From 373140576ff90d14a9a501ce52dcb827a2d288df Mon Sep 17 00:00:00 2001 From: Sebastian Raschka Date: Thu, 7 Nov 2019 10:05:39 -0600 Subject: [PATCH] new dcgan architecture --- ch17/ch17_optional_DCGAN.ipynb | 534 ++++++++++++--------------------- ch17/ch17_optional_DCGAN.py | 517 +++++++++++++++++++++++++++++++ 2 files changed, 709 insertions(+), 342 deletions(-) create mode 100644 ch17/ch17_optional_DCGAN.py diff --git a/ch17/ch17_optional_DCGAN.ipynb b/ch17/ch17_optional_DCGAN.ipynb index fe696325..23e2dcb8 100644 --- a/ch17/ch17_optional_DCGAN.ipynb +++ b/ch17/ch17_optional_DCGAN.ipynb @@ -27,7 +27,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 1, "metadata": {}, "outputs": [ { @@ -35,13 +35,13 @@ "output_type": "stream", "text": [ "Sebastian Raschka & Vahid Mirjalili \n", - "last updated: 2019-11-04 \n", + "last updated: 2019-11-06 \n", "\n", - "numpy 1.17.3\n", - "scipy 1.3.1\n", - "matplotlib 3.1.1\n", + "numpy 1.17.2\n", + "scipy 1.2.1\n", + "matplotlib 3.1.0\n", "tensorflow 2.0.0\n", - "tensorflow_datasets 1.2.0\n" + "tensorflow_datasets 1.3.0\n" ] } ], @@ -52,7 +52,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -62,7 +62,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 3, "metadata": { "colab": { "base_uri": "https://localhost:8080/", @@ -91,7 +91,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 4, "metadata": { "colab": { "base_uri": "https://localhost:8080/", @@ -120,7 +120,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 5, "metadata": { "colab": { "base_uri": "https://localhost:8080/", @@ -152,7 +152,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 6, "metadata": { "colab": { "base_uri": "https://localhost:8080/", @@ -179,8 +179,8 @@ "output_type": "stream", "text": [ "2.0.0\n", - "GPU Available: False\n", - "cpu:0\n" + "GPU Available: True\n", + "/device:GPU:0\n" ] } ], @@ -207,7 +207,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -217,7 +217,7 @@ "" ] }, - "execution_count": 15, + "execution_count": 7, "metadata": { "image/png": { "width": 700 @@ -230,64 +230,9 @@ "Image(filename='images/17_12.png', width=700)\n" ] }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "def make_dcgan_generator(\n", - " z_size=20, \n", - " output_size=(28, 28, 1),\n", - " n_filters=64, \n", - " n_blocks=2):\n", - " size_factor = 2**n_blocks\n", - " hidden_size = (\n", - " output_size[0]//size_factor, \n", - " output_size[1]//size_factor\n", - " )\n", - " \n", - " model = tf.keras.Sequential([\n", - " tf.keras.layers.Input(shape=(z_size,)),\n", - " \n", - " tf.keras.layers.Dense(\n", - " units=n_filters*np.prod(hidden_size), \n", - " use_bias=False),\n", - " \n", - " tf.keras.layers.BatchNormalization(),\n", - " tf.keras.layers.LeakyReLU(),\n", - " tf.keras.layers.Reshape(\n", - " (hidden_size[0], hidden_size[1], n_filters)),\n", - " \n", - " tf.keras.layers.Conv2DTranspose(\n", - " filters=n_filters, kernel_size=(3, 3), strides=(1, 1),\n", - " padding='same', use_bias=False),\n", - " tf.keras.layers.BatchNormalization(),\n", - " tf.keras.layers.LeakyReLU()\n", - " ])\n", - " \n", - " nf = n_filters\n", - " for i in range(n_blocks):\n", - " nf = nf // 2\n", - " model.add(\n", - " tf.keras.layers.Conv2DTranspose(\n", - " filters=nf, kernel_size=(3, 3), strides=(2, 2),\n", - " padding='same', use_bias=False))\n", - " \n", - " model.add(tf.keras.layers.BatchNormalization())\n", - " \n", - " model.add(tf.keras.layers.LeakyReLU())\n", - " \n", - " model.add(\n", - " tf.keras.layers.Conv2DTranspose(\n", - " filters=output_size[2], kernel_size=(5, 5), \n", - " strides=(1, 1), padding='same', use_bias=True, \n", - " activation='tanh'))\n", - " \n", - " return model" - ] - }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -306,14 +251,10 @@ " )\n", " model.add(tf.keras.layers.BatchNormalization())\n", " model.add(tf.keras.layers.LeakyReLU(alpha=0.0001))\n", - " \n", - " print(model.compute_output_shape((None, z_size)))\n", "\n", " model.add(tf.keras.layers.Reshape(\n", " target_shape=(hidden_size[0], hidden_size[1], n_filters))\n", " )\n", - " \n", - " print(model.compute_output_shape((None, z_size)))\n", "\n", " # 7x7x64 ==> 14*14*32\n", " model.add(tf.keras.layers.Conv2DTranspose(\n", @@ -324,8 +265,6 @@ " model.add(tf.keras.layers.LeakyReLU(alpha=0.0001))\n", " model.add(tf.keras.layers.Dropout(0.5))\n", " \n", - " print(model.compute_output_shape((None, z_size)))\n", - " \n", " # 14x14x32 ==> 28x28x16\n", " model.add(tf.keras.layers.Conv2DTranspose(\n", " filters=n_filters//4, kernel_size=(3, 3), strides=(2, 2),\n", @@ -334,8 +273,6 @@ " model.add(tf.keras.layers.BatchNormalization())\n", " model.add(tf.keras.layers.LeakyReLU(alpha=0.0001))\n", " model.add(tf.keras.layers.Dropout(0.5))\n", - "\n", - " print(model.compute_output_shape((None, z_size)))\n", " \n", " # 28x28x16 ==> 28x28x8\n", " model.add(tf.keras.layers.Conv2DTranspose(\n", @@ -346,71 +283,61 @@ " model.add(tf.keras.layers.LeakyReLU(alpha=0.0001))\n", " model.add(tf.keras.layers.Dropout(0.5))\n", "\n", - " print(model.compute_output_shape((None, z_size)))\n", - "\n", " # 28x28x8 ==> 28x28x1\n", " model.add(tf.keras.layers.Conv2DTranspose(\n", " filters=1, kernel_size=(3, 3), strides=(1, 1),\n", " padding='same', use_bias=False, activation='tanh')\n", " )\n", "\n", - " print(model.compute_output_shape((None, z_size)))\n", - "\n", " return model" ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "(None, 3136)\n", - "(None, 7, 7, 64)\n", - "(None, 14, 14, 32)\n", - "(None, 28, 28, 16)\n", - "(None, 28, 28, 8)\n", - "(None, 28, 28, 1)\n", - "Model: \"sequential_6\"\n", + "Model: \"sequential\"\n", "_________________________________________________________________\n", "Layer (type) Output Shape Param # \n", "=================================================================\n", - "dense_6 (Dense) multiple 62720 \n", + "dense (Dense) multiple 62720 \n", "_________________________________________________________________\n", - "batch_normalization_17 (Batc multiple 12544 \n", + "batch_normalization (BatchNo multiple 12544 \n", "_________________________________________________________________\n", - "leaky_re_lu_15 (LeakyReLU) multiple 0 \n", + "leaky_re_lu (LeakyReLU) multiple 0 \n", "_________________________________________________________________\n", - "reshape_4 (Reshape) multiple 0 \n", + "reshape (Reshape) multiple 0 \n", "_________________________________________________________________\n", - "conv2d_transpose_14 (Conv2DT multiple 18432 \n", + "conv2d_transpose (Conv2DTran multiple 18432 \n", "_________________________________________________________________\n", - "batch_normalization_18 (Batc multiple 128 \n", + "batch_normalization_1 (Batch multiple 128 \n", "_________________________________________________________________\n", - "leaky_re_lu_16 (LeakyReLU) multiple 0 \n", + "leaky_re_lu_1 (LeakyReLU) multiple 0 \n", "_________________________________________________________________\n", - "dropout_10 (Dropout) multiple 0 \n", + "dropout (Dropout) multiple 0 \n", "_________________________________________________________________\n", - "conv2d_transpose_15 (Conv2DT multiple 4608 \n", + "conv2d_transpose_1 (Conv2DTr multiple 4608 \n", "_________________________________________________________________\n", - "batch_normalization_19 (Batc multiple 64 \n", + "batch_normalization_2 (Batch multiple 64 \n", "_________________________________________________________________\n", - "leaky_re_lu_17 (LeakyReLU) multiple 0 \n", + "leaky_re_lu_2 (LeakyReLU) multiple 0 \n", "_________________________________________________________________\n", - "dropout_11 (Dropout) multiple 0 \n", + "dropout_1 (Dropout) multiple 0 \n", "_________________________________________________________________\n", - "conv2d_transpose_16 (Conv2DT multiple 1152 \n", + "conv2d_transpose_2 (Conv2DTr multiple 1152 \n", "_________________________________________________________________\n", - "batch_normalization_20 (Batc multiple 32 \n", + "batch_normalization_3 (Batch multiple 32 \n", "_________________________________________________________________\n", - "leaky_re_lu_18 (LeakyReLU) multiple 0 \n", + "leaky_re_lu_3 (LeakyReLU) multiple 0 \n", "_________________________________________________________________\n", - "dropout_12 (Dropout) multiple 0 \n", + "dropout_2 (Dropout) multiple 0 \n", "_________________________________________________________________\n", - "conv2d_transpose_17 (Conv2DT multiple 72 \n", + "conv2d_transpose_3 (Conv2DTr multiple 72 \n", "=================================================================\n", "Total params: 99,752\n", "Trainable params: 93,368\n", @@ -427,7 +354,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 10, "metadata": {}, "outputs": [ { @@ -437,7 +364,7 @@ "" ] }, - "execution_count": 18, + "execution_count": 10, "metadata": { "image/png": { "width": 700 @@ -447,59 +374,12 @@ } ], "source": [ - "Image(filename='images/17_13.png', width=700)\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "colab": {}, - "colab_type": "code", - "id": "O9QIFmPZ3jjg" - }, - "source": [ - "\n", - "\n", - "def make_dcgan_discriminator(\n", - " input_size=(28, 28, 1),\n", - " n_filters=16, \n", - " n_blocks=2):\n", - " \n", - " model = tf.keras.Sequential()\n", - " model.add(tf.keras.layers.Input(shape=input_size))\n", - " # [tf.keras.layers.Input(shape=input_size),\n", - " # tf.keras.layers.Conv2D(\n", - " # filters=n_filters, kernel_size=5, \n", - " # strides=(2, 2), padding='same', use_bias=False),\n", - " # tf.keras.layers.BatchNormalization(),\n", - " ## tf.keras.layers.LeakyReLU(),\n", - " # model.add(tf.keras.layers.Dropout(0.5)\n", - " #])\n", - " \n", - " nf = n_filters\n", - " for i in range(n_blocks):\n", - " model.add(\n", - " tf.keras.layers.Conv2D(\n", - " filters=nf, kernel_size=(3, 3), \n", - " strides=(2, 2),padding='same', use_bias=False))\n", - " model.add(tf.keras.layers.BatchNormalization())\n", - " model.add(tf.keras.layers.LeakyReLU())\n", - " model.add(tf.keras.layers.Dropout(0.5))\n", - " nf = nf*2\n", - " \n", - " model.add(tf.keras.layers.Conv2D(\n", - " filters=1, kernel_size=(7, 7), padding='valid',\n", - " use_bias=True, activation=None))\n", - " \n", - " model.add(tf.keras.layers.Reshape((1,)))\n", - " \n", - " return model" + "Image(filename='images/17_13.png', width=700)" ] }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ @@ -514,7 +394,6 @@ " model.add(tf.keras.layers.Reshape(\n", " target_shape=(input_size[0], input_size[1], input_size[2]))\n", " )\n", - " print(model.compute_output_shape((None, *input_size)))\n", "\n", " # 7x7x64 ==> 14*14*32\n", " model.add(tf.keras.layers.Conv2D(\n", @@ -525,8 +404,6 @@ " model.add(tf.keras.layers.LeakyReLU(alpha=0.0001))\n", " model.add(tf.keras.layers.Dropout(0.5))\n", " \n", - " print(model.compute_output_shape((None, *input_size)))\n", - " \n", " # 14x14x32 ==> 28x28x16\n", " model.add(tf.keras.layers.Conv2D(\n", " filters=n_filters//2, kernel_size=(3, 3), strides=(2, 2),\n", @@ -536,26 +413,20 @@ " model.add(tf.keras.layers.LeakyReLU(alpha=0.0001))\n", " model.add(tf.keras.layers.Dropout(0.5))\n", "\n", - " print(model.compute_output_shape((None, *input_size)))\n", - "\n", " model.add(tf.keras.layers.Reshape(\n", " target_shape=(np.prod([input_size[0]//4, input_size[1]//4, n_filters//2]),))\n", " )\n", " \n", - " print(model.compute_output_shape((None, *input_size)))\n", - " \n", " model.add(tf.keras.layers.Dense(\n", " units=1, use_bias=False)\n", " )\n", "\n", - " print(model.compute_output_shape((None, *input_size)))\n", - "\n", " return model" ] }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 12, "metadata": { "colab": { "base_uri": "https://localhost:8080/", @@ -581,36 +452,31 @@ "name": "stdout", "output_type": "stream", "text": [ - "(None, 28, 28, 1)\n", - "(None, 14, 14, 8)\n", - "(None, 7, 7, 32)\n", - "(None, 1568)\n", - "(None, 1)\n", - "Model: \"sequential_11\"\n", + "Model: \"sequential_1\"\n", "_________________________________________________________________\n", "Layer (type) Output Shape Param # \n", "=================================================================\n", - "reshape_12 (Reshape) multiple 0 \n", + "reshape_1 (Reshape) multiple 0 \n", "_________________________________________________________________\n", - "conv2d_7 (Conv2D) multiple 72 \n", + "conv2d (Conv2D) multiple 72 \n", "_________________________________________________________________\n", - "batch_normalization_28 (Batc multiple 32 \n", + "batch_normalization_4 (Batch multiple 32 \n", "_________________________________________________________________\n", - "leaky_re_lu_26 (LeakyReLU) multiple 0 \n", + "leaky_re_lu_4 (LeakyReLU) multiple 0 \n", "_________________________________________________________________\n", - "dropout_20 (Dropout) multiple 0 \n", + "dropout_3 (Dropout) multiple 0 \n", "_________________________________________________________________\n", - "conv2d_8 (Conv2D) multiple 2304 \n", + "conv2d_1 (Conv2D) multiple 2304 \n", "_________________________________________________________________\n", - "batch_normalization_29 (Batc multiple 128 \n", + "batch_normalization_5 (Batch multiple 128 \n", "_________________________________________________________________\n", - "leaky_re_lu_27 (LeakyReLU) multiple 0 \n", + "leaky_re_lu_5 (LeakyReLU) multiple 0 \n", "_________________________________________________________________\n", - "dropout_21 (Dropout) multiple 0 \n", + "dropout_4 (Dropout) multiple 0 \n", "_________________________________________________________________\n", - "reshape_13 (Reshape) multiple 0 \n", + "reshape_2 (Reshape) multiple 0 \n", "_________________________________________________________________\n", - "dense_8 (Dense) multiple 1568 \n", + "dense_1 (Dense) multiple 1568 \n", "=================================================================\n", "Total params: 4,104\n", "Trainable params: 4,024\n", @@ -620,8 +486,6 @@ } ], "source": [ - "\n", - "\n", "disc_model = make_dcgan_discriminator()\n", "disc_model.build(input_shape=(None, 28, 28, 1))\n", "disc_model.summary()" @@ -636,7 +500,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 13, "metadata": { "colab": { "base_uri": "https://localhost:8080/", @@ -693,11 +557,10 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ - "\n", "num_epochs = 100\n", "batch_size = 64\n", "image_size = (28, 28)\n", @@ -732,9 +595,12 @@ " lambda ex: preprocess(ex, mode=mode_z))\n", "\n", "mnist_trainset = mnist_trainset.shuffle(10000)\n", + "\n", + "#mnist_trainset = mnist_trainset.batch(\n", + "# batch_size, drop_remainder=True)\n", + "\n", "mnist_trainset = mnist_trainset.batch(\n", - " batch_size, drop_remainder=True)\n", - "\n" + " batch_size, drop_remainder=True).prefetch(tf.data.experimental.AUTOTUNE)" ] }, { @@ -746,136 +612,126 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "(None, 3136)\n", - "(None, 7, 7, 64)\n", - "(None, 14, 14, 32)\n", - "(None, 28, 28, 16)\n", - "(None, 28, 28, 8)\n", - "(None, 28, 28, 1)\n", - "(None, 28, 28, 1)\n", - "(None, 14, 14, 8)\n", - "(None, 7, 7, 32)\n", - "(None, 1568)\n", - "(None, 1)\n", - "Epoch 001 | ET 0.02 min | Avg Losses >> G/D 0.9679/1.8191 [D-Real: 0.9502 D-Fake: 0.8689]\n", - "Epoch 002 | ET 0.05 min | Avg Losses >> G/D 0.8301/1.7114 [D-Real: 0.5024 D-Fake: 1.2090]\n", - "Epoch 003 | ET 0.08 min | Avg Losses >> G/D 0.7296/1.4192 [D-Real: 0.5160 D-Fake: 0.9032]\n", - "Epoch 004 | ET 0.10 min | Avg Losses >> G/D 0.7307/1.2728 [D-Real: 0.4649 D-Fake: 0.8079]\n", - "Epoch 005 | ET 0.13 min | Avg Losses >> G/D 0.8306/1.4187 [D-Real: 0.5127 D-Fake: 0.9059]\n", - "Epoch 006 | ET 0.16 min | Avg Losses >> G/D 0.7892/1.2391 [D-Real: 0.5841 D-Fake: 0.6550]\n", - "Epoch 007 | ET 0.18 min | Avg Losses >> G/D 1.0004/1.2078 [D-Real: 0.4549 D-Fake: 0.7530]\n", - "Epoch 008 | ET 0.21 min | Avg Losses >> G/D 0.8834/1.1440 [D-Real: 0.4708 D-Fake: 0.6732]\n", - "Epoch 009 | ET 0.24 min | Avg Losses >> G/D 1.1597/1.1740 [D-Real: 0.4377 D-Fake: 0.7363]\n", - "Epoch 010 | ET 0.26 min | Avg Losses >> G/D 1.0251/1.0580 [D-Real: 0.3267 D-Fake: 0.7313]\n", - "Epoch 011 | ET 0.29 min | Avg Losses >> G/D 0.9642/0.9563 [D-Real: 0.4066 D-Fake: 0.5497]\n", - "Epoch 012 | ET 0.31 min | Avg Losses >> G/D 1.1879/1.2914 [D-Real: 0.6752 D-Fake: 0.6162]\n", - "Epoch 013 | ET 0.34 min | Avg Losses >> G/D 1.0150/1.3947 [D-Real: 0.6365 D-Fake: 0.7582]\n", - "Epoch 014 | ET 0.36 min | Avg Losses >> G/D 1.0017/1.3073 [D-Real: 0.6649 D-Fake: 0.6424]\n", - "Epoch 015 | ET 0.39 min | Avg Losses >> G/D 1.0690/1.2905 [D-Real: 0.6280 D-Fake: 0.6625]\n", - "Epoch 016 | ET 0.41 min | Avg Losses >> G/D 1.0558/1.5397 [D-Real: 0.8485 D-Fake: 0.6912]\n", - "Epoch 017 | ET 0.43 min | Avg Losses >> G/D 1.2415/1.4538 [D-Real: 0.8512 D-Fake: 0.6027]\n", - "Epoch 018 | ET 0.45 min | Avg Losses >> G/D 1.3488/1.0646 [D-Real: 0.5617 D-Fake: 0.5028]\n", - "Epoch 019 | ET 0.48 min | Avg Losses >> G/D 1.0452/1.2157 [D-Real: 0.5340 D-Fake: 0.6816]\n", - "Epoch 020 | ET 0.50 min | Avg Losses >> G/D 0.9865/1.3803 [D-Real: 0.6450 D-Fake: 0.7353]\n", - "Epoch 021 | ET 0.53 min | Avg Losses >> G/D 0.7513/1.2003 [D-Real: 0.4808 D-Fake: 0.7195]\n", - "Epoch 022 | ET 0.56 min | Avg Losses >> G/D 1.0232/1.0885 [D-Real: 0.3661 D-Fake: 0.7224]\n", - "Epoch 023 | ET 0.58 min | Avg Losses >> G/D 1.5241/1.1690 [D-Real: 0.5414 D-Fake: 0.6276]\n", - "Epoch 024 | ET 0.60 min | Avg Losses >> G/D 1.7852/1.0307 [D-Real: 0.5453 D-Fake: 0.4854]\n", - "Epoch 025 | ET 0.63 min | Avg Losses >> G/D 2.2540/0.9616 [D-Real: 0.6329 D-Fake: 0.3287]\n", - "Epoch 026 | ET 0.65 min | Avg Losses >> G/D 1.9983/0.7554 [D-Real: 0.3732 D-Fake: 0.3822]\n", - "Epoch 027 | ET 0.68 min | Avg Losses >> G/D 1.9499/0.6046 [D-Real: 0.2423 D-Fake: 0.3624]\n", - "Epoch 028 | ET 0.71 min | Avg Losses >> G/D 2.1818/0.6039 [D-Real: 0.2693 D-Fake: 0.3346]\n", - "Epoch 029 | ET 0.74 min | Avg Losses >> G/D 2.1325/0.6343 [D-Real: 0.3253 D-Fake: 0.3090]\n", - "Epoch 030 | ET 0.76 min | Avg Losses >> G/D 1.1791/0.7710 [D-Real: 0.2358 D-Fake: 0.5351]\n", - "Epoch 031 | ET 0.79 min | Avg Losses >> G/D 1.4316/0.7393 [D-Real: 0.3391 D-Fake: 0.4002]\n", - "Epoch 032 | ET 0.81 min | Avg Losses >> G/D 1.5051/0.7856 [D-Real: 0.2834 D-Fake: 0.5022]\n", - "Epoch 033 | ET 0.84 min | Avg Losses >> G/D 1.5408/1.0971 [D-Real: 0.6737 D-Fake: 0.4234]\n", - "Epoch 034 | ET 0.86 min | Avg Losses >> G/D 1.8426/0.8144 [D-Real: 0.4867 D-Fake: 0.3277]\n", - "Epoch 035 | ET 0.88 min | Avg Losses >> G/D 1.5406/0.8945 [D-Real: 0.6024 D-Fake: 0.2921]\n", - "Epoch 036 | ET 0.91 min | Avg Losses >> G/D 1.6541/0.7236 [D-Real: 0.4057 D-Fake: 0.3179]\n", - "Epoch 037 | ET 0.93 min | Avg Losses >> G/D 1.3306/0.9658 [D-Real: 0.4549 D-Fake: 0.5109]\n", - "Epoch 038 | ET 0.96 min | Avg Losses >> G/D 1.7937/0.6214 [D-Real: 0.2963 D-Fake: 0.3251]\n", - "Epoch 039 | ET 0.98 min | Avg Losses >> G/D 1.7667/0.6594 [D-Real: 0.1860 D-Fake: 0.4734]\n", - "Epoch 040 | ET 1.01 min | Avg Losses >> G/D 1.8878/0.6767 [D-Real: 0.3794 D-Fake: 0.2973]\n", - "Epoch 041 | ET 1.04 min | Avg Losses >> G/D 2.9364/0.5544 [D-Real: 0.3553 D-Fake: 0.1991]\n", - "Epoch 042 | ET 1.06 min | Avg Losses >> G/D 2.1003/0.5165 [D-Real: 0.2586 D-Fake: 0.2579]\n", - "Epoch 043 | ET 1.08 min | Avg Losses >> G/D 2.2725/0.6405 [D-Real: 0.3554 D-Fake: 0.2851]\n", - "Epoch 044 | ET 1.11 min | Avg Losses >> G/D 1.9844/0.5991 [D-Real: 0.2336 D-Fake: 0.3655]\n", - "Epoch 045 | ET 1.14 min | Avg Losses >> G/D 2.1647/0.5339 [D-Real: 0.2636 D-Fake: 0.2704]\n", - "Epoch 046 | ET 1.16 min | Avg Losses >> G/D 2.2159/0.6072 [D-Real: 0.1876 D-Fake: 0.4196]\n", - "Epoch 047 | ET 1.19 min | Avg Losses >> G/D 2.2117/0.5072 [D-Real: 0.2795 D-Fake: 0.2277]\n", - "Epoch 048 | ET 1.21 min | Avg Losses >> G/D 2.2858/0.7156 [D-Real: 0.3275 D-Fake: 0.3881]\n", - "Epoch 049 | ET 1.24 min | Avg Losses >> G/D 2.1452/0.5571 [D-Real: 0.3366 D-Fake: 0.2205]\n", - "Epoch 050 | ET 1.27 min | Avg Losses >> G/D 1.8323/1.1450 [D-Real: 0.5285 D-Fake: 0.6165]\n", - "Epoch 051 | ET 1.29 min | Avg Losses >> G/D 1.7796/1.1325 [D-Real: 0.6822 D-Fake: 0.4503]\n", - "Epoch 052 | ET 1.32 min | Avg Losses >> G/D 1.9502/1.3841 [D-Real: 0.9983 D-Fake: 0.3859]\n", - "Epoch 053 | ET 1.34 min | Avg Losses >> G/D 1.4218/1.5957 [D-Real: 0.7020 D-Fake: 0.8937]\n", - "Epoch 054 | ET 1.37 min | Avg Losses >> G/D 0.8225/1.5191 [D-Real: 0.6772 D-Fake: 0.8419]\n", - "Epoch 055 | ET 1.39 min | Avg Losses >> G/D 0.9367/1.4117 [D-Real: 0.6707 D-Fake: 0.7410]\n", - "Epoch 056 | ET 1.42 min | Avg Losses >> G/D 1.0720/1.5701 [D-Real: 0.7137 D-Fake: 0.8565]\n", - "Epoch 057 | ET 1.45 min | Avg Losses >> G/D 1.0420/1.7670 [D-Real: 0.5299 D-Fake: 1.2371]\n", - "Epoch 058 | ET 1.48 min | Avg Losses >> G/D 1.3140/1.6405 [D-Real: 0.8653 D-Fake: 0.7752]\n", - "Epoch 059 | ET 1.50 min | Avg Losses >> G/D 1.2324/1.5356 [D-Real: 0.8082 D-Fake: 0.7274]\n", - "Epoch 060 | ET 1.53 min | Avg Losses >> G/D 1.5095/1.1937 [D-Real: 0.3565 D-Fake: 0.8372]\n", - "Epoch 061 | ET 1.55 min | Avg Losses >> G/D 1.6141/1.3190 [D-Real: 0.7341 D-Fake: 0.5849]\n", - "Epoch 062 | ET 1.57 min | Avg Losses >> G/D 1.9320/1.1335 [D-Real: 0.7102 D-Fake: 0.4234]\n", - "Epoch 063 | ET 1.59 min | Avg Losses >> G/D 1.8270/1.1795 [D-Real: 0.5615 D-Fake: 0.6180]\n", - "Epoch 064 | ET 1.62 min | Avg Losses >> G/D 1.6218/0.8507 [D-Real: 0.3138 D-Fake: 0.5369]\n", - "Epoch 065 | ET 1.65 min | Avg Losses >> G/D 1.6893/0.9168 [D-Real: 0.4542 D-Fake: 0.4626]\n", - "Epoch 066 | ET 1.67 min | Avg Losses >> G/D 1.7396/0.8148 [D-Real: 0.3940 D-Fake: 0.4208]\n", - "Epoch 067 | ET 1.70 min | Avg Losses >> G/D 2.5805/0.7244 [D-Real: 0.5076 D-Fake: 0.2167]\n", - "Epoch 068 | ET 1.73 min | Avg Losses >> G/D 2.0447/0.6292 [D-Real: 0.3990 D-Fake: 0.2302]\n", - "Epoch 069 | ET 1.76 min | Avg Losses >> G/D 1.8876/0.5063 [D-Real: 0.2470 D-Fake: 0.2592]\n", - "Epoch 070 | ET 1.78 min | Avg Losses >> G/D 2.0404/0.6406 [D-Real: 0.2153 D-Fake: 0.4253]\n", - "Epoch 071 | ET 1.81 min | Avg Losses >> G/D 2.1025/0.6257 [D-Real: 0.3410 D-Fake: 0.2847]\n", - "Epoch 072 | ET 1.83 min | Avg Losses >> G/D 2.2874/0.6604 [D-Real: 0.3222 D-Fake: 0.3382]\n", - "Epoch 073 | ET 1.86 min | Avg Losses >> G/D 1.6613/1.1022 [D-Real: 0.3937 D-Fake: 0.7085]\n", - "Epoch 074 | ET 1.88 min | Avg Losses >> G/D 1.5143/1.2422 [D-Real: 0.7030 D-Fake: 0.5392]\n", - "Epoch 075 | ET 1.90 min | Avg Losses >> G/D 1.3990/1.3495 [D-Real: 1.0116 D-Fake: 0.3378]\n", - "Epoch 076 | ET 1.93 min | Avg Losses >> G/D 0.7597/3.2018 [D-Real: 1.3266 D-Fake: 1.8752]\n", - "Epoch 077 | ET 1.95 min | Avg Losses >> G/D 0.3170/3.7426 [D-Real: 0.8799 D-Fake: 2.8627]\n", - "Epoch 078 | ET 1.98 min | Avg Losses >> G/D 0.6403/3.1735 [D-Real: 1.5082 D-Fake: 1.6653]\n", - "Epoch 079 | ET 2.00 min | Avg Losses >> G/D 1.6515/2.1266 [D-Real: 1.5192 D-Fake: 0.6074]\n", - "Epoch 080 | ET 2.03 min | Avg Losses >> G/D 2.3499/1.2471 [D-Real: 0.9909 D-Fake: 0.2562]\n", - "Epoch 081 | ET 2.05 min | Avg Losses >> G/D 1.9184/0.8801 [D-Real: 0.4801 D-Fake: 0.4000]\n", - "Epoch 082 | ET 2.08 min | Avg Losses >> G/D 1.0375/0.8797 [D-Real: 0.2484 D-Fake: 0.6313]\n", - "Epoch 083 | ET 2.10 min | Avg Losses >> G/D 0.9910/1.4697 [D-Real: 0.4218 D-Fake: 1.0480]\n", - "Epoch 084 | ET 2.13 min | Avg Losses >> G/D 1.4655/1.0101 [D-Real: 0.5323 D-Fake: 0.4778]\n", - "Epoch 085 | ET 2.15 min | Avg Losses >> G/D 2.2822/1.3068 [D-Real: 1.0131 D-Fake: 0.2937]\n", - "Epoch 086 | ET 2.18 min | Avg Losses >> G/D 1.4969/0.8677 [D-Real: 0.4345 D-Fake: 0.4332]\n", - "Epoch 087 | ET 2.20 min | Avg Losses >> G/D 1.4758/1.0396 [D-Real: 0.6140 D-Fake: 0.4257]\n", - "Epoch 088 | ET 2.23 min | Avg Losses >> G/D 1.6664/0.9983 [D-Real: 0.4647 D-Fake: 0.5336]\n", - "Epoch 089 | ET 2.26 min | Avg Losses >> G/D 1.7536/1.1249 [D-Real: 0.6140 D-Fake: 0.5108]\n", - "Epoch 090 | ET 2.28 min | Avg Losses >> G/D 1.3702/1.2308 [D-Real: 0.6393 D-Fake: 0.5915]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 091 | ET 2.31 min | Avg Losses >> G/D 1.2233/1.2756 [D-Real: 0.5037 D-Fake: 0.7719]\n", - "Epoch 092 | ET 2.34 min | Avg Losses >> G/D 1.4475/1.3191 [D-Real: 0.6401 D-Fake: 0.6790]\n", - "Epoch 093 | ET 2.37 min | Avg Losses >> G/D 1.9619/1.5093 [D-Real: 0.8096 D-Fake: 0.6997]\n", - "Epoch 094 | ET 2.39 min | Avg Losses >> G/D 1.6718/1.3646 [D-Real: 0.8153 D-Fake: 0.5493]\n", - "Epoch 095 | ET 2.42 min | Avg Losses >> G/D 1.4617/1.1160 [D-Real: 0.6126 D-Fake: 0.5034]\n", - "Epoch 096 | ET 2.44 min | Avg Losses >> G/D 1.3098/1.5227 [D-Real: 0.8559 D-Fake: 0.6667]\n", - "Epoch 097 | ET 2.47 min | Avg Losses >> G/D 0.9726/1.0533 [D-Real: 0.5013 D-Fake: 0.5520]\n", - "Epoch 098 | ET 2.50 min | Avg Losses >> G/D 1.1679/1.4432 [D-Real: 0.6131 D-Fake: 0.8301]\n", - "Epoch 099 | ET 2.53 min | Avg Losses >> G/D 1.7074/1.4044 [D-Real: 0.7453 D-Fake: 0.6590]\n", - "Epoch 100 | ET 2.55 min | Avg Losses >> G/D 1.5163/1.2579 [D-Real: 0.6500 D-Fake: 0.6079]\n" + "Epoch 001 | ET 1.17 min | Avg Losses >> G/D 1.4423/1.2245 [D-Real: 0.6096 D-Fake: 0.6149]\n", + "Epoch 002 | ET 2.30 min | Avg Losses >> G/D 1.5769/0.9223 [D-Real: 0.4605 D-Fake: 0.4618]\n", + "Epoch 003 | ET 3.44 min | Avg Losses >> G/D 2.2352/0.5379 [D-Real: 0.2684 D-Fake: 0.2696]\n", + "Epoch 004 | ET 4.58 min | Avg Losses >> G/D 1.4573/1.0198 [D-Real: 0.5179 D-Fake: 0.5020]\n", + "Epoch 005 | ET 5.73 min | Avg Losses >> G/D 1.2001/1.0968 [D-Real: 0.5515 D-Fake: 0.5453]\n", + "Epoch 006 | ET 6.86 min | Avg Losses >> G/D 1.0188/1.2351 [D-Real: 0.6220 D-Fake: 0.6131]\n", + "Epoch 007 | ET 8.01 min | Avg Losses >> G/D 0.9194/1.3020 [D-Real: 0.6565 D-Fake: 0.6454]\n", + "Epoch 008 | ET 9.15 min | Avg Losses >> G/D 0.8732/1.3115 [D-Real: 0.6674 D-Fake: 0.6441]\n", + "Epoch 009 | ET 10.30 min | Avg Losses >> G/D 0.8083/1.3442 [D-Real: 0.6789 D-Fake: 0.6653]\n", + "Epoch 010 | ET 11.45 min | Avg Losses >> G/D 0.7985/1.3474 [D-Real: 0.6790 D-Fake: 0.6684]\n", + "Epoch 011 | ET 12.60 min | Avg Losses >> G/D 0.7744/1.3548 [D-Real: 0.6802 D-Fake: 0.6746]\n", + "Epoch 012 | ET 13.73 min | Avg Losses >> G/D 0.7608/1.3628 [D-Real: 0.6901 D-Fake: 0.6727]\n", + "Epoch 013 | ET 14.88 min | Avg Losses >> G/D 0.7643/1.3544 [D-Real: 0.6801 D-Fake: 0.6743]\n", + "Epoch 014 | ET 16.03 min | Avg Losses >> G/D 0.7413/1.3629 [D-Real: 0.6801 D-Fake: 0.6828]\n", + "Epoch 015 | ET 17.16 min | Avg Losses >> G/D 0.7381/1.3694 [D-Real: 0.6876 D-Fake: 0.6818]\n", + "Epoch 016 | ET 18.30 min | Avg Losses >> G/D 0.7428/1.3662 [D-Real: 0.6866 D-Fake: 0.6796]\n", + "Epoch 017 | ET 19.44 min | Avg Losses >> G/D 0.7345/1.3709 [D-Real: 0.6867 D-Fake: 0.6841]\n", + "Epoch 018 | ET 20.59 min | Avg Losses >> G/D 0.7265/1.3703 [D-Real: 0.6817 D-Fake: 0.6887]\n", + "Epoch 019 | ET 21.74 min | Avg Losses >> G/D 0.7352/1.3672 [D-Real: 0.6819 D-Fake: 0.6853]\n", + "Epoch 020 | ET 22.89 min | Avg Losses >> G/D 0.7174/1.3754 [D-Real: 0.6867 D-Fake: 0.6886]\n", + "Epoch 021 | ET 24.03 min | Avg Losses >> G/D 0.7264/1.3731 [D-Real: 0.6866 D-Fake: 0.6866]\n", + "Epoch 022 | ET 25.17 min | Avg Losses >> G/D 0.7262/1.3714 [D-Real: 0.6843 D-Fake: 0.6871]\n", + "Epoch 023 | ET 26.30 min | Avg Losses >> G/D 0.7128/1.3777 [D-Real: 0.6884 D-Fake: 0.6893]\n", + "Epoch 024 | ET 27.44 min | Avg Losses >> G/D 0.7185/1.3762 [D-Real: 0.6900 D-Fake: 0.6862]\n", + "Epoch 025 | ET 28.59 min | Avg Losses >> G/D 0.7170/1.3745 [D-Real: 0.6844 D-Fake: 0.6901]\n", + "Epoch 026 | ET 29.73 min | Avg Losses >> G/D 0.7170/1.3788 [D-Real: 0.6945 D-Fake: 0.6843]\n", + "Epoch 027 | ET 30.88 min | Avg Losses >> G/D 0.7077/1.3786 [D-Real: 0.6868 D-Fake: 0.6918]\n", + "Epoch 028 | ET 32.02 min | Avg Losses >> G/D 0.7135/1.3797 [D-Real: 0.6939 D-Fake: 0.6858]\n", + "Epoch 029 | ET 33.16 min | Avg Losses >> G/D 0.7091/1.3790 [D-Real: 0.6901 D-Fake: 0.6889]\n", + "Epoch 030 | ET 34.30 min | Avg Losses >> G/D 0.7133/1.3763 [D-Real: 0.6873 D-Fake: 0.6891]\n", + "Epoch 031 | ET 35.45 min | Avg Losses >> G/D 0.7035/1.3791 [D-Real: 0.6849 D-Fake: 0.6943]\n", + "Epoch 032 | ET 36.60 min | Avg Losses >> G/D 0.7056/1.3810 [D-Real: 0.6884 D-Fake: 0.6926]\n", + "Epoch 033 | ET 37.74 min | Avg Losses >> G/D 0.7030/1.3815 [D-Real: 0.6911 D-Fake: 0.6904]\n", + "Epoch 034 | ET 38.89 min | Avg Losses >> G/D 0.7008/1.3812 [D-Real: 0.6886 D-Fake: 0.6926]\n", + "Epoch 035 | ET 40.03 min | Avg Losses >> G/D 0.7035/1.3825 [D-Real: 0.6928 D-Fake: 0.6897]\n", + "Epoch 036 | ET 41.17 min | Avg Losses >> G/D 0.6979/1.3822 [D-Real: 0.6864 D-Fake: 0.6959]\n", + "Epoch 037 | ET 42.32 min | Avg Losses >> G/D 0.7029/1.3806 [D-Real: 0.6884 D-Fake: 0.6922]\n", + "Epoch 038 | ET 43.46 min | Avg Losses >> G/D 0.7034/1.3834 [D-Real: 0.6934 D-Fake: 0.6900]\n", + "Epoch 039 | ET 44.60 min | Avg Losses >> G/D 0.7004/1.3830 [D-Real: 0.6913 D-Fake: 0.6917]\n", + "Epoch 040 | ET 45.75 min | Avg Losses >> G/D 0.7083/1.3784 [D-Real: 0.6892 D-Fake: 0.6891]\n", + "Epoch 041 | ET 46.89 min | Avg Losses >> G/D 0.7068/1.3823 [D-Real: 0.6929 D-Fake: 0.6894]\n", + "Epoch 042 | ET 48.03 min | Avg Losses >> G/D 0.6999/1.3820 [D-Real: 0.6892 D-Fake: 0.6928]\n", + "Epoch 043 | ET 49.18 min | Avg Losses >> G/D 0.6978/1.3831 [D-Real: 0.6893 D-Fake: 0.6938]\n", + "Epoch 044 | ET 50.32 min | Avg Losses >> G/D 0.7251/1.3680 [D-Real: 0.6807 D-Fake: 0.6873]\n", + "Epoch 045 | ET 51.47 min | Avg Losses >> G/D 0.6947/1.3837 [D-Real: 0.6872 D-Fake: 0.6965]\n", + "Epoch 046 | ET 52.62 min | Avg Losses >> G/D 0.6997/1.3836 [D-Real: 0.6900 D-Fake: 0.6936]\n", + "Epoch 047 | ET 53.77 min | Avg Losses >> G/D 0.7068/1.3840 [D-Real: 0.6982 D-Fake: 0.6859]\n", + "Epoch 048 | ET 54.91 min | Avg Losses >> G/D 0.6997/1.3836 [D-Real: 0.6899 D-Fake: 0.6937]\n", + "Epoch 049 | ET 56.05 min | Avg Losses >> G/D 0.6967/1.3852 [D-Real: 0.6917 D-Fake: 0.6935]\n", + "Epoch 050 | ET 57.20 min | Avg Losses >> G/D 0.6986/1.3824 [D-Real: 0.6872 D-Fake: 0.6952]\n", + "Epoch 051 | ET 58.34 min | Avg Losses >> G/D 0.7016/1.3818 [D-Real: 0.6899 D-Fake: 0.6919]\n", + "Epoch 052 | ET 59.49 min | Avg Losses >> G/D 0.6989/1.3854 [D-Real: 0.6935 D-Fake: 0.6919]\n", + "Epoch 053 | ET 60.64 min | Avg Losses >> G/D 0.7013/1.3839 [D-Real: 0.6940 D-Fake: 0.6899]\n", + "Epoch 054 | ET 61.78 min | Avg Losses >> G/D 0.7049/1.3853 [D-Real: 0.7007 D-Fake: 0.6846]\n", + "Epoch 055 | ET 62.92 min | Avg Losses >> G/D 0.7259/1.3617 [D-Real: 0.6717 D-Fake: 0.6899]\n", + "Epoch 056 | ET 64.07 min | Avg Losses >> G/D 0.7057/1.3851 [D-Real: 0.6998 D-Fake: 0.6853]\n", + "Epoch 057 | ET 65.20 min | Avg Losses >> G/D 0.7005/1.3853 [D-Real: 0.6961 D-Fake: 0.6892]\n", + "Epoch 058 | ET 66.34 min | Avg Losses >> G/D 0.6972/1.3847 [D-Real: 0.6921 D-Fake: 0.6925]\n", + "Epoch 059 | ET 67.49 min | Avg Losses >> G/D 0.7129/1.3753 [D-Real: 0.6868 D-Fake: 0.6884]\n", + "Epoch 060 | ET 68.64 min | Avg Losses >> G/D 0.7019/1.3858 [D-Real: 0.6976 D-Fake: 0.6882]\n", + "Epoch 061 | ET 69.79 min | Avg Losses >> G/D 0.6951/1.3855 [D-Real: 0.6917 D-Fake: 0.6938]\n", + "Epoch 062 | ET 70.95 min | Avg Losses >> G/D 0.6983/1.3851 [D-Real: 0.6944 D-Fake: 0.6907]\n", + "Epoch 063 | ET 72.10 min | Avg Losses >> G/D 0.6969/1.3857 [D-Real: 0.6935 D-Fake: 0.6922]\n", + "Epoch 064 | ET 73.25 min | Avg Losses >> G/D 0.6981/1.3853 [D-Real: 0.6948 D-Fake: 0.6905]\n", + "Epoch 065 | ET 74.40 min | Avg Losses >> G/D 0.7005/1.3845 [D-Real: 0.6952 D-Fake: 0.6892]\n", + "Epoch 066 | ET 75.56 min | Avg Losses >> G/D 0.7050/1.3830 [D-Real: 0.6959 D-Fake: 0.6871]\n", + "Epoch 067 | ET 76.71 min | Avg Losses >> G/D 0.6947/1.3843 [D-Real: 0.6887 D-Fake: 0.6957]\n", + "Epoch 068 | ET 77.86 min | Avg Losses >> G/D 0.7003/1.3844 [D-Real: 0.6939 D-Fake: 0.6905]\n", + "Epoch 069 | ET 79.01 min | Avg Losses >> G/D 0.6959/1.3851 [D-Real: 0.6917 D-Fake: 0.6933]\n", + "Epoch 070 | ET 80.17 min | Avg Losses >> G/D 0.6996/1.3841 [D-Real: 0.6937 D-Fake: 0.6904]\n", + "Epoch 071 | ET 81.32 min | Avg Losses >> G/D 0.6971/1.3853 [D-Real: 0.6937 D-Fake: 0.6916]\n", + "Epoch 072 | ET 82.47 min | Avg Losses >> G/D 0.7062/1.3841 [D-Real: 0.6992 D-Fake: 0.6849]\n", + "Epoch 073 | ET 83.62 min | Avg Losses >> G/D 0.6978/1.3837 [D-Real: 0.6896 D-Fake: 0.6941]\n", + "Epoch 074 | ET 84.78 min | Avg Losses >> G/D 0.6973/1.3848 [D-Real: 0.6931 D-Fake: 0.6917]\n", + "Epoch 075 | ET 85.94 min | Avg Losses >> G/D 0.6995/1.3847 [D-Real: 0.6945 D-Fake: 0.6902]\n", + "Epoch 076 | ET 87.09 min | Avg Losses >> G/D 0.6966/1.3849 [D-Real: 0.6921 D-Fake: 0.6928]\n", + "Epoch 077 | ET 88.24 min | Avg Losses >> G/D 0.7004/1.3837 [D-Real: 0.6934 D-Fake: 0.6903]\n", + "Epoch 078 | ET 89.39 min | Avg Losses >> G/D 0.6973/1.3851 [D-Real: 0.6924 D-Fake: 0.6927]\n", + "Epoch 079 | ET 90.55 min | Avg Losses >> G/D 0.6972/1.3856 [D-Real: 0.6942 D-Fake: 0.6914]\n", + "Epoch 080 | ET 91.71 min | Avg Losses >> G/D 0.6942/1.3855 [D-Real: 0.6917 D-Fake: 0.6938]\n", + "Epoch 081 | ET 92.86 min | Avg Losses >> G/D 0.6936/1.3848 [D-Real: 0.6889 D-Fake: 0.6959]\n", + "Epoch 082 | ET 94.01 min | Avg Losses >> G/D 0.6967/1.3839 [D-Real: 0.6905 D-Fake: 0.6934]\n", + "Epoch 083 | ET 95.16 min | Avg Losses >> G/D 0.6999/1.3849 [D-Real: 0.6934 D-Fake: 0.6915]\n", + "Epoch 084 | ET 96.32 min | Avg Losses >> G/D 0.6937/1.3835 [D-Real: 0.6871 D-Fake: 0.6964]\n", + "Epoch 085 | ET 97.47 min | Avg Losses >> G/D 0.6967/1.3847 [D-Real: 0.6908 D-Fake: 0.6939]\n", + "Epoch 086 | ET 98.63 min | Avg Losses >> G/D 0.6954/1.3849 [D-Real: 0.6909 D-Fake: 0.6940]\n", + "Epoch 087 | ET 99.78 min | Avg Losses >> G/D 0.7017/1.3851 [D-Real: 0.6972 D-Fake: 0.6879]\n", + "Epoch 088 | ET 100.93 min | Avg Losses >> G/D 0.7004/1.3854 [D-Real: 0.6964 D-Fake: 0.6890]\n", + "Epoch 089 | ET 102.08 min | Avg Losses >> G/D 0.6973/1.3856 [D-Real: 0.6941 D-Fake: 0.6916]\n", + "Epoch 090 | ET 103.21 min | Avg Losses >> G/D 0.6968/1.3852 [D-Real: 0.6932 D-Fake: 0.6920]\n", + "Epoch 091 | ET 104.37 min | Avg Losses >> G/D 0.6957/1.3843 [D-Real: 0.6903 D-Fake: 0.6940]\n", + "Epoch 092 | ET 105.52 min | Avg Losses >> G/D 0.6986/1.3842 [D-Real: 0.6926 D-Fake: 0.6916]\n", + "Epoch 093 | ET 106.68 min | Avg Losses >> G/D 0.7032/1.3860 [D-Real: 0.6996 D-Fake: 0.6863]\n", + "Epoch 094 | ET 107.83 min | Avg Losses >> G/D 0.6995/1.3856 [D-Real: 0.6973 D-Fake: 0.6884]\n", + "Epoch 095 | ET 108.98 min | Avg Losses >> G/D 0.6969/1.3854 [D-Real: 0.6939 D-Fake: 0.6915]\n", + "Epoch 096 | ET 110.14 min | Avg Losses >> G/D 0.6992/1.3852 [D-Real: 0.6958 D-Fake: 0.6893]\n", + "Epoch 097 | ET 111.29 min | Avg Losses >> G/D 0.7088/1.3778 [D-Real: 0.6881 D-Fake: 0.6898]\n", + "Epoch 098 | ET 112.44 min | Avg Losses >> G/D 0.7067/1.3890 [D-Real: 0.7023 D-Fake: 0.6868]\n", + "Epoch 099 | ET 113.59 min | Avg Losses >> G/D 0.6960/1.3856 [D-Real: 0.6938 D-Fake: 0.6918]\n", + "Epoch 100 | ET 114.74 min | Avg Losses >> G/D 0.6959/1.3857 [D-Real: 0.6939 D-Fake: 0.6918]\n" ] } ], "source": [ "import time\n", "\n", + "\n", + "# Delete the previously instantiated\n", + "# objects that we have defined\n", + "# for printing the model summaries\n", + "del gen_model \n", + "del disc_model\n", + "\n", "## Set-up the model\n", "with tf.device(device_name):\n", " gen_model = make_dcgan_generator()\n", @@ -950,7 +806,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "metadata": { "colab": { "base_uri": "https://localhost:8080/", @@ -985,12 +841,12 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 17, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -1060,36 +916,12 @@ }, { "cell_type": "code", - "execution_count": 10, - "metadata": { - "colab": {}, - "colab_type": "code", - "id": "nToA2xUQ6C3h" - }, - "outputs": [ - { - "data": { - "image/png": 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\n", 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\n", 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\n", 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" ] @@ -1121,6 +953,24 @@ "plt.show()" ] }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[NbConvertApp] Converting notebook ch17_optional_DCGAN.ipynb to script\n", + "[NbConvertApp] Writing 15401 bytes to ch17_optional_DCGAN.py\n" + ] + } + ], + "source": [ + "! python ../.convert_notebook_to_script.py --input ch17_optional_DCGAN.ipynb --output ch17_optional_DCGAN.py" + ] + }, { "cell_type": "code", "execution_count": null, @@ -1152,9 +1002,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.7.3" } }, "nbformat": 4, - "nbformat_minor": 1 + "nbformat_minor": 4 } diff --git a/ch17/ch17_optional_DCGAN.py b/ch17/ch17_optional_DCGAN.py new file mode 100644 index 00000000..378ed585 --- /dev/null +++ b/ch17/ch17_optional_DCGAN.py @@ -0,0 +1,517 @@ +# coding: utf-8 + + +# from google.colab import drive +import tensorflow as tf +import tensorflow_datasets as tfds +import numpy as np +import matplotlib.pyplot as plt +import time +import itertools + +# *Python Machine Learning 3rd Edition* by [Sebastian Raschka](https://sebastianraschka.com) & [Vahid Mirjalili](http://vahidmirjalili.com), Packt Publishing Ltd. 2019 +# +# Code Repository: https://github.com/rasbt/python-machine-learning-book-3rd-edition +# +# Code License: [MIT License](https://github.com/rasbt/python-machine-learning-book-3rd-edition/blob/master/LICENSE.txt) + +# # Chapter 17: Generative Adversarial Networks (Optional, DCGAN) + +# Note that the optional watermark extension is a small IPython notebook plugin that I developed to make the code reproducible. You can just skip the following line(s). + + + + + + + + + + + +## For running on Google-Colab +# ! pip install -q tensorflow-gpu==2.0.0 + + + + +# drive.mount('/content/drive/') + + + + + + + + +print(tf.__version__) + +print("GPU Available:", tf.test.is_gpu_available()) + +if tf.test.is_gpu_available(): + device_name = tf.test.gpu_device_name() + +else: + device_name = 'cpu:0' + +print(device_name) + + +# * **Defining the generator and discriminator networks** + + + + + +# def make_dcgan_generator( +# z_size=20, +# output_size=(28, 28, 1), +# n_filters=64, +# n_blocks=2): +# size_factor = 2**n_blocks +# hidden_size = ( +# output_size[0]//size_factor, +# output_size[1]//size_factor +# ) +# +# model = tf.keras.Sequential([ +# tf.keras.layers.Input(shape=(z_size,)), +# +# tf.keras.layers.Dense( +# units=n_filters*np.prod(hidden_size), +# use_bias=False), +# +# tf.keras.layers.BatchNormalization(), +# tf.keras.layers.LeakyReLU(), +# tf.keras.layers.Reshape( +# (hidden_size[0], hidden_size[1], n_filters)), +# +# tf.keras.layers.Conv2DTranspose( +# filters=n_filters, kernel_size=(3, 3), strides=(1, 1), +# padding='same', use_bias=False), +# tf.keras.layers.BatchNormalization(), +# tf.keras.layers.LeakyReLU() +# ]) +# +# nf = n_filters +# for i in range(n_blocks): +# nf = nf // 2 +# model.add( +# tf.keras.layers.Conv2DTranspose( +# filters=nf, kernel_size=(3, 3), strides=(2, 2), +# padding='same', use_bias=False)) +# +# model.add(tf.keras.layers.BatchNormalization()) +# +# model.add(tf.keras.layers.LeakyReLU()) +# +# model.add( +# tf.keras.layers.Conv2DTranspose( +# filters=output_size[2], kernel_size=(5, 5), +# strides=(1, 1), padding='same', use_bias=True, +# activation='tanh')) +# +# return model + + + +def make_dcgan_generator( + z_size=100, + output_size=(28, 28, 1), + n_filters=64): + + hidden_size = (7, 7) + + model = tf.keras.Sequential() + + # 100 ==> 784 ==> 7x7x64 + model.add(tf.keras.layers.Dense( + units=n_filters*np.prod(hidden_size), use_bias=False) + ) + model.add(tf.keras.layers.BatchNormalization()) + model.add(tf.keras.layers.LeakyReLU(alpha=0.0001)) + + model.add(tf.keras.layers.Reshape( + target_shape=(hidden_size[0], hidden_size[1], n_filters)) + ) + + # 7x7x64 ==> 14*14*32 + model.add(tf.keras.layers.Conv2DTranspose( + filters=n_filters//2, kernel_size=(3, 3), strides=(2, 2), + padding='same', use_bias=False, activation=None) + ) + model.add(tf.keras.layers.BatchNormalization()) + model.add(tf.keras.layers.LeakyReLU(alpha=0.0001)) + model.add(tf.keras.layers.Dropout(0.5)) + + # 14x14x32 ==> 28x28x16 + model.add(tf.keras.layers.Conv2DTranspose( + filters=n_filters//4, kernel_size=(3, 3), strides=(2, 2), + padding='same', use_bias=False, activation=None) + ) + model.add(tf.keras.layers.BatchNormalization()) + model.add(tf.keras.layers.LeakyReLU(alpha=0.0001)) + model.add(tf.keras.layers.Dropout(0.5)) + + # 28x28x16 ==> 28x28x8 + model.add(tf.keras.layers.Conv2DTranspose( + filters=n_filters//8, kernel_size=(3, 3), strides=(1, 1), + padding='same', use_bias=False, activation=None) + ) + model.add(tf.keras.layers.BatchNormalization()) + model.add(tf.keras.layers.LeakyReLU(alpha=0.0001)) + model.add(tf.keras.layers.Dropout(0.5)) + + # 28x28x8 ==> 28x28x1 + model.add(tf.keras.layers.Conv2DTranspose( + filters=1, kernel_size=(3, 3), strides=(1, 1), + padding='same', use_bias=False, activation='tanh') + ) + + return model + + + + +gen_model = make_dcgan_generator() +gen_model.build(input_shape=(None, 20)) +gen_model.summary() + + + + + + +# +# +# def make_dcgan_discriminator( +# input_size=(28, 28, 1), +# n_filters=16, +# n_blocks=2): +# +# model = tf.keras.Sequential() +# model.add(tf.keras.layers.Input(shape=input_size)) +# # [tf.keras.layers.Input(shape=input_size), +# # tf.keras.layers.Conv2D( +# # filters=n_filters, kernel_size=5, +# # strides=(2, 2), padding='same', use_bias=False), +# # tf.keras.layers.BatchNormalization(), +# ## tf.keras.layers.LeakyReLU(), +# # model.add(tf.keras.layers.Dropout(0.5) +# #]) +# +# nf = n_filters +# for i in range(n_blocks): +# model.add( +# tf.keras.layers.Conv2D( +# filters=nf, kernel_size=(3, 3), +# strides=(2, 2),padding='same', use_bias=False)) +# model.add(tf.keras.layers.BatchNormalization()) +# model.add(tf.keras.layers.LeakyReLU()) +# model.add(tf.keras.layers.Dropout(0.5)) +# nf = nf*2 +# +# model.add(tf.keras.layers.Conv2D( +# filters=1, kernel_size=(7, 7), padding='valid', +# use_bias=True, activation=None)) +# +# model.add(tf.keras.layers.Reshape((1,))) +# +# return model + + + +def make_dcgan_discriminator( + input_size=(28, 28, 1), + n_filters=64): + + hidden_size = (7, 7) + + model = tf.keras.Sequential() + + model.add(tf.keras.layers.Reshape( + target_shape=(input_size[0], input_size[1], input_size[2])) + ) + + # 7x7x64 ==> 14*14*32 + model.add(tf.keras.layers.Conv2D( + filters=n_filters//8, kernel_size=(3, 3), strides=(2, 2), + padding='same', use_bias=False, activation=None) + ) + model.add(tf.keras.layers.BatchNormalization()) + model.add(tf.keras.layers.LeakyReLU(alpha=0.0001)) + model.add(tf.keras.layers.Dropout(0.5)) + + # 14x14x32 ==> 28x28x16 + model.add(tf.keras.layers.Conv2D( + filters=n_filters//2, kernel_size=(3, 3), strides=(2, 2), + padding='same', use_bias=False, activation=None) + ) + model.add(tf.keras.layers.BatchNormalization()) + model.add(tf.keras.layers.LeakyReLU(alpha=0.0001)) + model.add(tf.keras.layers.Dropout(0.5)) + + model.add(tf.keras.layers.Reshape( + target_shape=(np.prod([input_size[0]//4, input_size[1]//4, n_filters//2]),)) + ) + + model.add(tf.keras.layers.Dense( + units=1, use_bias=False) + ) + + return model + + + + +disc_model = make_dcgan_discriminator() +disc_model.build(input_shape=(None, 28, 28, 1)) +disc_model.summary() + + +# * **Loading and preprocessing the data** + + + +mnist_bldr = tfds.builder('mnist') +mnist_bldr.download_and_prepare() +mnist = mnist_bldr.as_dataset(shuffle_files=False) + +def preprocess(ex, mode='uniform'): + image = ex['image'] + image = tf.image.convert_image_dtype(image, tf.float32) + + image = image*2 - 1.0 + + if mode == 'uniform': + input_z = tf.random.uniform(shape=(z_size,), + minval=-1.0, maxval=1.0) + elif mode == 'normal': + input_z = tf.random.normal(shape=(z_size,)) + return input_z, image + + + + +num_epochs = 100 +batch_size = 64 +image_size = (28, 28) +z_size = 20 +mode_z = 'uniform' +#gen_hidden_layers = 1 +#gen_hidden_size = 100 +#disc_hidden_layers = 1 +#disc_hidden_size = 100 + +tf.random.set_seed(1) +np.random.seed(1) + + +if mode_z == 'uniform': + fixed_z = tf.random.uniform( + shape=(batch_size, z_size), + minval=-1, maxval=1) +elif mode_z == 'normal': + fixed_z = tf.random.normal( + shape=(batch_size, z_size)) + + +def create_samples(g_model, input_z): + g_output = g_model(input_z, training=False) + images = tf.reshape(g_output, (batch_size, *image_size)) + return (images+1)/2.0 + +## Set-up the dataset +mnist_trainset = mnist['train'] +mnist_trainset = mnist_trainset.map( + lambda ex: preprocess(ex, mode=mode_z)) + +mnist_trainset = mnist_trainset.shuffle(10000) + +#mnist_trainset = mnist_trainset.batch( +# batch_size, drop_remainder=True) + +mnist_trainset = mnist_trainset.batch( + batch_size, drop_remainder=True).prefetch(tf.data.experimental.AUTOTUNE) + + +# * **Final Training** + + + + + +# Delete the previously instantiated +# objects that we have defined +# for printing the model summaries +del gen_model +del disc_model + +## Set-up the model +with tf.device(device_name): + gen_model = make_dcgan_generator() + disc_model = make_dcgan_discriminator() + + +## Loss function and optimizers: +loss_fn = tf.keras.losses.BinaryCrossentropy(from_logits=True) +g_optimizer = tf.keras.optimizers.Adam() +d_optimizer = tf.keras.optimizers.Adam() + +all_losses = [] +all_d_vals = [] +epoch_samples = [] + +start_time = time.time() +for epoch in range(1, num_epochs+1): + epoch_losses, epoch_d_vals = [], [] + for i,(input_z,input_real) in enumerate(mnist_trainset): #.take(4) + + ## Compute generator's loss + with tf.GradientTape() as g_tape: + g_output = gen_model(input_z) + d_logits_fake = disc_model(g_output, training=True) + + g_loss = loss_fn(y_true=tf.ones_like(d_logits_fake), + y_pred=d_logits_fake) + + ## > Compute the gradients of g_loss + g_grads = g_tape.gradient(g_loss, gen_model.trainable_variables) + g_optimizer.apply_gradients( + grads_and_vars=zip(g_grads, gen_model.trainable_variables)) + + + ## Compute discriminator's loss + with tf.GradientTape() as d_tape: + d_logits_real = disc_model(input_real, training=True) + + d_logits_fake = disc_model(g_output, training=True) + + d_loss_real = loss_fn(y_true=tf.ones_like(d_logits_real), + y_pred=d_logits_real) + + d_loss_fake = loss_fn(y_true=tf.zeros_like(d_logits_fake), + y_pred=d_logits_fake) + + d_loss = d_loss_real + d_loss_fake + + ## > Compute the gradients of d_loss + d_grads = d_tape.gradient(d_loss, disc_model.trainable_variables) + d_optimizer.apply_gradients( + grads_and_vars=zip(d_grads, disc_model.trainable_variables)) + + epoch_losses.append( + (g_loss.numpy(), d_loss.numpy(), + d_loss_real.numpy(), d_loss_fake.numpy())) + + d_probs_real = tf.reduce_mean(tf.sigmoid(d_logits_real)) + d_probs_fake = tf.reduce_mean(tf.sigmoid(d_logits_fake)) + epoch_d_vals.append((d_probs_real.numpy(), d_probs_fake.numpy())) + all_losses.append(epoch_losses) + all_d_vals.append(epoch_d_vals) + print( + 'Epoch {:03d} | ET {:.2f} min | Avg Losses >>' + ' G/D {:.4f}/{:.4f} [D-Real: {:.4f} D-Fake: {:.4f}]' + .format( + epoch, (time.time() - start_time)/60, + *list(np.mean(all_losses[-1], axis=0)))) + epoch_samples.append( + create_samples(gen_model, fixed_z).numpy()) + + + + +#import pickle +#pickle.dump({'all_losses':all_losses, +# 'all_d_vals':all_d_vals, +# 'samples':epoch_samples}, +# open('/content/drive/My Drive/Colab Notebooks/PyML-3rd-edition/ch17-dcgan-learning.pkl', 'wb')) + +#gen_model.save('/content/drive/My Drive/Colab Notebooks/PyML-3rd-edition/ch17-dcgangan_gen.h5') +#disc_model.save('/content/drive/My Drive/Colab Notebooks/PyML-3rd-edition/ch17-dcgan_disc.h5') + + + + + + +fig = plt.figure(figsize=(16, 6)) + +## Plotting the losses +ax = fig.add_subplot(1, 2, 1) +g_losses = [item[0] for item in itertools.chain(*all_losses)] +d_losses = [item[1]/2.0 for item in itertools.chain(*all_losses)] +plt.plot(g_losses, label='Generator loss', alpha=0.95) +plt.plot(d_losses, label='Discriminator loss', alpha=0.95) +plt.legend(fontsize=20) +ax.set_xlabel('Iteration', size=15) +ax.set_ylabel('Loss', size=15) + +epochs = np.arange(1, 101) +epoch2iter = lambda e: e*len(all_losses[-1]) +epoch_ticks = [1, 20, 40, 60, 80, 100] +newpos = [epoch2iter(e) for e in epoch_ticks] +ax2 = ax.twiny() +ax2.set_xticks(newpos) +ax2.set_xticklabels(epoch_ticks) +ax2.xaxis.set_ticks_position('bottom') +ax2.xaxis.set_label_position('bottom') +ax2.spines['bottom'].set_position(('outward', 60)) +ax2.set_xlabel('Epoch', size=15) +ax2.set_xlim(ax.get_xlim()) +ax.tick_params(axis='both', which='major', labelsize=15) +ax2.tick_params(axis='both', which='major', labelsize=15) + +## Plotting the outputs of the discriminator +ax = fig.add_subplot(1, 2, 2) +d_vals_real = [item[0] for item in itertools.chain(*all_d_vals)] +d_vals_fake = [item[1] for item in itertools.chain(*all_d_vals)] +plt.plot(d_vals_real, alpha=0.75, label=r'Real: $D(\mathbf{x})$') +plt.plot(d_vals_fake, alpha=0.75, label=r'Fake: $D(G(\mathbf{z}))$') +plt.legend(fontsize=20) +ax.set_xlabel('Iteration', size=15) +ax.set_ylabel('Discriminator output', size=15) + +ax2 = ax.twiny() +ax2.set_xticks(newpos) +ax2.set_xticklabels(epoch_ticks) +ax2.xaxis.set_ticks_position('bottom') +ax2.xaxis.set_label_position('bottom') +ax2.spines['bottom'].set_position(('outward', 60)) +ax2.set_xlabel('Epoch', size=15) +ax2.set_xlim(ax.get_xlim()) +ax.tick_params(axis='both', which='major', labelsize=15) +ax2.tick_params(axis='both', which='major', labelsize=15) + + +#plt.savefig('images/ch17-dcgan-learning-curve.pdf') +plt.show() + + + + +selected_epochs = [1, 2, 4, 10, 50, 100] +fig = plt.figure(figsize=(10, 14)) +for i,e in enumerate(selected_epochs): + for j in range(5): + ax = fig.add_subplot(6, 5, i*5+j+1) + ax.set_xticks([]) + ax.set_yticks([]) + if j == 0: + ax.text( + -0.06, 0.5, 'Epoch {}'.format(e), + rotation=90, size=18, color='red', + horizontalalignment='right', + verticalalignment='center', + transform=ax.transAxes) + + image = epoch_samples[e-1][j] + ax.imshow(image, cmap='gray_r') + +#plt.savefig('images/ch17-dcgan-samples.pdf') +plt.show() + + + + +