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Results 11 - 20 of 28 for operandType (1.59 sec)
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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) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/convert_tf_xla_op_to_tf_op.cc
bool IsXlaGatherWithoutBatch(Value operand, Value start_indices) { auto operand_type = mlir::dyn_cast_or_null<ShapedType>(operand.getType()); auto start_indices_type = mlir::dyn_cast_or_null<ShapedType>(start_indices.getType()); if (start_indices_type == nullptr || operand_type == nullptr) return false; return start_indices_type.getShape().size() == 1; }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 13.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_device.cc
llvm::SmallVector<Type, 8> replicated_region_arg_types; llvm::SmallVector<Type, 8> packed_region_arg_types; do { OpAsmParser::UnresolvedOperand operand_type; if (parser->parseOptionalOperand(operand_type).has_value()) { packed_inputs->emplace_back(operand_type); if (parser->parseKeyword("as", " between packed input and block argument") ||
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 33.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/shape_inference.cc
for (auto entry : llvm::zip(operand_types, result_types, region_argument_types)) { auto operand_type = mlir::cast<TensorType>(std::get<0>(entry)); auto result_type = mlir::cast<TensorType>(std::get<1>(entry)); if (operand_type == result_type) { types.push_back(operand_type); } else if (RankedAndSameRank(operand_type, result_type)) { auto potential_refined_type = GetCompatibleRankedTensorType(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Jun 08 07:28:49 UTC 2024 - 134.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/quantize.cc
inputs.reserve(quantizing_op->getNumOperands()); for (const auto& operand : quantizing_op->getOperands()) { Type operand_type = operand.getType(); if (operand_type.isa<NoneType>()) { inputs.push_back(operand); continue; } Type elem_type = operand_type.cast<TensorType>().getElementType(); if (auto dq_op = dyn_cast_or_null<quantfork::DequantizeCastOp>(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 22 05:52:39 UTC 2024 - 23.6K bytes - Viewed (0) -
src/cmd/compile/internal/types2/assignments.go
check.expr(target, x, rhs) } if T == nil && context == "assignment" { context = "assignment to _ identifier" } check.assignment(x, T, context) } // operandTypes returns the list of types for the given operands. func operandTypes(list []*operand) (res []Type) { for _, x := range list { res = append(res, x.typ) } return res } // varTypes returns the list of types for the given variables.
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Fri Feb 23 21:21:43 UTC 2024 - 16.4K bytes - Viewed (0) -
src/go/types/assignments.go
check.expr(target, x, rhs) } if T == nil && context == "assignment" { context = "assignment to _ identifier" } check.assignment(x, T, context) } // operandTypes returns the list of types for the given operands. func operandTypes(list []*operand) (res []Type) { for _, x := range list { res = append(res, x.typ) } return res } // varTypes returns the list of types for the given variables.
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Wed Apr 03 18:48:38 UTC 2024 - 16.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/internal/passes/mark_ops_for_outside_compilation.cc
}); return has_string; } bool HasStringOperand(Operation& op) { for (auto operand : op.getOperands()) { auto operand_type = getElementTypeOrSelf(operand); if (IsStringType(operand_type)) return true; } return false; } bool HasStringResult(Operation& op) { for (auto result : op.getResults()) { auto result_type = getElementTypeOrSelf(result);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 21.4K bytes - Viewed (0)