Searched refs:pad_output (Results 1 – 3 of 3) sorted by relevance
243 mlir::Value pad_output) { in VerifyPaddedDimensionNotSharded() argument245 auto output_type = pad_output.getType().dyn_cast<mlir::RankedTensorType>(); in VerifyPaddedDimensionNotSharded()274 auto pad_output = op->getResult(0); in ExpandOp() local285 VerifyPaddedDimensionNotSharded(*op_layout, pad_input, pad_output)); in ExpandOp()296 mlir::Value pad_output; in ComputeLayoutForward() local299 pad_output = pad_v2.output(); in ComputeLayoutForward()303 pad_output = pad_op.output(); in ComputeLayoutForward()308 VerifyPaddedDimensionNotSharded(input_layout, pad_input, pad_output)); in ComputeLayoutForward()316 mlir::Value pad_output; in ComputeLayoutBackward() local323 pad_output = pad_v2.output(); in ComputeLayoutBackward()[all …]
142 auto pad_output = graph->FindOutputs(node->id)[0]; in ApplyToNode() local143 auto consumer_nodes = graph->FindConsumers(pad_output->id); in ApplyToNode()
464 bool pad_output = false; in ResizeUsingDilationAndConvolutionGradOp() local467 pad_output = true; in ResizeUsingDilationAndConvolutionGradOp()471 if (pad_output) { in ResizeUsingDilationAndConvolutionGradOp()