using data shape instead of model.

TS-Lee · TS-Lee · commit 7ec4b2a3e080 · 2022-04-19T15:13:43.000Z
Signed-off-by: Taesung Lee &lt;taesung.lee@ibm.com&gt;
diff --git a/art/attacks/poisoning/gradient_matching_attack.py b/art/attacks/poisoning/gradient_matching_attack.py
@@ -190,7 +190,7 @@ def _weight_grad(classifier: TensorFlowV2Classifier, x: tf.Tensor, target: tf.Te
         y_true_poison = Input(shape=np.shape(y_poison)[1:])
         embedding_layer = Embedding(
             len(x_poison),
-            np.prod(input_poison.shape[1:]),
+            np.prod(x_poison.shape[1:]),
             embeddings_initializer=tf.keras.initializers.RandomNormal(stddev=self.epsilon * 0.01),
         )
         embeddings = embedding_layer(input_indices)

Original file line number	Diff line number	Diff line change
`@@ -190,7 +190,7 @@ def _weight_grad(classifier: TensorFlowV2Classifier, x: tf.Tensor, target: tf.Te`
`190`	`190`	`y_true_poison = Input(shape=np.shape(y_poison)[1:])`
`191`	`191`	`embedding_layer = Embedding(`
`192`	`192`	`len(x_poison),`
`193`		`- np.prod(input_poison.shape[1:]),`
	`193`	`+ np.prod(x_poison.shape[1:]),`
`194`	`194`	`embeddings_initializer=tf.keras.initializers.RandomNormal(stddev=self.epsilon * 0.01),`
`195`	`195`	`)`
`196`	`196`	`embeddings = embedding_layer(input_indices)`