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from keras.layers import LSTM
 
model = Sequential()
model.add(Embedding(max_features, 256, input_length=maxlen)) 
model.add(LSTM(output_dim=128, activation='sigmoid', inner_activation='hard_sigmoid'))
model.add(Dropout(0.5)) model.add(Dense(1))
model.add(Activation('sigmoid'))
 
model.compile(loss='binary_crossentropy', optimizer='rmsprop', metrics=['accuracy'])
model.fit(X_train, Y_train, batch_size=16, nb_epoch=10)

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Model: "mobilenetv2_1.00_224"
__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to
==================================================================================================
input_1 (InputLayer)            [(None, 224, 224, 3) 0
__________________________________________________________________________________________________
Conv1_pad (ZeroPadding2D)       (None, 225, 225, 3)  0           input_1[0][0]
__________________________________________________________________________________________________
Conv1 (Conv2D)                  (None, 112, 112, 32) 864         Conv1_pad[0][0]
__________________________________________________________________________________________________

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WORKSPACE: /Users/ljohnson/repos/tensorflow
CI_DOCKER_BUILD_EXTRA_PARAMS: 
CI_DOCKER_EXTRA_PARAMS: -e CI_BUILD_PYTHON=python3 -e CROSSTOOL_PYTHON_INCLUDE_PATH=/usr/include/python3.4
COMMAND: tensorflow/tools/ci_build/pi/build_raspberry_pi.sh
CI_COMMAND_PREFIX: ./tensorflow/tools/ci_build/builds/with_the_same_user ./tensorflow/tools/ci_build/builds/configured pi-python3
CONTAINER_TYPE: pi-python3
BUILD_TAG: tf_ci
  (docker container name will be tf_ci.pi-python3)

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CI_DOCKER_EXTRA_PARAMS="-e CI_BUILD_PYTHON=python3 -e CROSSTOOL_PYTHON_INCLUDE_PATH=/usr/include/python3.5" \
    tensorflow/tools/ci_build/ci_build.sh PI-PYTHON3 \
    tensorflow/tools/ci_build/pi/build_raspberry_pi.sh
    
CC_TOOL=/tools/cross-pi-gcc-8.3.0-1/bin/arm-linux-gnueabihf-g++ \
bazel build -c opt \
  --copt=-march=armv7-a \
  --copt=-mfpu=neon-vfpv4 \
  --copt=-std=c++11  \
  --copt=-funsafe-math-optimizations --copt=-ftree-vectorize \

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echo "Downloading and installing go"
wget https://dl.google.com/go/go1.11.2.linux-amd64.tar.gz /home/multipass/go1.11.2.linux-amd64.tar.gz
tar -xvf go1.11.2.linux-amd64.tar.gz

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def nth_iterinterleave(*arrays, nth=1):
    """Interleave multiple lists.
       via https://github.com/dgilland/pydash/blob/develop/src/pydash/arrays.py
       
      Expanded to allow an nth parameter, where arrays[0] is treated as the primary and arrays[1:] are interleaved every n elements

      Example:

      given *arrays = [ [1,2,3,4,5,6,7,8,9,10], ['x', 'y', 'z'], ['a', 'b', 'c'] ]

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<link href="/assets/threejs-cloth/styles/styles.css" rel="stylesheet">

<div class='container'>
    <div class='row'>
    </div>
      <h1> A quick demonstration - <small>writeup soon!</small></h1>
    <div class='row'>
      <h1 class='col-md-6'> Choose a pattern:</h1>
    </div>
    <div class='row controls'>

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from dateutil import rrule 
import datetime

# Generate ruleset for holiday observances on the NYSE

def NYSE_holidays(a=datetime.date.today(), b=datetime.date.today()+datetime.timedelta(days=365)):
    rs = rrule.rruleset()

    # Include all potential holiday observances
    rs.rrule(rrule.rrule(rrule.YEARLY, dtstart=a, until=b, bymonth=12, bymonthday=31, byweekday=rrule.FR)) # New Years Day