changed typings for Sequential (#393)

SeldonIO · Dec 1, 2021 · 31dc64d · 31dc64d
1 parent 573ef3b
commit 31dc64d
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Showing 7 changed files with 27 additions and 27 deletions.
diff --git a/alibi_detect/ad/adversarialae.py b/alibi_detect/ad/adversarialae.py
@@ -56,8 +56,8 @@ def __init__(self,
                  threshold: float = None,
                  ae: tf.keras.Model = None,
                  model: tf.keras.Model = None,
-                 encoder_net: tf.keras.Sequential = None,
-                 decoder_net: tf.keras.Sequential = None,
+                 encoder_net: tf.keras.Model = None,
+                 decoder_net: tf.keras.Model = None,
                  model_hl: List[tf.keras.Model] = None,
                  hidden_layer_kld: dict = None,
                  w_model_hl: list = None,

diff --git a/alibi_detect/models/tensorflow/autoencoder.py b/alibi_detect/models/tensorflow/autoencoder.py
@@ -31,7 +31,7 @@ def call(self, inputs: Tuple[tf.Tensor, tf.Tensor]) -> tf.Tensor:
 class EncoderVAE(Layer):
 
     def __init__(self,
-                 encoder_net: tf.keras.Sequential,
+                 encoder_net: tf.keras.Model,
                  latent_dim: int,
                  name: str = 'encoder_vae') -> None:
         """
@@ -65,7 +65,7 @@ def call(self, x: tf.Tensor) -> Tuple[tf.Tensor, tf.Tensor, tf.Tensor]:
 class Decoder(Layer):
 
     def __init__(self,
-                 decoder_net: tf.keras.Sequential,
+                 decoder_net: tf.keras.Model,
                  name: str = 'decoder') -> None:
         """
         Decoder of (V)AE.
@@ -87,8 +87,8 @@ def call(self, x: tf.Tensor) -> tf.Tensor:
 class VAE(tf.keras.Model):
 
     def __init__(self,
-                 encoder_net: tf.keras.Sequential,
-                 decoder_net: tf.keras.Sequential,
+                 encoder_net: tf.keras.Model,
+                 decoder_net: tf.keras.Model,
                  latent_dim: int,
                  beta: float = 1.,
                  name: str = 'vae') -> None:
@@ -126,7 +126,7 @@ def call(self, x: tf.Tensor) -> tf.Tensor:
 class EncoderAE(Layer):
 
     def __init__(self,
-                 encoder_net: tf.keras.Sequential,
+                 encoder_net: tf.keras.Model,
                  name: str = 'encoder_ae') -> None:
         """
         Encoder of AE.
@@ -148,8 +148,8 @@ def call(self, x: tf.Tensor) -> tf.Tensor:
 class AE(tf.keras.Model):
 
     def __init__(self,
-                 encoder_net: tf.keras.Sequential,
-                 decoder_net: tf.keras.Sequential,
+                 encoder_net: tf.keras.Model,
+                 decoder_net: tf.keras.Model,
                  name: str = 'ae') -> None:
         """
         Combine encoder and decoder in AE.
@@ -234,7 +234,7 @@ class Seq2Seq(tf.keras.Model):
     def __init__(self,
                  encoder_net: EncoderLSTM,
                  decoder_net: DecoderLSTM,
-                 threshold_net: tf.keras.Sequential,
+                 threshold_net: tf.keras.Model,
                  n_features: int,
                  score_fn: Callable = tf.math.squared_difference,
                  beta: float = 1.,
@@ -359,9 +359,9 @@ def eucl_cosim_features(x: tf.Tensor,
 class AEGMM(tf.keras.Model):
 
     def __init__(self,
-                 encoder_net: tf.keras.Sequential,
-                 decoder_net: tf.keras.Sequential,
-                 gmm_density_net: tf.keras.Sequential,
+                 encoder_net: tf.keras.Model,
+                 decoder_net: tf.keras.Model,
+                 gmm_density_net: tf.keras.Model,
                  n_gmm: int,
                  recon_features: Callable = eucl_cosim_features,
                  name: str = 'aegmm') -> None:
@@ -402,9 +402,9 @@ def call(self, x: tf.Tensor) -> Tuple[tf.Tensor, tf.Tensor, tf.Tensor]:
 class VAEGMM(tf.keras.Model):
 
     def __init__(self,
-                 encoder_net: tf.keras.Sequential,
-                 decoder_net: tf.keras.Sequential,
-                 gmm_density_net: tf.keras.Sequential,
+                 encoder_net: tf.keras.Model,
+                 decoder_net: tf.keras.Model,
+                 gmm_density_net: tf.keras.Model,
                  n_gmm: int,
                  latent_dim: int,
                  recon_features: Callable = eucl_cosim_features,

diff --git a/alibi_detect/od/ae.py b/alibi_detect/od/ae.py
@@ -15,8 +15,8 @@ class OutlierAE(BaseDetector, FitMixin, ThresholdMixin):
     def __init__(self,
                  threshold: float = None,
                  ae: tf.keras.Model = None,
-                 encoder_net: tf.keras.Sequential = None,
-                 decoder_net: tf.keras.Sequential = None,
+                 encoder_net: tf.keras.Model = None,
+                 decoder_net: tf.keras.Model = None,
                  data_type: str = None
                  ) -> None:
         """

diff --git a/alibi_detect/od/aegmm.py b/alibi_detect/od/aegmm.py
@@ -17,9 +17,9 @@ class OutlierAEGMM(BaseDetector, FitMixin, ThresholdMixin):
     def __init__(self,
                  threshold: float = None,
                  aegmm: tf.keras.Model = None,
-                 encoder_net: tf.keras.Sequential = None,
-                 decoder_net: tf.keras.Sequential = None,
-                 gmm_density_net: tf.keras.Sequential = None,
+                 encoder_net: tf.keras.Model = None,
+                 decoder_net: tf.keras.Model = None,
+                 gmm_density_net: tf.keras.Model = None,
                  n_gmm: int = None,
                  recon_features: Callable = eucl_cosim_features,
                  data_type: str = None

diff --git a/alibi_detect/od/seq2seq.py b/alibi_detect/od/seq2seq.py
@@ -18,7 +18,7 @@ def __init__(self,
                  seq_len: int,
                  threshold: Union[float, np.ndarray] = None,
                  seq2seq: tf.keras.Model = None,
-                 threshold_net: tf.keras.Sequential = None,
+                 threshold_net: tf.keras.Model = None,
                  latent_dim: int = None,
                  output_activation: str = None,
                  beta: float = 1.

diff --git a/alibi_detect/od/vae.py b/alibi_detect/od/vae.py
@@ -18,8 +18,8 @@ def __init__(self,
                  threshold: float = None,
                  score_type: str = 'mse',  # TODO: reconstruction proba; make sure to infer correct distribution
                  vae: tf.keras.Model = None,
-                 encoder_net: tf.keras.Sequential = None,
-                 decoder_net: tf.keras.Sequential = None,
+                 encoder_net: tf.keras.Model = None,
+                 decoder_net: tf.keras.Model = None,
                  latent_dim: int = None,
                  samples: int = 10,
                  beta: float = 1.,

diff --git a/alibi_detect/od/vaegmm.py b/alibi_detect/od/vaegmm.py
@@ -18,9 +18,9 @@ class OutlierVAEGMM(BaseDetector, FitMixin, ThresholdMixin):
     def __init__(self,
                  threshold: float = None,
                  vaegmm: tf.keras.Model = None,
-                 encoder_net: tf.keras.Sequential = None,
-                 decoder_net: tf.keras.Sequential = None,
-                 gmm_density_net: tf.keras.Sequential = None,
+                 encoder_net: tf.keras.Model = None,
+                 decoder_net: tf.keras.Model = None,
+                 gmm_density_net: tf.keras.Model = None,
                  n_gmm: int = None,
                  latent_dim: int = None,
                  samples: int = 10,