andreaschandra

kmeans_model = 'topic-kmeans'

sm = boto3.client('sagemaker')

containers = {'us-west-2': '174872318107.dkr.ecr.us-west-2.amazonaws.com/kmeans:latest'}

create_model_response = sm.create_model( ModelName=kmeans_model,
                                         ExecutionRoleArn=role,
                                         PrimaryContainer={
                                            'Image': containers[boto3.Session().region_name],

andreaschandra

kmeans_endpoint_config = 'topic-kmeans-config'
print(kmeans_endpoint_config)

create_endpoint_config_response = sm.create_endpoint_config(
    EndpointConfigName = kmeans_endpoint_config,
    ProductionVariants = [{'InstanceType'        : 'ml.m4.xlarge',
                           'InitialInstanceCount': 1,
                           'ModelName'           : kmeans_model,
                           'VariantName'         : 'AllTraffic'}
                         ])

andreaschandra

%%time

kmeans_endpoint = 'topic-kmeans-endpoint'
print(kmeans_endpoint)

create_endpoint_response = sm.create_endpoint(
    EndpointName = kmeans_endpoint,
    EndpointConfigName = kmeans_endpoint_config)
print(create_endpoint_response['EndpointArn'])

andreaschandra

import tensorflow as tf

a_const = tf.constant([1,2,3])
sess = tf.Session()
sess.run(a_const)

#array([1, 2, 3], dtype=int32)

andreaschandra

d = tf.Variable([3,4,5])
init_op = tf.global_variables_initializer()
sess = tf.Session()
sess.run(init_op)
sess.run(d)

#array([4, 5, 6], dtype=int32)

andreaschandra

ph = tf.placeholder(tf.int32)
sess = tf.Session()
sess.run(ph, feed_dict={ph: [9,8,7]})

#array([9, 8, 7], dtype=int32)

andreaschandra

if len(args) != 2:
        sys.stderr.write(
            'Usage: example.py <aggressiveness> <path to wav file>\n')
        sys.exit(1)

andreaschandra

print("Reading file:", args[1])
print("aggressiveness:", args[0])
audio, sample_rate = read_wave(args[1])

andreaschandra

vad = webrtcvad.Vad(int(args[0]))
print("Generating Frames...")
frames = frame_generator(30, audio, sample_rate)
frames = list(frames)

andreaschandra

def vad_collector(sample_rate, frame_duration_ms, padding_duration_ms, vad, frames):
    triggered = False

    voiced_frames = []
    for frame in frames:
        is_speech = vad.is_speech(frame.bytes, sample_rate)

        sys.stdout.write('1' if is_speech else '0')
        if not triggered:
            ring_buffer.append((frame, is_speech))