package xla.gpu

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• repeated AlgorithmBlacklistEntry entries = 1

Used in: AlgorithmBlacklist

• string hlo = 1

• optional tensorflow.ComputeCapability cc = 2

• optional tensorflow.CudnnVersion cudnn_version = 3

• string blas_version = 5

• repeated BlacklistedAlgorithm algos = 4

Used in: AlgorithmBlacklistEntry

• int64 id = 1

• bool tensor_ops = 2

• optional HloInstructionProto instruction = 1

• repeated ShapeProto operand_shapes = 2

• uint64 result_address = 3

• repeated uint64 operand_addresses = 4

Backend config for the BatchNormForwardTraining operation running through cuDNN.

• int64 activation_mode = 1

  The requested activation (e.g. relu) after the batchnorm. It is with type stream_executor::dnn::ActivationMode.

Backend config for a convolution that runs through cudnn.

• int64 algorithm = 1

  Opaque algorithm number of cudnn algorithm chosen for this conv.

• bool tensor_ops_enabled = 2

  Whether we may use tensor cores when running this conv. Even if this is true, cudnn may choose not to use tensor cores, e.g. because the GPU or selected algorithm doesn't support it.

• double conv_result_scale = 4

  The scaling factor multiplied with the convolution result.

• int64 activation_mode = 3

  The requested activation (e.g. relu) after the convolution. It is with type stream_executor::dnn::ActivationMode.

• double side_input_scale = 5

  The scaling factor multiplied with the side input. If no side input buffer is provided, this field must be 0.

Backend config for the GEMM operation running through cuBLAS.

• oneof algorithm

  Opaque optional algorithm number. No chosen number indicates that a different cuBLAS API will be used, which does not allow for choosing an algorithm.

  • int64 selected_algorithm = 1

• double alpha_real = 2

• double alpha_imag = 9

• double beta = 3

• optional DotDimensionNumbers dot_dimension_numbers = 7

• int64 batch_size = 8