tf.raw_ops.XlaSparseDenseMatmulGradWithFtrlAndCsrInput

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tf.compat.v1.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
)

Args
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.
linear	A Tensor of type float32.
num_minibatches_per_physical_sparse_core	A Tensor of type int32.
multiply_linear_by_learning_rate	A bool.
beta	A float.
learning_rate_power	A float.
l1_regularization_strength	A float.
l2_regularization_strength	A float.
table_name	A string.
clip_weight_min	An optional float. Defaults to float('-inf').
clip_weight_max	An optional float. Defaults to float('inf').
name	A name for the operation (optional).

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