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tensorflow/compiler/mlir/quantization/tensorflow/passes/propagate_quantize_type.cc
if (failed(applyPatternsAndFoldGreedily(func, frozen_patterns))) { func.emitError() << "quant-propagate-quantize-type failed."; signalPassFailure(); } } } } // namespace // Creates an instance of the TensorFlow dialect PropagateQuantizeType pass. std::unique_ptr<OperationPass<ModuleOp>> CreatePropagateQuantizeTypePass() { return std::make_unique<PropagateQuantizeType>(); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/host_runtime/tpu_variable_runtime_reformatting.cc
// supported. const auto& device_list = devices.find(tensorflow::GetDeviceAliasForLogicalCore(0))->getSecond(); // Create the state variable for each device. for (llvm::StringRef device : device_list) { state_vars.push_back(builder->create<TF::VarHandleOp>( loc, llvm::ArrayRef<Type>{RankedTensorType::get( {}, TF::ResourceType::get(llvm::ArrayRef<TensorType>{key_type},
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 21.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/legalize_tf.cc
auto static_shape_attr = mlir::DenseIntElementsAttr::get(static_shape_type, static_shape); return rewriter.create<TF::ConstOp>(loc, static_shape_attr).getOutput(); } // If the shape is not static, create a new ShapeOp. BoolAttr false_attr = rewriter.getBoolAttr(false); return rewriter .create<TF::ShapeOp>(loc, input, /*use_32bit=*/false_attr) .getOutput(); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 20 20:06:54 UTC 2024 - 45.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/transforms/legalize_tf.cc
rewriter.create<SubtractOp>(loc, b_max_diag_len, diag_len_d), b_zero); // x = max(d, 0) - offset // y = max(-d, 0) - offset Value x = rewriter.create<SubtractOp>( loc, rewriter.create<MaxOp>(loc, d, b_zero), offset); Value y = rewriter.create<SubtractOp>( loc, rewriter.create<MaxOp>(loc, neg_d, b_zero), offset); Value n_plus_x = rewriter.create<AddOp>(loc, iotaN, x);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 20:00:43 UTC 2024 - 291.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/legalize_hlo.cc
auto out_segids_cst = builder.create<TF::ConstOp>( builder.getI32TensorAttr(flattened_out_segids)); auto contracting_segids_cst = builder.create<TF::ConstOp>( builder.getI32TensorAttr(flattened_contracting_segids)); auto num_segids_tensor = builder.create<TF::ConstOp>(builder.getI32IntegerAttr(1)); auto flattened_out_dims = builder.create<TF::UnsortedSegmentProdOp>(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 154.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/prepare_quantize_drq.cc
return false; } } rewriter.setInsertionPointAfter(op); auto q = rewriter.create<quantfork::QuantizeCastOp>(op->getLoc(), cast_type, op.getResult()); auto dq = rewriter.create<quantfork::DequantizeCastOp>(op->getLoc(), expressed_type, q);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 11.5K bytes - Viewed (0) -
tensorflow/c/experimental/stream_executor/stream_executor.cc
TF_RETURN_IF_ERROR(c_event->Create()); return std::move(c_event); } absl::StatusOr<std::unique_ptr<Stream>> CreateStream( std::optional<std::variant<StreamPriority, int>> priority = std::nullopt) override { auto stream = std::make_unique<CStream>(&device_, stream_executor_, this); TF_RETURN_IF_ERROR(stream->Create()); return std::move(stream); } private:
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jun 14 07:39:19 UTC 2024 - 27.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/optimize_batch_matmul.cc
if (constant.getType().getRank() != 2) return failure(); // Create a tfl.transpose op that performs ZX transpose on `input`. auto create_z_x_transpose_op = [&](Value input) -> Value { RankedTensorType input_type = mlir::cast<RankedTensorType>(input.getType()); const int input_rank = input_type.getRank(); // Create a 1D I32 tensor for representing the dimension permutation.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 9.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/utils/tpu_rewrite_device_util_test.cc
context.loadDialect<mlir::tf_device::TensorFlowDeviceDialect>(); mlir::OwningOpRef<mlir::ModuleOp> module_ref = mlir::ModuleOp::create(mlir::UnknownLoc::get(&context)); mlir::OpBuilder builder(module_ref->getBodyRegion()); llvm::SmallVector<mlir::Type, 8> result_types; auto cluster = builder.create<mlir::tf_device::ClusterOp>( mlir::UnknownLoc::get(&context), result_types); cluster->setAttr(kNumCoresPerReplicaAttr,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Apr 26 09:37:10 UTC 2024 - 46.8K bytes - Viewed (0) -
tensorflow/compiler/jit/xla_compile_util.cc
// _Arg nodes, and let CompileGraph walk it. This could be optimized. std::unique_ptr<Graph> graph(new Graph(OpRegistry::Global())); // First create the actual node we care about computing. TF_ASSIGN_OR_RETURN(Node * main_node, graph->AddNode(node_def)); // Create dummy _Arg nodes. Link these to `node` and also via a control // dependency edge to the _SOURCE node. for (int64_t i = 0, end = args.size(); i < end; ++i) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 21 09:53:30 UTC 2024 - 4.6K bytes - Viewed (0)