# tf.placeholder(dtype, shape=None, name=None)

### tf.placeholder(dtype, shape=None, name=None)

See the guide: Inputs and Readers > Placeholders

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.

Defined in tensorflow/python/ops/array_ops.py.