 0 interactive, 1 GC (on 8 virtual cores)\n",
       "Environment:\n",
-      "  LD_LIBRARY_PATH = /home/mhamdi/torch/install/lib:/home/mhamdi/torch/install/lib:/home/mhamdi/torch/install/lib:\n",
       "  DYLD_LIBRARY_PATH = /home/mhamdi/torch/install/lib:/home/mhamdi/torch/install/lib:/home/mhamdi/torch/install/lib:\n",
+      "  LD_LIBRARY_PATH = /home/mhamdi/torch/install/lib:/home/mhamdi/torch/install/lib:/home/mhamdi/torch/install/lib:\n",
       "  JULIA_NUM_THREADS = 8\n"
      ]
     }
    ],
    "source": [
-    "versioninfo() # -> v\"1.11.1\""
+    "versioninfo() # -> v\"1.11.2\""
    ]
   },
   {
@@ -63,7 +63,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "using Flux # v0.14.25\n",
+    "using Flux # v\"0.16.0\"\n",
     "using Flux: @functor\n",
     "using Flux: DataLoader\n",
     "using Flux: onecold, onehotbatch"
@@ -151,7 +151,7 @@
    "id": "bc40899e-5ae7-4e21-8315-cc3c9fb71571",
    "metadata": {},
    "source": [
-    "Define the `encoder` network"
+    "Define the `encoder` network: The encoder network should return the parameters of the _latent distribution_ (μ and σ)."
    ]
   },
   {
@@ -161,7 +161,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# The encoder network should return the parameters of the _latent distribution_ (μ and σ).\n",
     "struct Encoder\n",
     "    linear\n",
     "    μ\n",
@@ -211,7 +210,7 @@
    "id": "2b653535-0cfb-44e7-ab0f-363638bb0cd5",
    "metadata": {},
    "source": [
-    "Define the `decoder` network"
+    "Define the `decoder` network: The decoder network should return the reconstruction of the input data"
    ]
   },
   {
@@ -221,7 +220,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# The decoder network should return the reconstruction of the input data\n",
     "decoder(input_dim::Int, hidden_dim::Int, latent_dim::Int) = Chain(\n",
     "    Dense(latent_dim, hidden_dim, tanh),\n",
     "    Dense(hidden_dim, input_dim)\n",
@@ -308,7 +306,7 @@
     "        end\n",
     "    end\n",
     "    \n",
-    "    md\"Save the model\"\n",
+    "    # Save the model\n",
     "    #=\n",
     "    using DrWatson: struct2dict\n",
     "    using BSON\n",
@@ -337,15 +335,15 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Julia 1.11.1",
+   "display_name": "IJulia 1.11.2",
    "language": "julia",
-   "name": "julia-1.11"
+   "name": "ijulia-1.11"
   },
   "language_info": {
    "file_extension": ".jl",
    "mimetype": "application/julia",
    "name": "julia",
-   "version": "1.11.1"
+   "version": "1.11.2"
   }
  },
  "nbformat": 4,

diff --git a/Codes/Julia/Part-3/vae/vae.jl b/Codes/Julia/Part-3/vae/vae.jl
@@ -1,19 +1,14 @@
 ### A Pluto.jl notebook ###
-# v0.20.3
+# v0.20.4
 
 using Markdown
 using InteractiveUtils
 
-# ╔═╡ be2eb522-922c-4cd9-9f60-3305eacef23a
-###################################
-#= VARIATIONAL AUTOENCODER (VAE) =#
-###################################
-# `versioninfo()` -> 1.11.1
-
-using Markdown
+# ╔═╡ 4c4e5a73-dfb5-4925-9b3e-5100879feee6
+	import Pkg; Pkg.activate(".")
 
 # ╔═╡ 5431e024-d2ae-4279-bf9e-c72e1455c7bc
-using Flux # v0.14.25
+using Flux # v"0.16.0"
 
 # ╔═╡ 1d0e8c52-3758-4520-afde-2c7cadd3b427
 using Flux: @functor
@@ -30,8 +25,14 @@ using ProgressMeter: Progress, next!
 # ╔═╡ 165e4355-ada6-4c29-9687-01ca368735a2
 using MLDatasets
 
+# ╔═╡ be2eb522-922c-4cd9-9f60-3305eacef23a
+md"# VARIATIONAL AUTOENCODER (VAE)"
+
+# ╔═╡ aae8ee36-56b0-4594-9454-e0fb13bb9e32
+versioninfo() # -> v"1.11.2"
+
 # ╔═╡ 6cdf0ae0-ac6b-4938-9598-e834cad5a94f
-md"VAE implemented in `Julia` using the `Flux.jl` library"
+md"**VAE** implemented in `Julia` using the `Flux.jl` library"
 
 # ╔═╡ a294646d-fc11-472e-9b3a-f7567387a373
 md"Import the machine learning library `Flux`"
@@ -72,11 +73,23 @@ train_loader = get_data();
 test_loader = get_data(split=:test);
 
 # ╔═╡ 52d26401-72b9-421f-85bb-42cab7acf738
-md"Define the `encoder` network"
-# The encoder network should return the parameters of the _latent distribution_ (μ and σ).
+md"Define the `encoder` network: The encoder network should return the parameters of the _latent distribution_ (μ and σ)."
 
-# ╔═╡ 166f94e0-e865-4bb8-96e8-0383180db4a3
-@functor Encoder
+# ╔═╡ 1f68c46b-443f-404a-b872-f2ac0f5b0b0f
+Encoder = begin 
+	struct Encoder
+	    linear
+	    μ
+	    log_σ
+	end
+
+	@functor Encoder
+
+	function (encoder::Encoder)(x)
+    	h = encoder.linear(x)
+    	encoder.μ(h), encoder.log_σ(h)
+	end
+end
 
 # ╔═╡ 8940c576-206d-42e2-bb3f-12ecedf963c2
 encoder(input_dim::Int, hidden_dim::Int, latent_dim::Int) = Encoder(
@@ -86,8 +99,7 @@ encoder(input_dim::Int, hidden_dim::Int, latent_dim::Int) = Encoder(
 )
 
 # ╔═╡ b413a818-19f5-4d89-b8de-04bf085a2ffb
-md"Define the `decoder` network"
-# The decoder network should return the reconstruction of the input data
+md"Define the `decoder` network: The decoder network should return the reconstruction of the input data"
 
 # ╔═╡ f2b696d0-06c5-4570-8419-aa921609500c
 decoder(input_dim::Int, hidden_dim::Int, latent_dim::Int) = Chain(
@@ -150,7 +162,7 @@ function train(; kws...)
         end
     end
 
-    md"Save the model"
+    # Save the model
     #=
     using DrWatson: struct2dict
     using BSON
@@ -168,22 +180,23 @@ end
 # ╔═╡ 73aec761-ab49-4235-9d52-3c80419de7e2
 enc_model, dec_model = train()
 
-# ╔═╡ c4f262cb-938a-457c-807f-e17b41caee5e
-function (encoder::Encoder)(x)
-    h = encoder.linear(x)
-    encoder.μ(h), encoder.log_σ(h)
-end
-
-# ╔═╡ 1f68c46b-443f-404a-b872-f2ac0f5b0b0f
-struct Encoder
-    linear
-    μ
-    log_σ
-end
+# ╔═╡ a43c274c-81fd-4d5d-a37c-858ead7dfd01
+html"""
+<style>
+	main {
+		margin: 0 auto;
+		max-width: 2000px;
+		padding-left: max(160px, 10%);
+		padding-right: max(160px, 10%);
+	}
+</style>
+"""
 
 # ╔═╡ Cell order:
 # ╠═be2eb522-922c-4cd9-9f60-3305eacef23a
+# ╠═aae8ee36-56b0-4594-9454-e0fb13bb9e32
 # ╠═6cdf0ae0-ac6b-4938-9598-e834cad5a94f
+# ╠═4c4e5a73-dfb5-4925-9b3e-5100879feee6
 # ╠═a294646d-fc11-472e-9b3a-f7567387a373
 # ╠═5431e024-d2ae-4279-bf9e-c72e1455c7bc
 # ╠═1d0e8c52-3758-4520-afde-2c7cadd3b427
@@ -199,13 +212,12 @@ end
 # ╠═6a0cc987-638e-45cf-9f8c-e7cdbbfa189b
 # ╠═52d26401-72b9-421f-85bb-42cab7acf738
 # ╠═1f68c46b-443f-404a-b872-f2ac0f5b0b0f
-# ╠═166f94e0-e865-4bb8-96e8-0383180db4a3
 # ╠═8940c576-206d-42e2-bb3f-12ecedf963c2
-# ╠═c4f262cb-938a-457c-807f-e17b41caee5e
 # ╠═b413a818-19f5-4d89-b8de-04bf085a2ffb
 # ╠═f2b696d0-06c5-4570-8419-aa921609500c
 # ╠═bf736186-b254-42be-a2ec-a6d27af51b6e
 # ╠═7dc4a830-9289-49bb-a690-32a9e82ff262
 # ╠═db131d6e-c245-46cb-a292-b14c44a845b7
 # ╠═91d78390-28d4-456b-9a24-8708e9172233
 # ╠═73aec761-ab49-4235-9d52-3c80419de7e2
+# ╟─a43c274c-81fd-4d5d-a37c-858ead7dfd01