x=tf.compat.v1.placeholder(tf.float32,shape=(1024,1024))y=tf.matmul(x,x)withtf.compat.v1.Session()assess: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.
[null,null,["Last updated 2024-04-26 UTC."],[],[],null,["# tf.compat.v1.placeholder\n\n\u003cbr /\u003e\n\n|-------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.16.1/tensorflow/python/ops/array_ops.py#L2942-L2994) |\n\nInserts a placeholder for a tensor that will be always fed. \n\n tf.compat.v1.placeholder(\n dtype, shape=None, name=None\n )\n\n\u003cbr /\u003e\n\nMigrate to TF2\n--------------\n\n\u003cbr /\u003e\n\n| **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](https://www.tensorflow.org/guide/migrate) for instructions on how to migrate the rest of your code.\n\nThis API is not compatible with eager execution and [`tf.function`](../../../tf/function). To migrate\nto TF2, rewrite the code to be compatible with eager execution. Check the\n[migration\nguide](https://www.tensorflow.org/guide/migrate#1_replace_v1sessionrun_calls)\non replacing `Session.run` calls. In TF2, you can just pass tensors directly\ninto ops and layers. If you want to explicitly set up your inputs, also see\n[Keras functional API](https://www.tensorflow.org/guide/keras/functional) on\nhow to use [`tf.keras.Input`](../../../tf/keras/Input) to replace [`tf.compat.v1.placeholder`](../../../tf/compat/v1/placeholder).\n[`tf.function`](../../../tf/function) arguments also do the job of [`tf.compat.v1.placeholder`](../../../tf/compat/v1/placeholder).\nFor more details please read [Better\nperformance with tf.function](https://www.tensorflow.org/guide/function).\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\nDescription\n-----------\n\n### Used in the notebooks\n\n| Used in the guide | Used in the tutorials |\n|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| - [Debug a TensorFlow 2 migrated training pipeline](https://www.tensorflow.org/guide/migrate/migration_debugging) - [Migrate the SavedModel workflow](https://www.tensorflow.org/guide/migrate/saved_model) - [Migrating your TFLite code to TF2](https://www.tensorflow.org/guide/migrate/tflite) | - [Generating Images with BigBiGAN](https://www.tensorflow.org/hub/tutorials/bigbigan_with_tf_hub) - [Classify Flowers with Transfer Learning](https://www.tensorflow.org/hub/tutorials/image_feature_vector) - [Generating Images with Little Data Using S3GAN](https://www.tensorflow.org/hub/tutorials/s3gan_generation_with_tf_hub) - [Generating Images with BigGAN](https://www.tensorflow.org/hub/tutorials/biggan_generation_with_tf_hub) - [Exploring the TF-Hub CORD-19 Swivel Embeddings](https://www.tensorflow.org/hub/tutorials/cord_19_embeddings) |\n\n| **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()`](https://www.tensorflow.org/api_docs/python/tf/Tensor#eval), or [`Operation.run()`](https://www.tensorflow.org/api_docs/python/tf/Operation#run).\n\n#### For example:\n\n x = tf.compat.v1.placeholder(tf.float32, shape=(1024, 1024))\n y = tf.matmul(x, x)\n\n with tf.compat.v1.Session() as sess:\n print(sess.run(y)) # ERROR: will fail because x was not fed.\n\n rand_array = np.random.rand(1024, 1024)\n print(sess.run(y, feed_dict={x: rand_array})) # Will succeed.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|---------|------------------------------------------------------------------------------------------------------------------|\n| `dtype` | The type of elements in the tensor to be fed. |\n| `shape` | The shape of the tensor to be fed (optional). If the shape is not specified, you can feed a tensor of any shape. |\n| `name` | A name for the operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A `Tensor` that may be used as a handle for feeding a value, but not evaluated directly. ||\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Raises ------ ||\n|----------------|-------------------------------|\n| `RuntimeError` | if eager execution is enabled |\n\n\u003cbr /\u003e"]]
View source on GitHub