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line<= 80 and RELU to ReLU #9109

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Expand Up @@ -11,7 +11,8 @@
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""This is an example of using convolutional networks over characters for DBpedia dataset to predict class from description of an entity.
"""This is an example of using convolutional networks over characters for
DBpedia dataset to predict class from description of an entity.

This model is similar to one described in this paper:
"Character-level Convolutional Networks for Text Classification"
Expand Down Expand Up @@ -54,7 +55,7 @@ def char_cnn_model(features, target):
# Apply Convolution filtering on input sequence.
conv1 = tf.contrib.layers.convolution2d(
byte_list, N_FILTERS, FILTER_SHAPE1, padding='VALID')
# Add a RELU for non linearity.
# Add a ReLU for non linearity.
conv1 = tf.nn.relu(conv1)
# Max pooling across output of Convolution+Relu.
pool1 = tf.nn.max_pool(
Expand Down