[mlgo][nfc] Remove / fix vestigial references to Tensorflow

Some references in comments are unnecessarily specific, for historical reasons.

Author: mtrofin

llvm/include/llvm/Analysis/InlineAdvisor.h

@@ -36,9 +36,8 @@ struct ReplayInlinerSettings;
 ///
 /// - Development mode, for training new models.
 /// In this mode, we trade off runtime performance for flexibility. This mode
-/// requires the full C Tensorflow API library, and evaluates models
-/// dynamically. This mode also permits generating training logs, for offline
-/// training.
+/// requires the TFLite library, and evaluates models dynamically. This mode
+/// also permits generating training logs, for offline training.
 ///
 /// - Dynamically load an advisor via a plugin (PluginInlineAdvisorAnalysis)
 enum class InliningAdvisorMode : int { Default, Release, Development };

llvm/include/llvm/Analysis/InlineModelFeatureMaps.h

@@ -92,8 +92,8 @@ constexpr bool isHeuristicInlineCostFeature(InlineCostFeatureIndex Feature) {
 
 // List of features. Each feature is defined through a triple:
 // - the name of an enum member, which will be the feature index
-// - a textual name, used for Tensorflow model binding (so it needs to match the
-// names used by the Tensorflow model)
+// - a textual name, used for ML model binding (so it needs to match the
+// names used by the ML model).
 // - a documentation description. Currently, that is not used anywhere
 // programmatically, and serves as workaround to inability of inserting comments
 // in macros.

llvm/include/llvm/Analysis/MLModelRunner.h

@@ -17,7 +17,9 @@ namespace llvm {
 class LLVMContext;
 
 /// MLModelRunner interface: abstraction of a mechanism for evaluating a
-/// tensorflow "saved model".
+/// ML model. More abstractly, evaluating a function that has as tensors as
+/// arguments, described via TensorSpecs, and returns a tensor. Currently, the
+/// latter is assumed to be a scalar, in absence of more elaborate scenarios.
 /// NOTE: feature indices are expected to be consistent all accross
 /// MLModelRunners (pertaining to the same model), and also Loggers (see
 /// TFUtils.h)

llvm/include/llvm/Analysis/ModelUnderTrainingRunner.h

@@ -23,9 +23,10 @@
 
 namespace llvm {
 
-/// ModelUnderTrainingRunner - training mode implementation. It uses TF C APIs
+/// ModelUnderTrainingRunner - training mode implementation. It uses TFLite
 /// to dynamically load and evaluate a TF SavedModel
-/// (https://www.tensorflow.org/guide/saved_model). Runtime performance is
+/// (https://www.tensorflow.org/guide/saved_model) converted to TFLite. see
+/// lib/Analysis/models/saved-model-to-tflite.py. Runtime performance is
 /// sacrificed for ease of use while training.
 class ModelUnderTrainingRunner final : public MLModelRunner {
 public:

llvm/include/llvm/Analysis/TensorSpec.h

@@ -26,11 +26,15 @@ namespace llvm {
 /// Machine Learning on Heterogeneous Distributed Systems", section 4.2, para 2:
 /// https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/45166.pdf)
 ///
-/// Known tensor types. The left part is the C type, the right is a name we
-/// can use to identify the type (to implement TensorSpec equality checks), and
-/// to use, if needed, when mapping to an underlying evaluator's type system.
-/// The main requirement is that the C type we use has the same size and
-/// encoding (e.g. endian-ness) as the one used by the evaluator.
+/// Note that the design is motivated by Tensorflow, but it is not intended to
+/// be Tensorflow-specific.
+///
+/// Known tensor types. The left part is the C type, the
+/// right is a name we can use to identify the type (to implement TensorSpec
+/// equality checks), and to use, if needed, when mapping to an underlying
+/// evaluator's type system. The main requirement is that the C type we use has
+/// the same size and encoding (e.g. endian-ness) as the one used by the
+/// evaluator.
 #define SUPPORTED_TENSOR_TYPES(M)                                              \
   M(float, Float)                                                              \
   M(double, Double)                                                            \

llvm/include/llvm/Analysis/Utils/TFUtils.h

@@ -1,4 +1,4 @@
-//===- TFUtils.h - utilities for tensorflow C API ---------------*- C++ -*-===//
+//===- TFUtils.h - utilities for TFLite -------------------------*- C++ -*-===//
 //
 // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
 // See https://llvm.org/LICENSE.txt for license information.
@@ -93,7 +93,7 @@ class TFModelEvaluator final {
     return static_cast<T *>(getUntypedInput(Index));
   }
 
-  /// Returns true if the tensorflow model was loaded successfully, false
+  /// Returns true if the model was loaded successfully, false
   /// otherwise.
   bool isValid() const { return !!Impl; }
 

llvm/include/llvm/Config/llvm-config.h.cmake

@@ -98,7 +98,7 @@
 /* Define if zstd compression is available */
 #cmakedefine01 LLVM_ENABLE_ZSTD
 
-/* Define if LLVM is using tflite instead of libtensorflow */
+/* Define if LLVM is using tflite */
 #cmakedefine LLVM_HAVE_TFLITE
 
 /* Define to 1 if you have the <sysexits.h> header file. */

llvm/lib/Analysis/DevelopmentModeInlineAdvisor.cpp

@@ -6,7 +6,7 @@
 //
 //===----------------------------------------------------------------------===//
 //
-// This file implements a model runner using Tensorflow C APIs, allowing the
+// This file implements a model runner using TFLite, allowing the
 // loading of a model from a command line option.
 //
 //===----------------------------------------------------------------------===//

llvm/lib/Analysis/TFLiteUtils.cpp

@@ -1,12 +1,12 @@
-//===- TFUtils.cpp - tensorflow evaluation utilities ----------------------===//
+//===- TFUtils.cpp - TFLite-based evaluation utilities --------------------===//
 //
 // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
 // See https://llvm.org/LICENSE.txt for license information.
 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
 //
 //===----------------------------------------------------------------------===//
 //
-// This file implements utilities for interfacing with tensorflow C APIs.
+// This file implements utilities for interfacing with TFLite.
 //
 //===----------------------------------------------------------------------===//
 #include "llvm/Config/config.h"