Remove if_mlir_tflite build flag.
PiperOrigin-RevId: 264920065
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@ -1,5 +1,5 @@
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load("//tensorflow:tensorflow.bzl", "tf_py_wrap_cc")
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load("//tensorflow:tensorflow.bzl", "tf_py_wrap_cc")
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load("//tensorflow:tensorflow.bzl", "if_mlir_tflite", "py_binary", "tf_py_test")
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load("//tensorflow:tensorflow.bzl", "py_binary", "tf_py_test")
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package(
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package(
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default_visibility = [
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default_visibility = [
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@ -22,10 +22,6 @@ cc_library(
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name = "toco_python_api",
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name = "toco_python_api",
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srcs = ["toco_python_api.cc"],
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srcs = ["toco_python_api.cc"],
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hdrs = ["toco_python_api.h"],
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hdrs = ["toco_python_api.h"],
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defines = if_mlir_tflite(
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if_false = [],
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if_true = ["TFLITE_BUILD_WITH_MLIR_CONVERTER"],
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),
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visibility = [
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visibility = [
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"//tensorflow/python:__subpackages__",
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"//tensorflow/python:__subpackages__",
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],
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],
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@ -39,6 +35,7 @@ cc_library(
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"//tensorflow/lite/toco:toco_port",
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"//tensorflow/lite/toco:toco_port",
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"//tensorflow/lite/toco:toco_tooling",
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"//tensorflow/lite/toco:toco_tooling",
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"//tensorflow/core:protos_all_cc",
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"//tensorflow/core:protos_all_cc",
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"//tensorflow/compiler/mlir/lite/python:graphdef_to_tfl_flatbuffer",
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] + select({
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] + select({
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# This is required when running `tflite_convert` from `bazel`.
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# This is required when running `tflite_convert` from `bazel`.
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# It requires to link with TensorFlow Ops to get the op definitions.
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# It requires to link with TensorFlow Ops to get the op definitions.
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@ -46,10 +43,7 @@ cc_library(
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"//tensorflow/core:ops",
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"//tensorflow/core:ops",
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],
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],
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"//conditions:default": [],
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"//conditions:default": [],
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}) + if_mlir_tflite(
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}),
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if_false = [],
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if_true = ["//tensorflow/compiler/mlir/lite/python:graphdef_to_tfl_flatbuffer"],
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),
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)
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)
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# Compatibility stub. Remove when internal customers moved.
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# Compatibility stub. Remove when internal customers moved.
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@ -18,6 +18,7 @@ limitations under the License.
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#include <string>
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#include <string>
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#include <vector>
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#include <vector>
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#include "tensorflow/compiler/mlir/lite/python/graphdef_to_tfl_flatbuffer.h"
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#include "tensorflow/core/platform/logging.h"
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#include "tensorflow/core/platform/logging.h"
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#include "tensorflow/lite/python/interpreter_wrapper/python_utils.h"
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#include "tensorflow/lite/python/interpreter_wrapper/python_utils.h"
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#include "tensorflow/lite/toco/import_tensorflow.h"
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#include "tensorflow/lite/toco/import_tensorflow.h"
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@ -28,11 +29,6 @@ limitations under the License.
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#include "tensorflow/lite/toco/toco_tooling.h"
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#include "tensorflow/lite/toco/toco_tooling.h"
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#include "tensorflow/lite/toco/toco_types.h"
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#include "tensorflow/lite/toco/toco_types.h"
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#if defined(TFLITE_BUILD_WITH_MLIR_CONVERTER)
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#include "tensorflow/compiler/mlir/lite/python/graphdef_to_tfl_flatbuffer.h"
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#endif
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#include "tensorflow/core/protobuf/graph_debug_info.pb.h"
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namespace toco {
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namespace toco {
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// NOTE(aselle): We are using raw PyObject's here because we want to make
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// NOTE(aselle): We are using raw PyObject's here because we want to make
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@ -124,18 +120,9 @@ PyObject* TocoConvert(PyObject* model_flags_proto_txt_raw,
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// Convert model.
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// Convert model.
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if (enable_mlir_converter) {
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if (enable_mlir_converter) {
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#if defined(TFLITE_BUILD_WITH_MLIR_CONVERTER)
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status = tensorflow::ConvertGraphDefToTFLiteFlatBuffer(
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status = tensorflow::ConvertGraphDefToTFLiteFlatBuffer(
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model_flags, toco_flags, debug_info, graph_def,
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model_flags, toco_flags, debug_info, graph_def,
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&output_file_contents_txt);
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&output_file_contents_txt);
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#else
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// TODO(b/124314620): Remove this condition.
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PyErr_SetString(PyExc_RuntimeError,
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"This flag is not supported by this version of the "
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"TFLite converter. This functionality is being "
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"actively worked on.");
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return nullptr;
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#endif
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} else {
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} else {
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model = toco::Import(toco_flags, model_flags, input_contents_txt);
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model = toco::Import(toco_flags, model_flags, input_contents_txt);
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toco::Transform(toco_flags, model.get());
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toco::Transform(toco_flags, model.get());
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@ -2556,9 +2556,5 @@ def if_mlir(if_true, if_false = []):
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"//tensorflow:with_mlir_support": if_true,
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"//tensorflow:with_mlir_support": if_true,
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})
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})
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# TODO(b/138724071): Remove when build is stable.
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def if_mlir_tflite(if_true, if_false = []):
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return if_true # Internally we always build with MLIR.
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def tfcompile_extra_flags():
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def tfcompile_extra_flags():
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return ""
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return ""
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