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tensorflow/compiler/aot/tfcompile_main.cc
#include "tensorflow/compiler/aot/compile.h" #include "tensorflow/compiler/aot/flags.h" #include "tensorflow/compiler/tf2xla/tf2xla.pb.h" #include "tensorflow/compiler/tf2xla/tf2xla_util.h" #include "xla/debug_options_flags.h" #include "xla/service/compiler.h" #include "tensorflow/core/framework/function.h" #include "tensorflow/core/framework/graph.pb.h" #include "tensorflow/core/framework/tensor_shape.h"
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Sep 06 19:12:29 UTC 2023 - 3.6K bytes - Viewed (0) -
tensorflow/compiler/jit/xla_compilation_cache.proto
syntax = "proto3"; package tensorflow; import "xla/service/hlo.proto"; // Represents the cache key used for persistence. message XlaSerializedCacheKey { uint64 signature_fingerprint = 1; uint64 cluster_fingerprint = 2; string device_type = 3; string prefix = 4; bool compiled_using_pjrt = 5; } // Represents an entry in the XLA compile cache. message XlaSerializedCacheEntry {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Sep 06 19:12:29 UTC 2023 - 1.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/utils/tpu_rewrite_device_util.h
// Checks if a device string is a TPU replicated core device. bool IsTPUReplicatedCore(llvm::StringRef device); // Checks if `type` is allowed for XLA. String and resources are not XLA types. // There are other TF types that are not XLA types which will be removed by // successive passes in TF/XLA bridge phase 2. bool TypeValidForXLA(const mlir::Type& type); // Returns the map from core to the host that is associated with the
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Apr 26 09:37:10 UTC 2024 - 11.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/README.md
# MLIR dialects and utilities for TensorFlow, TensorFlow Lite and XLA. This module contains the MLIR ([Multi-Level Intermediate Representation](https://mlir.llvm.org)) dialects and utilities for 1. TensorFlow 2. XLA 3. TF Lite See [MLIR's website](https://mlir.llvm.org) for complete documentation. ## Getting started Building dialects and utilities here follow the standard approach using `bazel` as the rest of TensorFlow.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 14 21:50:47 UTC 2023 - 1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/tf_device_passes.td
} def XlaInlineDeviceOpsPass : Pass<"tf-xla-inline-device-ops", "ModuleOp"> { let summary = "Inline all Cluster op based in the parent region"; let constructor = "TFDevice::CreateXlaInlineDeviceOpsPass()"; let dependentDialects = ["tf_device::TensorFlowDeviceDialect"]; } def XlaRewritePass : Pass<"tf-xla-rewrite", "mlir::ModuleOp"> { let summary = "Rewrites partition calls into Xla launch ops to make the attached function run on XLA.";
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Apr 17 18:52:57 UTC 2024 - 12.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/transforms/xla_legalize_tf.cc
#include "tensorflow/compiler/mlir/tf2xla/transforms/passes.h" #include "tensorflow/compiler/mlir/tf2xla/transforms/xla_legalize_targets.h" #include "xla/mlir_hlo/mhlo/IR/hlo_ops.h" #include "xla/mlir_hlo/mhlo/transforms/rewriters.h" #include "xla/mlir_hlo/mhlo/utils/type_conversion.h" #include "tensorflow/core/lib/monitoring/counter.h" namespace mlir { namespace mhlo { namespace {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 28 21:49:50 UTC 2024 - 10.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/passes/bridge/legalize_tf_quant_test.cc
#include "llvm/ADT/StringRef.h" #include "mlir/Pass/Pass.h" // from @llvm-project #include "tensorflow/compiler/mlir/tf2xla/api/v2/legalize_tf.h" #include "xla/client/client_library.h" #include "xla/shape.h" #include "xla/stream_executor/platform.h" #include "xla/stream_executor/platform_manager.h" #include "tensorflow/core/framework/tensor_shape.h" #include "tensorflow/core/framework/types.pb.h"
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 29 18:43:55 UTC 2024 - 7.2K bytes - Viewed (0) -
tensorflow/compiler/aot/codegen.h
// program_shape_access_shim is a C++ expression that constructs the // xla::ProgramShapeProto instance for the CompileResult passed to // GenerateMetadata. string program_shape_access_shim; // hlo_profile_printer_data_access_shim is a C++ expression that constructs // the xla::HloProfilePrinterData instance for the CompileResult passed to // GenerateMetadata. If the xla::HloProfilePrinterData is null then this is a
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 01 22:03:27 UTC 2023 - 4.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/internal/test_matchers_test.cc
#include <gmock/gmock.h> #include <gtest/gtest.h> #include "absl/status/status.h" #include "tensorflow/compiler/mlir/tf2xla/api/v1/compile_mlir_util.h" #include "tensorflow/compiler/tf2xla/xla_helpers.h" #include "xla/client/xla_computation.h" #include "xla/service/hlo.pb.h" #include "tensorflow/core/lib/monitoring/cell_reader.h" #include "tensorflow/core/lib/monitoring/counter.h" #include "tsl/platform/statusor.h" namespace {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sun Apr 14 20:29:34 UTC 2024 - 4.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/convert_xla_call_module_op_to_bfloat16.mlir
// RUN: stablehlo-quant-opt %s -split-input-file -tf-xla-call-module-serialization -stablehlo-convert-xla-call-module-op-to-bfloat16 -tf-xla-call-module-deserialization | FileCheck %s // ConvertXlaCallModuleOpToBfloat16Pass works on XlaCallModuleOps with // serialized modules. Which makes verification difficult. Therefore we add // (de)serialization passes so that the input and output are deserializated // StableHLO functions. // CHECK-LABEL: module module {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 08 22:40:14 UTC 2024 - 2.3K bytes - Viewed (0)