cleanup reqs

ecg/network.py

@@ -18,13 +18,13 @@ def add_conv_weight(
         num_filters,
         subsample_length=1,
         **params):
-    from keras.layers.convolutional import Convolution1D
-    layer = Convolution1D(
-        nb_filter=num_filters,
-        filter_length=filter_length,
-        border_mode='same',
-        subsample_length=subsample_length,
-        init=params["conv_init"])(layer)
+    from keras.layers import Conv1D 
+    layer = Conv1D(
+        filters=num_filters,
+        kernel_size=filter_length,
+        strides=subsample_length,
+        padding='same',
+        kernel_initializer=params["conv_init"])(layer)
     return layer
 
 
@@ -45,8 +45,8 @@ def resnet_block(
         subsample_length,
         block_index,
         **params):
-    from keras.layers import merge
-    from keras.layers.pooling import MaxPooling1D
+    from keras.layers import Add 
+    from keras.layers import MaxPooling1D
     from keras.layers.core import Lambda
 
     def zeropad(x):
@@ -59,7 +59,7 @@ def zeropad_output_shape(input_shape):
         shape[2] *= 2
         return tuple(shape)
 
-    shortcut = MaxPooling1D(pool_length=subsample_length)(layer)
+    shortcut = MaxPooling1D(pool_size=subsample_length)(layer)
     zero_pad = (block_index % params["conv_increase_channels_at"]) == 0 \
         and block_index > 0
     if zero_pad is True:
@@ -77,7 +77,7 @@ def zeropad_output_shape(input_shape):
             num_filters,
             subsample_length if i == 0 else 1,
             **params)
-    layer = merge([shortcut, layer], mode="sum")
+    layer = Add()([shortcut, layer])
     return layer
 
 def get_num_filters_at_index(index, num_start_filters, **params):
@@ -142,6 +142,6 @@ def build_network(**params):
         layer = add_resnet_layers(inputs, **params)
 
     output = add_output_layer(layer, **params)
-    model = Model(input=[inputs], output=[output])
+    model = Model(inputs=[inputs], outputs=[output])
     add_compile(model, **params)
     return model

ecg/train.py

@@ -142,12 +142,12 @@ def train(args, params):
                     batch_size=batch_size,
                     augmenter=get_augment_fn(params))
 
-    samples_per_epoch = batch_size * int(x_train.shape[0] / batch_size)
+    steps_per_epoch = int(x_train.shape[0] / batch_size)
 
     model.fit_generator(
         train_data,
-        samples_per_epoch=samples_per_epoch,
-        nb_epoch=MAX_EPOCHS,
+        steps_per_epoch=steps_per_epoch,
+        epochs=MAX_EPOCHS,
         validation_data=(x_test, y_test),
         callbacks=[checkpointer, reduce_lr, stopping],
         verbose=args.verbose)

requirements.txt

@@ -1,76 +1,5 @@
-appdirs==1.4.3
-backports-abc==0.5
-backports.shutil-get-terminal-size==1.0.0
-backports.ssl-match-hostname==3.5.0.1
-bleach==2.0.0
-certifi==2017.4.17
-configparser==3.5.0
-cycler==0.10.0
-decorator==4.0.11
-docopt==0.6.2
-entrypoints==0.2.3
-enum34==1.1.6
-funcsigs==1.0.2
-functools32==3.2.3.post2
-future==0.16.0
-h5py==2.6.0
-html5lib==0.999999999
-ipykernel==4.6.1
-ipython==5.4.1
-ipython-genutils==0.2.0
-ipywidgets==6.0.0
-Jinja2==2.9.6
-joblib==0.10.3
-jsonschema==2.6.0
-jupyter==1.0.0
-jupyter-client==5.1.0
-jupyter-console==5.1.0
-jupyter-core==4.3.0
-Keras==1.2.2
-MarkupSafe==1.0
-matplotlib==2.0.0
-mistune==0.7.4
-mock==2.0.0
-nbconvert==5.2.1
-nbformat==4.3.0
-notebook==5.0.0
-numpy==1.12.1
-packaging==16.8
-pandas==0.19.2
-pandocfilters==1.4.1
-pathlib2==2.3.0
-pbr==3.0.0
-pexpect==4.2.1
-pickleshare==0.7.4
-pprint==0.1
-prompt-toolkit==1.0.14
-protobuf==3.2.0
-ptyprocess==0.5.2
-pydot-ng==1.0.0
-Pygments==2.2.0
-pyparsing==2.2.0
-python-dateutil==2.6.0
-pytz==2016.10
-PyWavelets==0.5.1
-PyYAML==3.12
-pyzmq==16.0.2
-qtconsole==4.3.0
-scandir==1.5
-scikit-learn==0.18.1
-scipy==0.18.1
-simplegeneric==0.8.1
-singledispatch==3.4.0.3
-six==1.10.0
+h5py==2.8.0rc1
+Keras==2.1.6
 sklearn==0.0
-subprocess32==3.2.7
-tabulate==0.7.7
-terminado==0.6
-testpath==0.3.1
-Theano==0.8.2
-tornado==4.5.1
-tqdm==4.11.0
-traitlets==4.3.2
-wcwidth==0.1.7
-webencodings==0.5.1
-Werkzeug==0.12.1
-widgetsnbextension==2.0.0
+tqdm==4.23.4
+unittest2==1.1.0

setup.sh

@@ -9,5 +9,5 @@ fi
 
 
 pip install -r requirements.txt
-pip install --upgrade $TF==1.0.1 
+pip install --upgrade $TF==1.8.0