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tensorflow/compiler/mlir/lite/ir/tfl_ops.td
let hasFolder = 1; } def TFL_RangeOp: TFL_Op<"range", [ Pure, TFL_OperandHasRank<0, 0>, TFL_OperandHasRank<1, 0>, TFL_OperandHasRank<2, 0>, PredOpTrait<"operands and output must have same element type", And<[TCresVTEtIsSameAsOp<0, 0>, TCresVTEtIsSameAsOp<0, 1>, TCresVTEtIsSameAsOp<0, 2>]>>]> { let summary = "Range operator"; let description = [{
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 19:09:08 UTC 2024 - 186K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/tf_passes.td
let description = [{ A pass that propagates device assignment of resources on a module. It performs in-function propagation, as well as cross-function propagation from callers to callees. This pass changes the module by adding "tf.device" attribute to function arguments and adding "device" attribute to TF ops. For example, given the function ```mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 21:18:05 UTC 2024 - 99.6K bytes - Viewed (0)