

def add_gradients_summary(grads, name_prefix='', name_suffix='', collection_key=None):
    ' add_gradients_summary.\n\n    Add histogram summary for given gradients.\n\n    Arguments:\n        grads: A list of `Tensor`. The gradients to summarize.\n        name_prefix: `str`. A prefix to add to summary scope.\n        name_suffix: `str`. A suffix to add to summary scope.\n        collection_key: `str`. A collection to store the summaries.\n\n    Returns:\n        The list of created gradient summaries.\n\n    '
    summ = []
    for (grad, var) in grads:
        if (grad is not None):
            summ_name = format_scope_name(var.op.name, name_prefix, ('Gradients/' + name_suffix))
            summ_exists = summary_exists(summ_name)
            if (summ_exists is not None):
                tf.add_to_collection(collection_key, summ_exists)
                summ.append(summ_exists)
            else:
                summ.append(get_summary('histogram', summ_name, grad, collection_key))
    return summ

dataset/ETHPy150Open tflearn/tflearn/tflearn/summaries.py add_gradients_summary/original