insertText
batchUpdate()
objectID
{ "insertText": { "objectId": objectID, "text": "Hello World!\n" }
{ "createShape": { "shapeType": "SMILEY_FACE", "elementProperties": { "pageObjectId": slideID, "size": { "height": { "magnitude": 3000000, "unit": "EMU" }, "width": { "magnitude": 3000000, "unit": "EMU" } }, "transform": { "unit": "EMU", "scaleX": 1.3449, "scaleY": 1.3031, "translateX": 4671925, "translateY": 450150 } } } }
requests
SLIDES
deckID)
SLIDES.presentations().batchUpdate(presentationId=deckID, body=requests).execute()
tfdbg
Session.run()
import numpy as np import tensorflow as tf import tensorflow.python.debug as tf_debug xs = np.linspace(-0.5, 0.49, 100) x = tf.placeholder(tf.float32, shape=[None], name="x") y = tf.placeholder(tf.float32, shape=[None], name="y") k = tf.Variable([0.0], name="k") y_hat = tf.multiply(k, x, name="y_hat") sse = tf.reduce_sum((y - y_hat) * (y - y_hat), name="sse") train_op = tf.train.GradientDescentOptimizer(learning_rate=0.02).minimize(sse) sess = tf.Session() sess.run(tf.global_variables_initializer()) sess = tf_debug.LocalCLIDebugWrapperSession(sess) for _ in range(10): sess.run(train_op, feed_dict={x: xs, y: 42 * xs})
LocalCLIDebugWrapperSession
run()
invoke_stepper
pip install tensorflow
http://www.example.com/amp/doc.html
https://www-example-com.cdn.ampproject.org/c/www.example.com/amp/doc.html
https://www.google.com/amp/www.example.com/amp.doc.html
www.google.com/amp
www.example.com/amp/doc.html
www-example-com.cdn.ampproject.org/www.example.com/amp/doc.html
www.google.com
www.google.com/amp/www.example.com/amp/doc.html
