tf.raw_ops.XlaSparseDenseMatmulGradWithFtrlAndCsrInput

tf.raw_ops.XlaSparseDenseMatmulGradWithFtrlAndCsrInput(
    row_pointers,
    sorted_sample_ids,
    sorted_token_ids,
    sorted_gains,
    activation_gradients,
    learning_rate,
    embedding_table,
    accumulator,
    linear,
    num_minibatches_per_physical_sparse_core,
    multiply_linear_by_learning_rate,
    beta,
    learning_rate_power,
    l1_regularization_strength,
    l2_regularization_strength,
    table_name,
    clip_weight_min=float('-inf'),
    clip_weight_max=float('inf'),
    name=None
)

row_pointersA Tensor of type int32.
sorted_sample_idsA Tensor of type int32.
sorted_token_idsA Tensor of type int32.
sorted_gainsA Tensor of type float32.
activation_gradientsA Tensor of type float32.
learning_rateA Tensor of type float32.
embedding_tableA Tensor of type float32.
accumulatorA Tensor of type float32.
linearA Tensor of type float32.
num_minibatches_per_physical_sparse_coreA Tensor of type int32.
multiply_linear_by_learning_rateA bool.
betaA float.
learning_rate_powerA float.
l1_regularization_strengthA float.
l2_regularization_strengthA float.
table_nameA string.
clip_weight_minAn optional float. Defaults to float('-inf').
clip_weight_maxAn optional float. Defaults to float('inf').
nameA name for the operation (optional).

A tuple of Tensor objects (updated_embedding_table, updated_accumulator, updated_linear).
updated_embedding_tableA Tensor of type float32.
updated_accumulatorA Tensor of type float32.
updated_linearA Tensor of type float32.