tf.placeholder(dtype, shape=None, name=None)
Inserts a placeholder for a tensor that will be always fed.
Important: This tensor will produce an error if evaluated. Its value must be fed using the feed_dict
optional argument to Session.run()
, Tensor.eval()
, or Operation.run()
.
For example:
x = tf.placeholder(tf.float32, shape=(1024, 1024)) y = tf.matmul(x, x) with tf.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.
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