tf.raw_ops.XlaSparseDenseMatmulGradWithAdagradMomentumAndStaticBufferSize 

tf.raw_ops.XlaSparseDenseMatmulGradWithAdagradMomentumAndStaticBufferSize(
    row_pointers,
    sorted_sample_ids,
    sorted_token_ids,
    sorted_gains,
    activation_gradients,
    learning_rate,
    embedding_table,
    accumulator,
    momenta,
    num_minibatches_per_physical_sparse_core,
    use_nesterov,
    exponent,
    beta1,
    beta2,
    epsilon,
    max_ids_per_sparse_core,
    max_unique_ids_per_sparse_core,
    table_name,
    clip_weight_min=float('-inf'),
    clip_weight_max=float('inf'),
    num_sparsecores_per_device=-1,
    name=None
)

row_pointers A Tensor of type int32.
sorted_sample_ids A Tensor of type int32.
sorted_token_ids A Tensor of type int32.
sorted_gains A Tensor of type float32.
activation_gradients A Tensor of type float32.
learning_rate A Tensor of type float32.
embedding_table A Tensor of type float32.
accumulator A Tensor of type float32.
momenta A Tensor of type float32.
num_minibatches_per_physical_sparse_core A Tensor of type int32.
use_nesterov A bool.
exponent A float.
beta1 A float.
beta2 A float.
epsilon A float.
max_ids_per_sparse_core An int that is >= 1.
max_unique_ids_per_sparse_core An int that is >= 1.
table_name A string.
clip_weight_min An optional float. Defaults to float('-inf').
clip_weight_max An optional float. Defaults to float('inf').
num_sparsecores_per_device An optional int. Defaults to -1.
name A name for the operation (optional).

A tuple of Tensor objects (updated_embedding_table, updated_accumulator, updated_momenta).
updated_embedding_table A Tensor of type float32.
updated_accumulator A Tensor of type float32.
updated_momenta A Tensor of type float32.