mirror of
https://github.com/vale981/ray
synced 2025-03-08 19:41:38 -05:00
0ac2abee51
* Added helper class for getting tf variables from loss function * Updated usage and documentation * Removed try-catches * Added futures * Added documentation * fixes and tests * more tests * install tensorflow in travis
53 lines
1.5 KiB
Python
53 lines
1.5 KiB
Python
from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import unittest
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import tensorflow as tf
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import ray
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class TensorFlowTest(unittest.TestCase):
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def testTensorFlowVariables(self):
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ray.init(start_ray_local=True, num_workers=2)
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x_data = tf.placeholder(tf.float32, shape=[100])
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y_data = tf.placeholder(tf.float32, shape=[100])
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w = tf.Variable(tf.random_uniform([1], -1.0, 1.0))
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b = tf.Variable(tf.zeros([1]))
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y = w * x_data + b
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loss = tf.reduce_mean(tf.square(y - y_data))
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sess = tf.Session()
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sess.run(tf.global_variables_initializer())
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variables = ray.experimental.TensorFlowVariables(loss, sess)
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weights = variables.get_weights()
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for (name, val) in weights.items():
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weights[name] += 1.0
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variables.set_weights(weights)
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self.assertEqual(weights, variables.get_weights())
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w2 = tf.Variable(tf.random_uniform([1], -1.0, 1.0), name="w")
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b2 = tf.Variable(tf.zeros([1]), name="b")
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y2 = w2 * x_data + b2
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loss2 = tf.reduce_mean(tf.square(y2 - y_data))
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sess.run(tf.global_variables_initializer())
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variables2 = ray.experimental.TensorFlowVariables(loss2, sess)
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weights2 = variables2.get_weights()
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for (name, val) in weights2.items():
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weights2[name] += 2.0
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variables2.set_weights(weights2)
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self.assertEqual(weights2, variables2.get_weights())
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ray.worker.cleanup()
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if __name__ == "__main__":
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unittest.main(verbosity=2)
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