tf.compat.v1.placeholder

Inserts a placeholder for a tensor that will be always fed.

tf.compat.v1.placeholder(
    dtype, shape=None, name=None
)

Migrate to TF2

Caution: This API was designed for TensorFlow v1. Continue reading for details on how to migrate from this API to a native TensorFlow v2 equivalent. See the TensorFlow v1 to TensorFlow v2 migration guide for instructions on how to migrate the rest of your code.

This API is not compatible with eager execution and tf.function. To migrate to TF2, rewrite the code to be compatible with eager execution. Check the migration guide on replacing Session.run calls. In TF2, you can just pass tensors directly into ops and layers. If you want to explicitly set up your inputs, also see Keras functional API on how to use tf.keras.Input to replace tf.compat.v1.placeholder. tf.function arguments also do the job of tf.compat.v1.placeholder. For more details please read Better performance with tf.function.

Description

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.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