Merge branch 'master' of github.com:keras-team/keras-io

Author: fchollet

examples/audio/md/stft.md

@@ -605,7 +605,7 @@ plt.show()
 
 
 
-![png](https://github.com/mostafa-mahmoud/keras-io/blob/master/examples/audio/img/stft/raw_audio.png)
+![png](https://github.com/keras-team/keras-io/blob/master/examples/audio/img/stft/raw_audio.png)
 
 
 
@@ -618,7 +618,7 @@ plot_single_spectrogram(sample_wav_data)
 
 
 
-![png](https://github.com/mostafa-mahmoud/keras-io/blob/master/examples/audio/img/stft/spectrogram.png)
+![png](https://github.com/keras-team/keras-io/blob/master/examples/audio/img/stft/spectrogram.png)
 
 
 
@@ -631,7 +631,7 @@ plot_multi_bandwidth_spectrogram(sample_wav_data)
 
 
 
-![png](https://github.com/mostafa-mahmoud/keras-io/blob/master/examples/audio/img/stft/multiband_spectrogram.png)
+![png](https://github.com/keras-team/keras-io/blob/master/examples/audio/img/stft/multiband_spectrogram.png)
 
 
 
@@ -643,9 +643,7 @@ def read_dataset(df, folds):
     msk = df["fold"].isin(folds)
     filenames = df["filename"][msk]
     targets = df["target"][msk].values
-    waves = np.array(
-        [read_wav_file(fil) for fil in filenames], dtype=np.float32
-    )
+    waves = np.array([read_wav_file(fil) for fil in filenames], dtype=np.float32)
     return waves, targets
 ```
 
@@ -1790,7 +1788,7 @@ plt.show()
 
 
 
-![png](https://github.com/mostafa-mahmoud/keras-io/blob/master/examples/audio/img/stft/training.png)
+![png](https://github.com/keras-team/keras-io/blob/master/examples/audio/img/stft/training.png)
 
 
 
@@ -1802,9 +1800,7 @@ Running the models on the test set.
 
 ```python
 _, test_acc = model1d.evaluate(test_x, test_y)
-print(
-    f"1D model wit non-trainable STFT -> Test Accuracy: {test_acc * 100:.2f}%"
-)
+print(f"1D model wit non-trainable STFT -> Test Accuracy: {test_acc * 100:.2f}%")
 ```
 
     3/3 ━━━━━━━━━━━━━━━━━━━━ 3s 307ms/step - accuracy: 0.8148 - loss: 0.6244

examples/keras_recipes/ipynb/reproducibility_recipes.ipynb

@@ -252,8 +252,13 @@
     "    )\n",
     "\n",
     "    model.compile(\n",
-    "        optimizer=\"adam\", loss=\"sparse_categorical_crossentropy\", metrics=[\"accuracy\"]\n",
+    "        optimizer=\"adam\",\n",
+    "        loss=\"sparse_categorical_crossentropy\",\n",
+    "        metrics=[\"accuracy\"],\n",
+    "        jit_compile=False,\n",
     "    )\n",
+    "    # jit_compile's default value is \"auto\" which will cause some problems in some\n",
+    "    # ops, therefore it's set to False.\n",
     "\n",
     "    # model.fit has a `shuffle` parameter which has a default value of `True`.\n",
     "    # If you are using array-like objects, this will shuffle the data before\n",

examples/keras_recipes/md/reproducibility_recipes.md

@@ -87,89 +87,89 @@ for initializer in initializers_list:
 <div class="k-default-codeblock">
 ```
 Running <class 'keras.src.initializers.random_initializers.RandomNormal'>
-	Iteration --> 0 // Result --> 0.05609520897269249
-	Iteration --> 1 // Result --> 0.05609520897269249
+	Iteration --> 0 // Result --> 0.000790853810030967
+	Iteration --> 1 // Result --> 0.000790853810030967
 ```
 </div>
 
 
 <div class="k-default-codeblock">
 ```
 Running <class 'keras.src.initializers.random_initializers.RandomUniform'>
-	Iteration --> 0 // Result --> 0.03690483793616295
-	Iteration --> 1 // Result --> 0.03690483793616295
+	Iteration --> 0 // Result --> -0.02175668440759182
+	Iteration --> 1 // Result --> -0.02175668440759182
 ```
 </div>
 
 
 <div class="k-default-codeblock">
 ```
 Running <class 'keras.src.initializers.random_initializers.TruncatedNormal'>
-	Iteration --> 0 // Result --> 0.05230803042650223
-	Iteration --> 1 // Result --> 0.05230803042650223
+	Iteration --> 0 // Result --> 0.000790853810030967
+	Iteration --> 1 // Result --> 0.000790853810030967
 ```
 </div>
 
 
 <div class="k-default-codeblock">
 ```
 Running <class 'keras.src.initializers.random_initializers.VarianceScaling'>
-	Iteration --> 0 // Result --> 1.1893247365951538
-	Iteration --> 1 // Result --> 1.1893247365951538
+	Iteration --> 0 // Result --> 0.017981600016355515
+	Iteration --> 1 // Result --> 0.017981600016355515
 ```
 </div>
 
 
 <div class="k-default-codeblock">
 ```
 Running <class 'keras.src.initializers.random_initializers.GlorotNormal'>
-	Iteration --> 0 // Result --> 1.1893247365951538
-	Iteration --> 1 // Result --> 1.1893247365951538
+	Iteration --> 0 // Result --> 0.017981600016355515
+	Iteration --> 1 // Result --> 0.017981600016355515
 ```
 </div>
 
 
 <div class="k-default-codeblock">
 ```
 Running <class 'keras.src.initializers.random_initializers.GlorotUniform'>
-	Iteration --> 0 // Result --> 1.2784210443496704
-	Iteration --> 1 // Result --> 1.2784210443496704
+	Iteration --> 0 // Result --> -0.7536736726760864
+	Iteration --> 1 // Result --> -0.7536736726760864
 ```
 </div>
 
 
 <div class="k-default-codeblock">
 ```
 Running <class 'keras.src.initializers.random_initializers.HeNormal'>
-	Iteration --> 0 // Result --> 1.6819592714309692
-	Iteration --> 1 // Result --> 1.6819592714309692
+	Iteration --> 0 // Result --> 0.025429822504520416
+	Iteration --> 1 // Result --> 0.025429822504520416
 ```
 </div>
 
 
 <div class="k-default-codeblock">
 ```
 Running <class 'keras.src.initializers.random_initializers.HeUniform'>
-	Iteration --> 0 // Result --> 1.8079603910446167
-	Iteration --> 1 // Result --> 1.8079603910446167
+	Iteration --> 0 // Result --> -1.065855622291565
+	Iteration --> 1 // Result --> -1.065855622291565
 ```
 </div>
 
 
 <div class="k-default-codeblock">
 ```
 Running <class 'keras.src.initializers.random_initializers.LecunNormal'>
-	Iteration --> 0 // Result --> 1.1893247365951538
-	Iteration --> 1 // Result --> 1.1893247365951538
+	Iteration --> 0 // Result --> 0.017981600016355515
+	Iteration --> 1 // Result --> 0.017981600016355515
 ```
 </div>
 
 
 <div class="k-default-codeblock">
 ```
 Running <class 'keras.src.initializers.random_initializers.LecunUniform'>
-	Iteration --> 0 // Result --> 1.2784210443496704
-	Iteration --> 1 // Result --> 1.2784210443496704
+	Iteration --> 0 // Result --> -0.7536736726760864
+	Iteration --> 1 // Result --> -0.7536736726760864
 ```
 </div>
 
@@ -273,8 +273,13 @@ def train_model(train_data: tf.data.Dataset, test_data: tf.data.Dataset) -> dict
     )
 
     model.compile(
-        optimizer="adam", loss="sparse_categorical_crossentropy", metrics=["accuracy"]
+        optimizer="adam",
+        loss="sparse_categorical_crossentropy",
+        metrics=["accuracy"],
+        jit_compile=False,
     )
+    # jit_compile's default value is "auto" which will cause some problems in some
+    # ops, therefore it's set to False.
 
     # model.fit has a `shuffle` parameter which has a default value of `True`.
     # If you are using array-like objects, this will shuffle the data before
@@ -298,6 +303,13 @@ train_ds = tf.data.Dataset.from_tensor_slices((train_images, train_labels))
 test_ds = tf.data.Dataset.from_tensor_slices((test_images, test_labels))
 ```
 
+<div class="k-default-codeblock">
+```
+Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/mnist.npz
+ 11490434/11490434 ━━━━━━━━━━━━━━━━━━━━ 0s 0us/step
+
+```
+</div>
 Remember we called `tf.config.experimental.enable_op_determinism()` at the
 beginning of the function. This makes the `tf.data` operations deterministic.
 However, making `tf.data` operations deterministic comes with a performance
@@ -375,11 +387,11 @@ history = train_model(train_data, test_data)
 <div class="k-default-codeblock">
 ```
 Epoch 1/2
- 938/938 ━━━━━━━━━━━━━━━━━━━━ 26s 27ms/step - accuracy: 0.5418 - loss: 1.2867 - val_accuracy: 0.9291 - val_loss: 0.2303
+ 938/938 ━━━━━━━━━━━━━━━━━━━━ 73s 73ms/step - accuracy: 0.5726 - loss: 1.2175 - val_accuracy: 0.9401 - val_loss: 0.1924
 Epoch 2/2
- 938/938 ━━━━━━━━━━━━━━━━━━━━ 25s 26ms/step - accuracy: 0.9075 - loss: 0.2983 - val_accuracy: 0.9583 - val_loss: 0.1343
- 157/157 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - accuracy: 0.9512 - loss: 0.1559
-Model accuracy on test data: 95.83%
+ 938/938 ━━━━━━━━━━━━━━━━━━━━ 89s 81ms/step - accuracy: 0.9105 - loss: 0.2885 - val_accuracy: 0.9630 - val_loss: 0.1131
+ 157/157 ━━━━━━━━━━━━━━━━━━━━ 3s 17ms/step - accuracy: 0.9553 - loss: 0.1353
+Model accuracy on test data: 96.30%
 
 ```
 </div>

examples/keras_recipes/reproducibility_recipes.py

@@ -151,8 +151,13 @@ def train_model(train_data: tf.data.Dataset, test_data: tf.data.Dataset) -> dict
     )
 
     model.compile(
-        optimizer="adam", loss="sparse_categorical_crossentropy", metrics=["accuracy"]
+        optimizer="adam",
+        loss="sparse_categorical_crossentropy",
+        metrics=["accuracy"],
+        jit_compile=False,
     )
+    # jit_compile's default value is "auto" which will cause some problems in some
+    # ops, therefore it's set to False.
 
     # model.fit has a `shuffle` parameter which has a default value of `True`.
     # If you are using array-like objects, this will shuffle the data before

guides/img/stable_diffusion_3_in_keras_hub/mountain_dog.png

@@ -44,10 +44,10 @@
    },
    "outputs": [],
    "source": [
-    "!!pip install -Uq keras\n",
-    "!!pip install -Uq git+https://github.com/keras-team/keras-hub.git\n",
-    "!!wget --user-agent=\"User-Agent: Mozilla/5.0\" -O mountain_dog.png https://i.imgur.com/3AHYG9Z.png\n",
-    "!!wget --user-agent=\"User-Agent: Mozilla/5.0\" -O mountain_dog_mask.png https://i.imgur.com/n3Prpj6.png"
+    "!pip install -Uq keras\n",
+    "!pip install -Uq git+https://github.com/keras-team/keras-hub.git\n",
+    "!wget -O mountain_dog.png https://raw.githubusercontent.com/keras-team/keras-io/master/guides/img/stable_diffusion_3_in_keras_hub/mountain_dog.png\n",
+    "!wget -O mountain_dog_mask.png https://raw.githubusercontent.com/keras-team/keras-io/master/guides/img/stable_diffusion_3_in_keras_hub/mountain_dog_mask.png"
    ]
   },
   {

guides/img/stable_diffusion_3_in_keras_hub/mountain_dog_mask.png

@@ -27,8 +27,8 @@
 """shell
 !pip install -Uq keras
 !pip install -Uq git+https://github.com/keras-team/keras-hub.git
-!wget --user-agent="User-Agent: Mozilla/5.0" -O mountain_dog.png https://i.imgur.com/3AHYG9Z.png
-!wget --user-agent="User-Agent: Mozilla/5.0" -O mountain_dog_mask.png https://i.imgur.com/n3Prpj6.png
+!wget -O mountain_dog.png https://raw.githubusercontent.com/keras-team/keras-io/master/guides/img/stable_diffusion_3_in_keras_hub/mountain_dog.png
+!wget -O mountain_dog_mask.png https://raw.githubusercontent.com/keras-team/keras-io/master/guides/img/stable_diffusion_3_in_keras_hub/mountain_dog_mask.png
 """
 
 import os

guides/ipynb/keras_hub/stable_diffusion_3_in_keras_hub.ipynb

@@ -240,7 +240,7 @@ plt.show()
 
 
 
-![png](/content/keras-io/guides/img/segment_anything_in_keras_hub/segment_anything_in_keras_hub_11_0.png)
+![png](/img/guides/segment_anything_in_keras_hub/segment_anything_in_keras_hub_11_0.png)
 
 
 
@@ -262,7 +262,7 @@ plt.show()
 
 
 
-![png](/content/keras-io/guides/img/segment_anything_in_keras_hub/segment_anything_in_keras_hub_13_0.png)
+![png](/img/guides/segment_anything_in_keras_hub/segment_anything_in_keras_hub_13_0.png)
 
 
 
@@ -326,7 +326,7 @@ plt.show()
 
 
 
-![png](/content/keras-io/guides/img/segment_anything_in_keras_hub/segment_anything_in_keras_hub_17_0.png)
+![png](/img/guides/segment_anything_in_keras_hub/segment_anything_in_keras_hub_17_0.png)
 
 
 
@@ -354,7 +354,7 @@ plt.show()
 
 
 
-![png](/content/keras-io/guides/img/segment_anything_in_keras_hub/segment_anything_in_keras_hub_20_0.png)
+![png](/img/guides/segment_anything_in_keras_hub/segment_anything_in_keras_hub_20_0.png)
 
 
 
@@ -395,7 +395,7 @@ plt.show()
 ```
 </div>
 
-![png](/content/keras-io/guides/img/segment_anything_in_keras_hub/segment_anything_in_keras_hub_23_1.png)
+![png](/img/guides/segment_anything_in_keras_hub/segment_anything_in_keras_hub_23_1.png)
 
 
 
@@ -442,7 +442,7 @@ plt.show()
 ```
 </div>
 
-![png](/content/keras-io/guides/img/segment_anything_in_keras_hub/segment_anything_in_keras_hub_25_1.png)
+![png](/img/guides/segment_anything_in_keras_hub/segment_anything_in_keras_hub_25_1.png)
 
 
 
@@ -625,7 +625,7 @@ WARNING:matplotlib.image:Clipping input data to the valid range for imshow with
 ```
 </div>
 
-![png](/content/keras-io/guides/img/segment_anything_in_keras_hub/segment_anything_in_keras_hub_31_2.png)
+![png](/img/guides/segment_anything_in_keras_hub/segment_anything_in_keras_hub_31_2.png)
 
 
 
@@ -690,7 +690,7 @@ WARNING:matplotlib.image:Clipping input data to the valid range for imshow with
 ```
 </div>
 
-![png](/content/keras-io/guides/img/segment_anything_in_keras_hub/segment_anything_in_keras_hub_35_1.png)
+![png](/img/guides/segment_anything_in_keras_hub/segment_anything_in_keras_hub_35_1.png)