update readme

google · Oct 28, 2021 · f896e85 · rubidijum · Aug 22, 2022 · kralka
1 parent 0768ec2
commit f896e85
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Showing 6 changed files with 290 additions and 89 deletions.
diff --git a/.gitignore b/.gitignore
@@ -10,7 +10,7 @@ scald/datasets/
 scald/archive/
 scald/deprecated/
 scald/tmp/
-
+*.zip
 .vscode/
 # Byte-compiled / optimized / DLL files
 __pycache__/

diff --git a/scaaml/intro/generator.py b/scaaml/intro/generator.py
@@ -68,13 +68,13 @@ def create_dataset(filepattern,
     cprint('|-x:%s' % str(x.shape), 'green')
 
     # make it a tf dataset
-    cprint("building tf dataset", 'magenta')
-    dataset = tf.data.Dataset.from_tensor_slices((x, y))
-    dataset.cache()
-    if is_training:
-        dataset = dataset.shuffle(shuffle_size, reshuffle_each_iteration=True)
-    dataset = dataset.batch(batch_size).prefetch(tf.data.experimental.AUTOTUNE)
-    return dataset
+    # cprint("building tf dataset", 'magenta')
+    # dataset = tf.data.Dataset.from_tensor_slices((x, y))
+    # dataset.cache()
+    # if is_training:
+    #     dataset = dataset.shuffle(shuffle_size, reshuffle_each_iteration=True)
+    # dataset = dataset.batch(batch_size).prefetch(tf.data.experimental.AUTOTUNE)
+    return (x, y)
 
 
 def list_shards(filepattern, num_shards):

diff --git a/scaaml_intro/README.md b/scaaml_intro/README.md
@@ -47,7 +47,7 @@ In order to run the notebooks/train models you need to download the following da
 
 | Filename                                                                               | What it is                                                | Download size | Expected Location | SHAS256                                                          |
 | -------------------------------------------------------------------------------------- | --------------------------------------------------------- | :-----------: | ----------------- | ---------------------------------------------------------------- |
-| [datasets.zip](https://storage.googleapis.com/scaaml-public/scaaml_intro/datasets.zip) | TinyAES train & test datasets                             |      7GB      | `datasets/`       | 4bf2c6defb79b40b30f01f488e83762396b56daad14a694f64916be2b665b2f8 |
+| [datasets.zip](https://storage.googleapis.com/scaaml-public/scaaml_intro/datasets.zip) | TinyAES train & test datasets                             |     8.2GB     | `datasets/`       | 4bf2c6defb79b40b30f01f488e83762396b56daad14a694f64916be2b665b2f8 |
 | [models.zip](https://storage.googleapis.com/scaaml-public/scaaml_intro/models.zip)     | TinyAES 48 pretrained models - 3 attack points * 16 bytes |     312MB     | `models/`         | 17d7d32cca0ac0db157ae1f5696f6c64bba6d753a8f33802d0d9614bb07d3d9b |
 | [logs.zip](https://storage.googleapis.com/scaaml-public/scaaml_intro/logs.zip)         | Tensorboard training logs (optional)                      |     616MB     | `logs`            | 5b2f43f89990653d64820cca61f15fc6818ee674ae4cc2b4f235cfd9a48f3b28 |
 

diff --git a/scaaml_intro/key_recovery_demo.ipynb b/scaaml_intro/key_recovery_demo.ipynb
diff --git a/scaaml_intro/train.py b/scaaml_intro/train.py
@@ -36,7 +36,7 @@ def train_model(config):
     for attack_byte in config['attack_bytes']:
         for attack_point in config['attack_points']:
 
-            g_train = create_dataset(
+            x_train, y_train = create_dataset(
                 TRAIN_GLOB,
                 batch_size=BATCH_SIZE,
                 attack_point=attack_point,
@@ -46,7 +46,7 @@ def train_model(config):
                 max_trace_length=config['max_trace_len'],
                 is_training=True)
 
-            g_test = create_dataset(
+            x_test, y_test = create_dataset(
                 TEST_GLOB,
                 batch_size=BATCH_SIZE,
                 attack_point=attack_point,
@@ -57,9 +57,7 @@ def train_model(config):
                 is_training=False)
 
             # infers shape
-            for data in g_test.take(1):
-                x, y = data
-            input_shape = x.shape[1:]
+            input_shape = x_train.shape[1:]
 
             # reset graph and load a new model
             K.clear_session()
@@ -85,8 +83,8 @@ def train_model(config):
                     TensorBoard(log_dir='logs/' + stub, update_freq='batch')
                 ]
 
-                model.fit(g_train,
-                          validation_data=g_test,
+                model.fit(x_train, y_train,
+                          validation_data=(x_test, y_test),
                           verbose=1,
                           epochs=config['epochs'],
                           callbacks=cb)

diff --git a/setup.py b/setup.py
@@ -40,6 +40,8 @@
     "tensorflow>=2.2.0",
     "future-fstrings",
     "pygments",
+    "chipwhisperer",
+    "scipy"
   ],
   package_data={"": ["*.pickle"]},
   classifiers=[