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tensorflow/compiler/mlir/lite/quantization/lite/quantize_model_test.cc
const OperatorT& quant_op, int idx) { const auto& builtin_code = GetBuiltinCode(quant_model.operator_codes[quant_op.opcode_index].get()); for (const auto& expected_op : expected_graph.operators) { const auto& op_code = expected_model.operator_codes[expected_op->opcode_index].get(); const auto& expected_code = GetBuiltinCode(op_code); if (expected_code == builtin_code) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 23:15:24 UTC 2024 - 73.9K bytes - Viewed (0) -
src/cmd/go/testdata/script/mod_vendor_auto.txt
import _ "example.com/printversion" -- $WORK/auto/auto.go -- package auto -- $WORK/auto/replacement-version/go.mod -- module example.com/version -- $WORK/auto/replacement-version/version.go -- package version const V = "v1.0.0-replaced" -- $WORK/modules-1.14.txt -- # example.com/printversion v1.0.0 ## explicit example.com/printversion # example.com/version v1.0.0 => ./replacement-version example.com/version
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Tue May 07 15:21:14 UTC 2024 - 9.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/tensor_list_ops_decomposition.cc
Block& block, const llvm::SmallDenseMap<Value, SizeInfo>& buffer_to_size) { auto old_terminator = block.getTerminator(); auto new_outputs = llvm::to_vector<8>(old_terminator->getOperands()); llvm::SmallVector<std::tuple<int64_t, int64_t, bool>, 8> output_buffer_to_size; for (auto retval : llvm::enumerate(old_terminator->getOperands())) { auto it = buffer_to_size.find(retval.value()); if (it == buffer_to_size.end()) continue;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 39.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/sparsecore/embedding_pipelining.cc
auto loop_operands_n = UnpackResults(loop_operands_indexes_i); auto forward_res_nm2 = UnpackResults(forward_res_indexes_im2); auto forward_res_nm1 = UnpackResults(forward_res_indexes_im1); auto core_tpu_res_nm2 = UnpackResults(core_tpu_res_indexes_im2); auto non_tpu_res_nm1 = UnpackResults(non_tpu_res_indexes_im1); auto C_nm2 = new_while_op->getResult(C_index_im2); auto C_nm1 = new_while_op->getResult(C_index_im1);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 92.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/translate/export_graphdef.cc
} void Exporter::UseOriginalFunctionNames(NodeDef& node_def) { if (!configs_.export_original_tf_func_name) return; auto& attrs = *node_def.mutable_attr(); auto try_use_original_func_name = [this](std::string* name) { if (auto func = symbol_table_.lookup<FuncOp>(*name)) { if (auto original_func_name = func->getAttrOfType<mlir::StringAttr>("tf._original_func_name")) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 01 11:17:36 UTC 2024 - 35.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/api/v2/tf_executor_to_graph.cc
} void Exporter::UseOriginalFunctionNames(NodeDef& node_def) { if (!configs_.export_original_tf_func_name) return; auto& attrs = *node_def.mutable_attr(); auto try_use_original_func_name = [this](std::string* name) { if (auto func = symbol_table_.lookup<FuncOp>(*name)) { if (auto original_func_name = func->getAttrOfType<mlir::StringAttr>("tf._original_func_name")) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 23:04:51 UTC 2024 - 35.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/tpu_space_to_depth_pass.cc
for (auto& input : inputs) { auto input_op = input.get().getDefiningOp(); if (!input_op || !IsSupportedHostInputOp(input_op)) return false; } for (auto entry : llvm::enumerate(inputs)) { Value input = entry.value().get(); auto ranked_type = mlir::dyn_cast<RankedTensorType>(input.getType()); if (!ranked_type) return false; auto input_shape = ranked_type.getShape();
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 29.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/ir/tfl_ops.cc
return success(); } auto stride_h = op.getStrideHAttr().getInt(); auto stride_w = op.getStrideWAttr().getInt(); auto dilation_h = op.getDilationHFactorAttr().getInt(); auto dilation_w = op.getDilationWFactorAttr().getInt(); // We don't have EXPLICIT PADDING in TfLite. auto paddings = op.getPadding(); tensorflow::Padding padding;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 169.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/passes/bridge/convert_tf_quant_ops_to_mhlo.cc
return rewriter.notifyMatchFailure(op, "zero_points must be constant"); } auto original_element_type = getElementTypeOrSelf(original_type); if (!mlir::isa<TF::Qint8Type, TF::Qint32Type>(original_element_type)) { return rewriter.notifyMatchFailure( op, "Quantized type must be qint8 or qint32."); } auto storage_type = GetIntTypeFromTFQint(original_element_type);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 17:58:54 UTC 2024 - 30.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/analysis/resource_alias_analysis.cc
// has the property that if there is an edge from SCC1->SCC2, SCC1 is visited // after SCC2, i.e., the graph is traversed bottom up just the way we want. auto scc_begin = llvm::scc_begin(&call_graph); auto scc_end = llvm::scc_end(&call_graph); for (auto& scc : make_range(scc_begin, scc_end)) { // Each SCC node is a collection of callgraph nodes that form a cycle. We
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 15 09:04:13 UTC 2024 - 28.2K bytes - Viewed (0)