what is tf.placeholder code example

Example 1: css style placeholder

input::-webkit-input-placeholder {/* Chrome/Opera/Safari/Edge */
	/*styles here*/
}

input::-ms-input-placeholder { /* Microsoft Edge */
   /*styles here*/
}

input:-ms-input-placeholder {/* IE 10+ */
	/*styles here*/
}

input::-moz-placeholder {/* Firefox 19+ */
	opacity: 1; /*Firefox by default has an opacity object that usually is ideal to reset so it matches webkit*/
	/*styles here*/
}

input:-moz-placeholder {/* Firefox 18- */
	opacity: 1; /*Firefox by default has an opacity object that usually is ideal to reset so it matches webkit*/
	/*styles here*/
}

input::placeholder {
	/*styles here*/
}

Example 2: tf.placeholder()

Inserts a placeholder for a tensor that will be always fed.
A placeholder is simply a variable that we will assign data to 
at a later date. It allows us to create our operations and build 
our computation graph, without needing the data. In TensorFlow
terminology, we then feed data into the graph through these 
placeholders.

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

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().

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.