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Optimizer that implements the Adagrad algorithm.
See this [paper](http://www.jmlr.org/papers/volume12/duchi11a/duchi11a.pdf).
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#### `tf.train.AdagradOptimizer.__init__(learning_rate, initial_accumulator_value=0.1, use_locking=False, name='Adagrad')` {#AdagradOptimizer.__init__}
Construct a new Adagrad optimizer.
##### Args:
* <b>`learning_rate`</b>: A `Tensor` or a floating point value. The learning rate.
* <b>`initial_accumulator_value`</b>: A floating point value.
Starting value for the accumulators, must be positive.
* <b>`use_locking`</b>: If `True` use locks for update operations.
* <b>`name`</b>: Optional name prefix for the operations created when applying
gradients. Defaults to "Adagrad".
##### Raises:
* <b>`ValueError`</b>: If the `initial_accumulator_value` is invalid.
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