Ruby×PyCallでTensorflowのMNISTチュートリアル

$ ruby -v
ruby 2.5.0p0 (2017-12-25 revision 61468) [x86_64-darwin16]
$ gem list | grep pycall
pycall (1.0.3)

$ python3 -V
Python 3.6.4
$ pip3 freeze | grep tensorflow
tensorflow==1.6.0

require 'pycall'
require 'pycall/import'

module Python
  extend PyCall::Import
  class << self
    def from(path, import: nil)
      pyfrom path, import: import
      self.send import
    end

    def method_missing(method_name)
      pyimport method_name
      self.send method_name
    end
  end
end

require_relative 'python'
# Python library import
Python.from('tensorflow.examples.tutorials.mnist', import: :input_data)
tf = Python.tensorflow
input_data = Python.input_data

# Download MMIST dataset
mnist = input_data.read_data_sets('MNIST_data/', one_hot: true)

# Input, weight, bias
x = tf.placeholder(tf.float32, [nil, 784])
w = tf.Variable.new(tf.zeros([784, 10]))
b = tf.Variable.new(tf.zeros([10]))

# Output
y = tf.nn.softmax(tf.matmul(x, w) + b)
y_ = tf.placeholder(tf.float32, [nil, 10])

# Error function
cross_entropy = tf.reduce_mean(-1 * tf.reduce_sum(y_ * tf.log(y), reduction_indices: [1]))

# Train Model
train_step = tf.train.GradientDescentOptimizer.new(0.5).minimize(cross_entropy)

sess = tf.InteractiveSession.new
tf.global_variables_initializer.run

# Train start
1000.times do
  batch = mnist.train.next_batch(100)
  batch_xs, batch_ys = batch[0], batch[1]
  sess.run(train_step, feed_dict: {x => batch_xs, y_ => batch_ys})
end

# normalize
correct_prediction = tf.equal(tf.argmax(y, 1), tf.argmax(y_, 1))

# Result
accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
puts sess.run(accuracy, feed_dict: { x => mnist.test.images, y_ => mnist.test.labels })

$ ruby tensorflow_tutorial.rb
0.9185

$ export PYTHON=path/to/python3

$ /Applications/Python\ 3.6/Install\ Certificates.command


Exception: PyCall::PyError: <class 'TypeError'>: _as_graph_element() missing 1 required positional argument: 'self'
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/math_ops.py", line 2004, in matmul
  with ops.name_scope(name, "MatMul", [a, b]) as name:
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 5616, in __enter__
  g = _get_graph_from_inputs(self._values)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 5277, in _get_graph_from_inputs
  graph_element = _as_graph_element(op_input)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 118, in _as_graph_element
  return conv_fn()


pythonの元コード: tf.Variable(tf.zeros([10]))
間違えたrubyコード: tf.Varialbe(tf.zeros([10]))
よく見るrubyコード: tf.Variable.(tf.zeros([10]))

正解のrubyコード: tf.Variable.new(tf.zeros([10]))

元のPythonコード: sess.run(train_step, feed_dict={x: batch_xs, y_: batch_ys})
Ruby間違いコード : sess.run(train_step, feed_dict: {x: batch_xs, y_: batch_ys})
Ruby正解コード　 : sess.run(train_step, feed_dict: {x => batch_xs, y_ => batch_ys})