November 2017
Intermediate to advanced
328 pages
6h 51m
Japanese
Content preview from 入門 PySpark ―PythonとJupyterで活用するSpark 2エコシステム
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8.2
TensorFlow
とは何か
167
TensorFlow
の演算グラフ
プレースフォルダ
プレースフォルダ
プレースホルダを使っているので、同じグラフを新しいセッションと新しい入力に対して簡単に再利
用できます。
#
入力行列のセットアップ
m1 = [[3., 2., 1., 0.]]
m2 = [[-5.], [-4.], [-3.], [-2.]]
#
セッションを使ってグラフを実行
with tf.Session() as s:
print(s.run([tp], feed_dict={t1:m1, t2:m2}))
結果は次のようになります。
[array([[-26.]], dtype=float32)]
8.2.5
議論
すでに述べたとおり、TensorFlowはPython のライブラリを使ってディープラーニングを実行する機
能を提供します。演算処理はグラフとして表現され、データはテンソル（グラフの辺）として、たとえ
ば数値演算などのような実行内容は、処理（グラフの頂点）になります。
さらに詳しい情報については、次を参照してください。
●
TensorFlow | Get Started | Basic Usage（https://www.tensorflow.org/get_started/basic_
usage）
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