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Results 1 - 10 of 20 for operandType (0.29 sec)
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src/cmd/compile/internal/typecheck/const.go
n = ir.NewConstExpr(n.Val(), n) break } n = ir.NewConstExpr(v, n) n.SetType(t) return n case ir.OPLUS, ir.ONEG, ir.OBITNOT, ir.ONOT, ir.OREAL, ir.OIMAG: ot := operandType(n.Op(), t) if ot == nil { n = DefaultLit(n, nil) break } n := n.(*ir.UnaryExpr) n.X = convlit(n.X, ot) if n.X.Type() == nil { n.SetType(nil) return n }
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Thu Oct 05 15:20:28 UTC 2023 - 10.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/hlo_matchers.cc
if (!reshape_op) return false; auto operand_type = mlir::dyn_cast<RankedTensorType>(reshape_op.getOperand().getType()); if (!operand_type || !operand_type.hasStaticShape()) return false; auto reshape_type = mlir::cast<RankedTensorType>(reshape_op.getType()); // Reshape can take a 1-D iota input and add extra dims of size one. if (operand_type.getRank() != 1) return false;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 11.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/legalize_hlo_conversions/scatter.h
ShapedType operand_type = mlir::cast<ShapedType>(operands[0].getType()); ShapedType indices_type = mlir::cast<ShapedType>(indices.getType()); ShapedType updates_type = mlir::cast<ShapedType>(updates[0].getType()); Value new_updates = updates[0]; // Can only convert with static shaped scatter. if (!operand_type.hasStaticShape() || !indices_type.hasStaticShape() ||
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 10.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_traits.h
return op->emitOpError() << "requires all return types to have compatible element types"; } for (auto operand_type : op->getOperandTypes()) { if (!mlir::tf_type::HasCompatibleElementTypes( operand_type, type, /*may_ignore_ref_type_lhs=*/true)) return op->emitError() << "requires all operands and results to have "
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 12.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/host_runtime/tpu_metadata_utils.cc
for (auto operand_type_and_idx : llvm::enumerate(op.getOperandTypes())) { Type operand_type = operand_type_and_idx.value(); int index = operand_type_and_idx.index(); tensorflow::tpu::TPUCompileMetadataProto::Arg* arg = metadata->add_args(); tensorflow::DataType dtype; tensorflow::Status status = tensorflow::ConvertToDataType(operand_type, &dtype); if (!status.ok()) return op.emitOpError(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 10.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_executor.cc
mlir::isa<tf_type::TensorFlowRefType>(output_tensor_ty.getElementType()); for (Type operand_type : merge.getOperandTypes()) { if (mlir::isa<ControlType>(operand_type)) break; // TODO(hinsu): Update ControlOperandsAfterAllData trait to verify this // constraint. TensorType operand_tensor_ty = mlir::dyn_cast<TensorType>(operand_type); if (!operand_tensor_ty) return merge.emitOpError()
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 42.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/passes/quantization_patterns.cc
// inputs. SmallVector<Value, 4> inputs; inputs.reserve(op_with_region->getNumOperands()); for (Value operand : op_with_region->getOperands()) { const Type operand_type = operand.getType(); if (mlir::isa<NoneType>(operand_type)) { inputs.push_back(operand); continue; } const Type element_type = mlir::cast<TensorType>(operand.getType()).getElementType();
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 03 06:04:36 UTC 2024 - 41.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/layout_optimization.cc
llvm::all_of(op->getOperands(), [result_type](Value operand) -> bool { auto operand_type = mlir::dyn_cast_or_null<ShapedType>(operand.getType()); return result_type && operand_type && result_type.hasRank() && operand_type.hasRank() && result_type.getRank() == operand_type.getRank(); }); if (!is_valid_move) return; }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 19.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/passes/quantization_patterns.h
// inputs. SmallVector<Value, 4> inputs; inputs.reserve(candidate_op->getNumOperands()); for (auto operand : candidate_op->getOperands()) { Type operand_type = operand.getType(); if (mlir::isa<NoneType>(operand_type)) { inputs.push_back(operand); continue; } auto ele_type = mlir::cast<TensorType>(operand.getType()).getElementType();
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 10.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/legalize_hlo_conversions/dot_general.cc
bool is_lhs) { auto operand_type = mlir::cast<ShapedType>(operand.getType()); auto operand_shape = builder.create<TFL::ShapeOp>( RankedTensorType::get(static_cast<int32_t>(operand_type.getRank()), builder.getIntegerType(32)), operand); const int64_t operand_rank = operand_type.getRank(); // Compute flattened out dimension and contracting dimension using
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 19.2K bytes - Viewed (0)