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  • References
  • Big Data
  • TensorFlow
  • TensorFlow Python
  • TensorArray Operations

tf.TensorArray

class tf.TensorArray

Class wrapping dynamic-sized, per-time-step, write-once Tensor arrays.

This class is meant to be used with dynamic iteration primitives such as while_loop and map_fn. It supports gradient back-propagation via special "flow" control flow dependencies.

Links:
  • https://www.tensorflow.org/versions/master/api_docs/python/tensor_array_ops.html#TensorArray
doc_TensorFlow
doc_TensorFlow
2025-01-10 15:47:30
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tf.TensorArray.handle tf.TensorArray.handle The reference to the TensorArray.
tf.TensorArray.flow tf.TensorArray.flow The flow Tensor forcing ops leading to this TensorArray state.
tf.TensorArray.dtype tf.TensorArray.dtype The data type of this TensorArray.
tf.TensorArray.unpack() tf.TensorArray.unpack(value, name=None) Pack the values of a Tensor in the TensorArray. Args: value: (N+1)-D. Tensor of type dtype. The Tensor to u
tf.TensorArray.pack() tf.TensorArray.pack(name=None) Return the values in the TensorArray as a packed Tensor. All of the values must have been written and their shapes mu


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