chaserileyroberts

tn_model = tf.keras.Sequential(
  [
    tf.keras.Input(shape=(2,)),
    Dense(1024, activation=tf.nn.relu),
    # Here use a TN layer instead of the dense layer.
    TNLayer(),
    Dense(1, activation=None)
  ]
)

chaserileyroberts

Dense = tf.keras.layers.Dense
fc_model = tf.keras.Sequential(
  [
    tf.keras.Input(shape=(2,)),
    Dense(1024, activation=tf.nn.relu),
    Dense(1024, activation=tf.nn.relu),
    Dense(1, activation=None)
  ]
)

chaserileyroberts

import tensorflow as tf
import tensornetwork as tn


class TNLayer(tf.keras.layers.Layer):
 
  def __init__(self):
    super(TNLayer, self).__init__()
    # Create the variables for the layer.
    self.a_var = tf.Variable(tf.random.normal(

chaserileyroberts

# Old way
tn.contractors.greedy(net).get_final_node().tensor

# New way!
tn.contractors.greedy(set_of_nodes).tensor

chaserileyroberts

import tensornetwork as tn
import numpy as np

a = tn.Node(np.eye(2))
b = tn.Node(np.eye(2))
a[0] ^ b[0] # Same as tn.connect(a[0], b[0])
result = a @ b # Same as tn.contract_between(a, b)

chaserileyroberts

import tensornetwork as tn
import numpy as np

net = tn.TensorNetwork()
a = net.add_node(np.eye(2))
b = net.add_node(np.eye(2))
a[0] ^ b[0] # Same as net.connect(a[0], b[0])
result = a @ b # Same as net.contract_between(a, b)

chaserileyroberts

import tensorflow as tf
tf.enable_v2_behavior()

def outer_product(x):
  return tf.tensordot(x, x, 0)

val = tf.ones((1000, 32, 32))
%timeit tf.map_fn(outer_product, val)
# >>> 1 loops, best of 3: 849 ms per loop
%timeit tf.vectorized_map(outer_product, val)

chaserileyroberts

Keybase proof

I hereby claim:

• I am thenerdstation on github.
• I am thenerdstation (https://keybase.io/thenerdstation) on keybase.
• I have a public key whose fingerprint is CA07 4782 93AF 7D53 8A41 85FF 0B19 951B 5876 E550

To claim this, I am signing this object:

chaserileyroberts

pip install mltest

chaserileyroberts

import mltest
import pytest

def setup():
  mltest.setup()