x = tf.compat.v1.placeholder(tf.float32, shape=(1024, 1024))
y = tf.matmul(x, x)
with tf.compat.v1.Session() as sess:
print(sess.run(y)) # ERROR: will fail because x was not fed.
rand_array = np.random.rand(1024, 1024)
print(sess.run(y, feed_dict={x: rand_array})) # Will succeed.
Args
dtype
The type of elements in the tensor to be fed.
shape
The shape of the tensor to be fed (optional). If the shape is not
specified, you can feed a tensor of any shape.
name
A name for the operation (optional).
Returns
A Tensor that may be used as a handle for feeding a value, but not
evaluated directly.
Raises
RuntimeError
if eager execution is enabled
Eager Compatibility
Placeholders are not compatible with eager execution.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2021-02-18 UTC."],[],[]]