From f02aaff21ab89196c7b6cc8edc04d532fe58e147 Mon Sep 17 00:00:00 2001
From: Amir MOHAMMADI <amir.mohammadi@idiap.ch>
Date: Wed, 9 Sep 2020 20:03:09 +0200
Subject: [PATCH] make sure all architectures output logits
---
bob/learn/tensorflow/models/alexnet.py | 2 +-
bob/learn/tensorflow/models/densenet.py | 7 +++----
bob/learn/tensorflow/models/inception.py | 2 +-
bob/learn/tensorflow/models/inception_resnet_v2.py | 2 +-
bob/learn/tensorflow/models/lenet5.py | 2 +-
bob/learn/tensorflow/models/mcae.py | 8 ++++----
6 files changed, 11 insertions(+), 12 deletions(-)
diff --git a/bob/learn/tensorflow/models/alexnet.py b/bob/learn/tensorflow/models/alexnet.py
index 326abe71..1ff09077 100644
--- a/bob/learn/tensorflow/models/alexnet.py
+++ b/bob/learn/tensorflow/models/alexnet.py
@@ -52,7 +52,7 @@ def AlexNet_simplified(name="AlexNet", **kwargs):
tf.keras.layers.Dense(units=4096, activation="relu", name="F6"),
tf.keras.layers.Dropout(rate=0.5, name="D7"),
tf.keras.layers.Dense(units=4096, activation="relu", name="F7"),
- tf.keras.layers.Dense(units=1000, activation="softmax", name="OUTPUT"),
+ tf.keras.layers.Dense(units=1000, name="OUTPUT"),
],
name=name,
**kwargs
diff --git a/bob/learn/tensorflow/models/densenet.py b/bob/learn/tensorflow/models/densenet.py
index bc0f6abd..f17f5b86 100644
--- a/bob/learn/tensorflow/models/densenet.py
+++ b/bob/learn/tensorflow/models/densenet.py
@@ -434,15 +434,14 @@ class DeepPixBiS(tf.keras.Model):
tf.keras.layers.Flatten(
data_format=data_format, name="Pixel_Logits_Flatten"
),
- tf.keras.layers.Activation("sigmoid", name="activation"),
]
def call(self, x, training=None):
- for l in self.sequential_layers:
+ for layer in self.sequential_layers:
try:
- x = l(x, training=training)
+ x = layer(x, training=training)
except TypeError:
- x = l(x)
+ x = layer(x)
return x
diff --git a/bob/learn/tensorflow/models/inception.py b/bob/learn/tensorflow/models/inception.py
index 90d56223..5a8314aa 100644
--- a/bob/learn/tensorflow/models/inception.py
+++ b/bob/learn/tensorflow/models/inception.py
@@ -132,7 +132,7 @@ def GoogLeNet(*, num_classes=1000, name="GoogLeNet", **kwargs):
InceptionModule(384, 192, 384, 48, 128, 128, name="inception_5b"),
tf.keras.layers.GlobalAvgPool2D(name="pool5"),
tf.keras.layers.Dropout(rate=0.4, name="dropout"),
- tf.keras.layers.Dense(num_classes, name="output", activation="softmax"),
+ tf.keras.layers.Dense(num_classes, name="output"),
],
name=name,
**kwargs
diff --git a/bob/learn/tensorflow/models/inception_resnet_v2.py b/bob/learn/tensorflow/models/inception_resnet_v2.py
index dc544b0f..bfab700a 100644
--- a/bob/learn/tensorflow/models/inception_resnet_v2.py
+++ b/bob/learn/tensorflow/models/inception_resnet_v2.py
@@ -542,7 +542,7 @@ def InceptionResNetV2(
if include_top:
# Classification block
x = GlobalAvgPool2D(name="avg_pool")(x)
- x = Dense(classes, activation="softmax", name="predictions")(x)
+ x = Dense(classes, name="predictions")(x)
else:
if pooling == "avg":
x = GlobalAvgPool2D()(x)
diff --git a/bob/learn/tensorflow/models/lenet5.py b/bob/learn/tensorflow/models/lenet5.py
index 8654001b..425b3377 100644
--- a/bob/learn/tensorflow/models/lenet5.py
+++ b/bob/learn/tensorflow/models/lenet5.py
@@ -22,7 +22,7 @@ def LeNet5_simplified(name="LeNet5", **kwargs):
),
tf.keras.layers.Flatten(name="FLATTEN"),
tf.keras.layers.Dense(units=84, activation="tanh", name="F6"),
- tf.keras.layers.Dense(units=10, activation="sigmoid", name="OUTPUT"),
+ tf.keras.layers.Dense(units=10, name="OUTPUT"),
],
name=name,
**kwargs
diff --git a/bob/learn/tensorflow/models/mcae.py b/bob/learn/tensorflow/models/mcae.py
index e4241c40..21430782 100644
--- a/bob/learn/tensorflow/models/mcae.py
+++ b/bob/learn/tensorflow/models/mcae.py
@@ -51,8 +51,8 @@ class ConvEncoder(tf.keras.Model):
self.sequential_layers = layers
def call(self, x, training=None):
- for l in self.sequential_layers:
- x = l(x)
+ for layer in self.sequential_layers:
+ x = layer(x)
return x
@@ -91,8 +91,8 @@ class ConvDecoder(tf.keras.Model):
self.sequential_layers = layers
def call(self, x, training=None):
- for l in self.sequential_layers:
- x = l(x)
+ for layer in self.sequential_layers:
+ x = layer(x)
return x
--
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