GraphXlaSparseDenseMatmulGradWithAdagradMomentumAndCsrInput Method

public Operation XlaSparseDenseMatmulGradWithAdagradMomentumAndCsrInput(
	Output row_pointers,
	Output sorted_sample_ids,
	Output sorted_token_ids,
	Output sorted_gains,
	Output activation_gradients,
	Output learning_rate,
	Output embedding_table,
	Output accumulator,
	Output momenta,
	Output num_minibatches_per_physical_sparse_core,
	bool use_nesterov,
	float exponent,
	float beta1,
	float beta2,
	float epsilon,
	string table_name,
	float clip_weight_min = -∞f,
	float clip_weight_max = ∞f,
	string opName = "XlaSparseDenseMatmulGradWithAdagradMomentumAndCsrInput"
)

Public Function XlaSparseDenseMatmulGradWithAdagradMomentumAndCsrInput ( 
	row_pointers As Output,
	sorted_sample_ids As Output,
	sorted_token_ids As Output,
	sorted_gains As Output,
	activation_gradients As Output,
	learning_rate As Output,
	embedding_table As Output,
	accumulator As Output,
	momenta As Output,
	num_minibatches_per_physical_sparse_core As Output,
	use_nesterov As Boolean,
	exponent As Single,
	beta1 As Single,
	beta2 As Single,
	epsilon As Single,
	table_name As String,
	Optional clip_weight_min As Single = -∞F,
	Optional clip_weight_max As Single = ∞F,
	Optional opName As String = "XlaSparseDenseMatmulGradWithAdagradMomentumAndCsrInput"
) As Operation

public:
Operation^ XlaSparseDenseMatmulGradWithAdagradMomentumAndCsrInput(
	Output^ row_pointers, 
	Output^ sorted_sample_ids, 
	Output^ sorted_token_ids, 
	Output^ sorted_gains, 
	Output^ activation_gradients, 
	Output^ learning_rate, 
	Output^ embedding_table, 
	Output^ accumulator, 
	Output^ momenta, 
	Output^ num_minibatches_per_physical_sparse_core, 
	bool use_nesterov, 
	float exponent, 
	float beta1, 
	float beta2, 
	float epsilon, 
	String^ table_name, 
	float clip_weight_min = -∞f, 
	float clip_weight_max = ∞f, 
	String^ opName = L"XlaSparseDenseMatmulGradWithAdagradMomentumAndCsrInput"
)

member XlaSparseDenseMatmulGradWithAdagradMomentumAndCsrInput : 
        row_pointers : Output * 
        sorted_sample_ids : Output * 
        sorted_token_ids : Output * 
        sorted_gains : Output * 
        activation_gradients : Output * 
        learning_rate : Output * 
        embedding_table : Output * 
        accumulator : Output * 
        momenta : Output * 
        num_minibatches_per_physical_sparse_core : Output * 
        use_nesterov : bool * 
        exponent : float32 * 
        beta1 : float32 * 
        beta2 : float32 * 
        epsilon : float32 * 
        table_name : string * 
        ?clip_weight_min : float32 * 
        ?clip_weight_max : float32 * 
        ?opName : string 
(* Defaults:
        let _clip_weight_min = defaultArg clip_weight_min -∞f
        let _clip_weight_max = defaultArg clip_weight_max ∞f
        let _opName = defaultArg opName "XlaSparseDenseMatmulGradWithAdagradMomentumAndCsrInput"
*)
-> Operation