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Results 81 - 89 of 89 for getOperands (0.16 sec)
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tensorflow/compiler/mlir/lite/experimental/tac/transforms/fold_constants_to_subgraph.cc
// Locate the argument position of the use. int argument_index = -1; for (int i = 0; i < consumer_call.getNumOperands(); ++i) { if (consumer_call.getOperand(i) == op->getResult(0)) { argument_index = i; break; } } // Copy the const into the consumer func and replace their usages.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 6.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/fuse_convolution_pass.cc
multiplier = isa<mhlo::ConstantOp>(bcast_or_const_op) ? dyn_cast_or_null<mhlo::ConstantOp>(bcast_or_const_op) : bcast_or_const_op->getOperand(0) .getDefiningOp<mhlo::ConstantOp>(); if (multiplier == nullptr) { return failure(); } auto result_type = OpTrait::util::getBroadcastedType(filter.getType(),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 22 22:21:19 UTC 2024 - 8.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/lift_quantizable_spots_as_functions_drq.cc
// This op is guaranteed to be a constant as ODS checks IsConstTensor. // Check if the number of elements meets the requirement. int current_num_elements = mlir::cast<ShapedType>(call_op.getOperand(idx).getType()) .getNumElements(); if (current_num_elements < min_num_elements_for_weights_) { call_op.emitRemark("Quantization is skipped for ")
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 8.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/op_stat_pass.cc
// Use rhs operand to detect types for dynamic range quantizable ops. Value value_for_deducing_op_type = (dyn_cast_or_null<DynamicRangeQuantizedOpInterface>(op)) ? op->getOperand(1) : op->getResult(0); ShapedType value_shaped_type = mlir::dyn_cast_or_null<ShapedType>( value_for_deducing_op_type.getType()); if (value_shaped_type != nullptr) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 8.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/lower_globals_to_ml_program.cc
if (v.getDefiningOp()->getNumOperands() == 1) { // If the value is originating from an unary op, assume it's something // simple like "cast" and keep tracing. return traceUpwardsToArgument(v.getDefiningOp()->getOperand(0), seen, out); } else { // Typically a tf.VarHandle op. return v.getDefiningOp()->emitOpError("Non constant predecessor"); } }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 8.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/modify_io_nodes.cc
} int num_return_operands = terminator->getNumOperands(); new_output_types.reserve(num_return_operands); for (int i = 0; i != num_return_operands; ++i) { auto returned_value = terminator->getOperand(i); Type returned_type = returned_value.getType(); Operation* returned_op = returned_value.getDefiningOp(); if (returned_op && llvm::isa<DequantizeOp>(returned_op)) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 8.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/utils/attribute_utils.h
bool GetValueAsConstant(Value val, AttrT &attr) { while (auto result = mlir::dyn_cast<OpResult>(val)) { Operation *op = result.getOwner(); if (!isa<IdentityOp>(op) && !isa<IdentityNOp>(op)) break; val = op->getOperand(result.getResultNumber()); } return matchPattern(val, m_Constant(&attr)); } // Checks if both compilation and replication attributes are present in the // operation, and if their values are valid.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 22 19:47:48 UTC 2024 - 8.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/default_quant_params.cc
quant::AccumulatorScaleFunc func) { std::vector<quant::QuantizedType> non_bias_types; non_bias_types.reserve(non_biases.size()); for (int non_bias : non_biases) { Operation *non_bias_define = op->getOperand(non_bias).getDefiningOp(); if (auto dequant = llvm::dyn_cast<TFL::DequantizeOp>(non_bias_define)) { auto non_bias_type = mlir::cast<TensorType>(dequant.getInput().getType()); auto non_bias_ele_type =
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 9.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/composite_avg_pool.cc
TorchAvgPoolData GetTorchAvgPoolData(CompositeOp op) { auto composite_attrs = op.getCompositeAttributes(); TorchAvgPoolData data; auto op_type = mlir::cast<RankedTensorType>(op.getOperand(0).getType()); data.n = op_type.getShape()[0]; data.c = op_type.getShape()[1]; data.h_in = op_type.getShape()[2]; data.w_in = op_type.getShape()[3]; std::vector<int32_t> kernel_size;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 28 23:16:05 UTC 2024 - 9.2K bytes - Viewed (0)