TensorFlow tutorial says that at creation time we need to specify the shape of tensors. That shape automatically becomes the shape of the tensor. It also says that TensorFlow provides advanced mechanisms to reshape variables. How can I do that? Any code example?
we can modify a tensor by using the assignment operator. Assigning a new value in the tensor will modify the tensor with the new value.
The tf.Variable
class is the recommended way to create variables, but it restricts your ability to change the shape of the variable once it has been created.
If you need to change the shape of a variable, you can do the following (e.g. for a 32-bit floating point tensor):
var = tf.Variable(tf.placeholder(tf.float32)) # ... new_value = ... # Tensor or numpy array. change_shape_op = tf.assign(var, new_value, validate_shape=False) # ... sess.run(change_shape_op) # Changes the shape of `var` to new_value's shape.
Note that this feature is not in the documented public API, so it is subject to change. If you do find yourself needing to use this feature, let us know, and we can investigate a way to support it moving forward.
Take a look at shapes-and-shaping from TensorFlow documentation. It describes different shape transformations available.
The most common function is probably tf.reshape, which is similar to its numpy equivalent. It allows you to specify any shape that you want as long as the number of elements stays the same. There are some examples available in the documentation.
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