Do not override the optimizer's default parameters

As discussed in kiudee#119. The
reasoning is that we don't have good reason to override those, the
library user will likely have to tune them anyways (or use a different
optimizer altogether). At the same time, they make the design proposed
in kiudee#119 (passing uninitialized optimizers and their parameters
separately) more difficult.

csrank/choicefunction/cmpnet_choice.py

@@ -19,7 +19,7 @@ def __init__(
         kernel_regularizer=l2(1e-4),
         kernel_initializer="lecun_normal",
         activation="relu",
-        optimizer=SGD(lr=1e-4, nesterov=True, momentum=0.9),
+        optimizer=SGD(),
         metrics=["binary_accuracy"],
         batch_size=256,
         random_state=None,

csrank/choicefunction/fate_choice.py

@@ -21,7 +21,7 @@ def __init__(
         activation="selu",
         kernel_initializer="lecun_normal",
         kernel_regularizer=l2(0.01),
-        optimizer=SGD(lr=1e-4, nesterov=True, momentum=0.9),
+        optimizer=SGD(),
         batch_size=256,
         metrics=None,
         random_state=None,

csrank/choicefunction/feta_choice.py

@@ -34,7 +34,7 @@ def __init__(
         kernel_regularizer=l2(1e-4),
         kernel_initializer="lecun_normal",
         activation="selu",
-        optimizer=SGD(lr=1e-4, nesterov=True, momentum=0.9),
+        optimizer=SGD(),
         metrics=["binary_accuracy"],
         batch_size=256,
         random_state=None,

csrank/choicefunction/ranknet_choice.py

@@ -19,7 +19,7 @@ def __init__(
         kernel_regularizer=l2(1e-4),
         kernel_initializer="lecun_normal",
         activation="relu",
-        optimizer=SGD(lr=1e-4, nesterov=True, momentum=0.9),
+        optimizer=SGD(),
         metrics=["binary_accuracy"],
         batch_size=256,
         random_state=None,

csrank/core/cmpnet_core.py

@@ -29,7 +29,7 @@ def __init__(
         kernel_regularizer=l2(1e-4),
         kernel_initializer="lecun_normal",
         activation="relu",
-        optimizer=SGD(lr=1e-4, nesterov=True, momentum=0.9),
+        optimizer=SGD(),
         metrics=["binary_accuracy"],
         batch_size=256,
         random_state=None,

csrank/core/fate_network.py

@@ -29,7 +29,7 @@ def __init__(
         activation="selu",
         kernel_initializer="lecun_normal",
         kernel_regularizer=l2(0.01),
-        optimizer=SGD(lr=1e-4, nesterov=True, momentum=0.9),
+        optimizer=SGD(),
         batch_size=256,
         random_state=None,
         **kwargs,

csrank/core/feta_network.py

@@ -36,7 +36,7 @@ def __init__(
         kernel_regularizer=l2(1e-4),
         kernel_initializer="lecun_normal",
         activation="selu",
-        optimizer=SGD(lr=1e-4, nesterov=True, momentum=0.9),
+        optimizer=SGD(),
         metrics=None,
         batch_size=256,
         random_state=None,

csrank/core/ranknet_core.py

@@ -28,7 +28,7 @@ def __init__(
         kernel_regularizer=l2(1e-4),
         kernel_initializer="lecun_normal",
         activation="relu",
-        optimizer=SGD(lr=1e-4, nesterov=True, momentum=0.9),
+        optimizer=SGD(),
         metrics=["binary_accuracy"],
         batch_size=256,
         random_state=None,

csrank/discretechoice/cmpnet_discrete_choice.py

@@ -18,7 +18,7 @@ def __init__(
         kernel_regularizer=l2(1e-4),
         kernel_initializer="lecun_normal",
         activation="relu",
-        optimizer=SGD(lr=1e-4, nesterov=True, momentum=0.9),
+        optimizer=SGD(),
         metrics=["binary_accuracy"],
         batch_size=256,
         random_state=None,

csrank/discretechoice/fate_discrete_choice.py

@@ -20,7 +20,7 @@ def __init__(
         activation="selu",
         kernel_initializer="lecun_normal",
         kernel_regularizer=l2(0.01),
-        optimizer=SGD(lr=1e-4, nesterov=True, momentum=0.9),
+        optimizer=SGD(),
         batch_size=256,
         random_state=None,
         **kwargs,

csrank/discretechoice/feta_discrete_choice.py

@@ -32,7 +32,7 @@ def __init__(
         kernel_regularizer=l2(1e-4),
         kernel_initializer="lecun_normal",
         activation="selu",
-        optimizer=SGD(lr=1e-4, nesterov=True, momentum=0.9),
+        optimizer=SGD(),
         metrics=["categorical_accuracy"],
         batch_size=256,
         random_state=None,

csrank/discretechoice/ranknet_discrete_choice.py

@@ -18,7 +18,7 @@ def __init__(
         kernel_regularizer=l2(1e-4),
         kernel_initializer="lecun_normal",
         activation="relu",
-        optimizer=SGD(lr=1e-4, nesterov=True, momentum=0.9),
+        optimizer=SGD(),
         metrics=["binary_accuracy"],
         batch_size=256,
         random_state=None,

csrank/objectranking/cmp_net.py

@@ -20,7 +20,7 @@ def __init__(
         kernel_regularizer=l2(1e-4),
         kernel_initializer="lecun_normal",
         activation="relu",
-        optimizer=SGD(lr=1e-4, nesterov=True, momentum=0.9),
+        optimizer=SGD(),
         metrics=["binary_accuracy"],
         batch_size=256,
         random_state=None,

csrank/objectranking/fate_object_ranker.py

@@ -19,7 +19,7 @@ def __init__(
         activation="selu",
         kernel_initializer="lecun_normal",
         kernel_regularizer=l2(0.01),
-        optimizer=SGD(lr=1e-4, nesterov=True, momentum=0.9),
+        optimizer=SGD(),
         batch_size=256,
         loss_function=hinged_rank_loss,
         metrics=[zero_one_rank_loss_for_scores_ties],

csrank/objectranking/feta_object_ranker.py

@@ -23,7 +23,7 @@ def __init__(
         kernel_regularizer=l2(1e-4),
         kernel_initializer="lecun_normal",
         activation="selu",
-        optimizer=SGD(lr=1e-4, nesterov=True, momentum=0.9),
+        optimizer=SGD(),
         metrics=None,
         batch_size=256,
         random_state=None,

csrank/objectranking/list_net.py

@@ -34,7 +34,7 @@ def __init__(
         kernel_regularizer=l2(1e-4),
         activation="selu",
         kernel_initializer="lecun_normal",
-        optimizer=SGD(lr=1e-4, nesterov=True, momentum=0.9),
+        optimizer=SGD(),
         metrics=[zero_one_rank_loss_for_scores_ties],
         batch_size=256,
         random_state=None,

csrank/objectranking/rank_net.py

@@ -20,7 +20,7 @@ def __init__(
         kernel_regularizer=l2(1e-4),
         kernel_initializer="lecun_normal",
         activation="relu",
-        optimizer=SGD(lr=1e-4, nesterov=True, momentum=0.9),
+        optimizer=SGD(),
         metrics=["binary_accuracy"],
         batch_size=256,
         random_state=None,