tf.placeholder
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Inserts a placeholder for a tensor that will be always fed.
tf.placeholder(
dtype, shape=None, name=None
)
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
|
Eager Compatibility
Placeholders are not compatible with eager execution.
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Last updated 2020-10-01 UTC.
[null,null,["Last updated 2020-10-01 UTC."],[],[],null,["# tf.placeholder\n\n\u003cbr /\u003e\n\n|-------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/python/ops/array_ops.py#L2577-L2619) |\n\nInserts a placeholder for a tensor that will be always fed.\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.placeholder`](/api_docs/python/tf/compat/v1/placeholder)\n\n\u003cbr /\u003e\n\n tf.placeholder(\n dtype, shape=None, name=None\n )\n\n| **Key Point:** This tensor will produce an error if evaluated. Its value must be fed using the `feed_dict` optional argument to [`Session.run()`](../tf/InteractiveSession#run), [`Tensor.eval()`](../tf/Tensor#eval), or [`Operation.run()`](../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\n\n#### Eager Compatibility\n\nPlaceholders are not compatible with eager execution."]]
View source on GitHub