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

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

Used in the notebooks

Used in the guide	Used in the tutorials
Debug a TensorFlow 2 migrated training pipeline Migrate the SavedModel workflow Migrating your TFLite code to TF2	Generating Images with BigBiGAN Classify Flowers with Transfer Learning Generating Images with Little Data Using S3GAN Generating Images with BigGAN Exploring the TF-Hub CORD-19 Swivel Embeddings

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