Add activations, regularizers...

keras_contrib/__init__.py

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+from __future__ import absolute_import
+from . import backend
+from . import datasets
+from . import layers
+from . import preprocessing
+from . import utils
+from . import wrappers
+from . import callbacks
+from . import constraints
+from . import initializations
+from . import metrics
+from . import objectives
+from . import optimizers
+from . import regularizers
+
+__version__ = '0.0.1'

keras_contrib/activations.py

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+from __future__ import absolute_import
+from . import backend as K
+from keras.utils.generic_utils import get_from_module
+
+from keras.activations import *

keras_contrib/backend/__init__.py

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+from keras import backend as K
+
+ # We import all keras backend functions here,
+ # so that files in this repo can import both
+ # core and contrib backend functions with a
+ # single import statement.
+ 
+from keras.backend import *
+
+
+if K.backend() == 'theano':
+	from .theano_backend import *
+elif K.backend() == 'tensorflow':
+	from .tensorflow_backend import *

keras_contrib/backend/tensorflow_backend.py

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+import tensorflow as tf
+from tensorflow.python.training import moving_averages
+from tensorflow.python.ops import tensor_array_ops
+from tensorflow.python.ops import control_flow_ops
+try:
+    from tensorflow.python.ops import ctc_ops as ctc
+except ImportError:
+    import tensorflow.contrib.ctc as ctc
+from keras import backend as K
+import numpy as np
+import os
+import warnings
+from keras.backend.common import floatx, _EPSILON, image_dim_ordering, reset_uids
+py_all = all

keras_contrib/backend/theano_backend.py

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+import theano
+from theano import tensor as T
+from theano.sandbox.rng_mrg import MRG_RandomStreams as RandomStreams
+from theano.tensor.signal import pool
+from theano.tensor.nnet import conv3d2d
+from theano.printing import Print
+try:
+    import theano.sparse as th_sparse_module
+except ImportError:
+    th_sparse_module = None
+try:
+    from theano.tensor.nnet.nnet import softsign as T_softsign
+except ImportError:
+    from theano.sandbox.softsign import softsign as T_softsign
+from keras import backend as K
+import inspect
+import numpy as np
+from keras.backend.common import _FLOATX, floatx, _EPSILON, image_dim_ordering
+py_all = all

keras_contrib/callbacks.py

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+from __future__ import absolute_import
+from __future__ import print_function
+
+import os
+import csv
+
+import numpy as np
+import time
+import json
+import warnings
+
+from collections import deque
+from collections import OrderedDict
+from collections import Iterable
+from keras.utils.generic_utils import Progbar
+from keras import backend as K
+from pkg_resources import parse_version
+
+try:
+    import requests
+except ImportError:
+    requests = None

keras_contrib/constraints.py

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+from __future__ import absolute_import
+from . import backend as K
+from keras.utils.generic_utils import get_from_module
+
+from keras.constraints import *
+

keras_contrib/initializations.py

@@ -0,0 +1,11 @@
+from __future__ import absolute_import
+import numpy as np
+from . import backend as K
+from keras.utils.generic_utils import get_from_module
+
+from keras.initializations import *
+
+
+def get(identifier, **kwargs):
+    return get_from_module(identifier, globals(),
+                           'initialization', kwargs=kwargs)

keras_contrib/metrics.py

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+from . import backend as K
+from keras.utils.generic_utils import get_from_module
+
+from keras.metrics import *
+
+
+def get(identifier):
+    return get_from_module(identifier, globals(), 'metric')

keras_contrib/objectives.py

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+from __future__ import absolute_import
+
+from . import backend as K
+from keras.utils.generic_utils import get_from_module
+
+from keras.objectives import *
+
+
+def get(identifier):
+    return get_from_module(identifier, globals(), 'objective')

keras_contrib/optimizers.py

@@ -0,0 +1,19 @@
+from __future__ import absolute_import
+
+from six.moves import zip
+
+from . import backend as K
+from keras.utils.generic_utils import get_from_module, get_custom_objects
+
+if K.backend() == 'tensorflow':
+    import tensorflow as tf
+
+
+def get(identifier, kwargs=None):
+    if K.backend() == 'tensorflow':
+        # Wrap TF optimizer instances
+        if isinstance(identifier, tf.train.Optimizer):
+            return TFOptimizer(identifier)
+    # Instantiate a Keras optimizer
+    return get_from_module(identifier, globals(), 'optimizer',
+                           instantiate=True, kwargs=kwargs)

keras_contrib/regularizers.py

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+from __future__ import absolute_import
+from . import backend as K
+from keras.utils.generic_utils import get_from_module
+
+from keras.regularizers import *
+
+
+def get(identifier, kwargs=None):
+    return get_from_module(identifier, globals(), 'regularizer',
+                           instantiate=True, kwargs=kwargs)

keras_contrib/utils/__init__.py

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+from keras.utils import *