// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_translate --tflite-flatbuffer-to-mlir - -o - | FileCheck %s
// Confirm function references in if ops are preserved
func.func @main(%arg0: tensor<1xf32>, %arg1: tensor<1xf32>) -> tensor<1xf32> {
// CHECK:   %{{.*}} = "tf.If"(%{{.*}}, %{{.*}}, %{{.*}}) <{else_branch = @cond_false, is_stateless = false, then_branch = @cond_true}> : (tensor<1xi1>, tensor<1xf32>, tensor<1xf32>) -> tensor<1xf32>

namespace mlir {
namespace TFL {
namespace utils {

// Returns true if 'op' has type that is supported by native TFLite
// variables.
bool IsSupportedVariableType(Operation* op);

// Returns true if 'type' is supported by native tflite variables.
bool IsSupportedVariableType(ShapedType type);

}  // namespace utils
}  // namespace TFL
}  // namespace mlir

// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_translate --tflite-flatbuffer-to-mlir - -o - | FileCheck %s
// Confirm float constants and operators survive a roundtrip

func.func @main(tensor<4xf32>) -> tensor<4xf32> {
^bb0(%arg0: tensor<4xf32>):
  // CHECK:      [[CONST:%.*]] = "tfl.pseudo_const"() <{value = dense<1.000000e+00> : tensor<4xf32>}> : () -> tensor<4xf32>

   *
   * <p>This is guaranteed to return zero if the dataset contains a single pair of finite values. It
   * is not guaranteed to return zero when the dataset consists of the same pair of values multiple
   * times, due to numerical errors.
   *
   * <h3>Non-finite values</h3>
   *
   * <p>If the dataset contains any non-finite values ({@link Double#POSITIVE_INFINITY}, {@link

// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_translate --tflite-flatbuffer-to-mlir - -o -
// TODO(b/329300758): add file check back after the cl is fixed | FileCheck %s
// Check a few basic properties of the import-export,
// including constants retaining their shape
// and the module including the TFLite version.

func.func @main(tensor<3x2xi32>) -> tensor<3x2xi32> {
^bb0(%arg0: tensor<3x2xi32>):
  // CHECK: module attributes

#include <Python.h>

namespace tflite {

// Run target-aware-conversion for the given tflite model with the given device
// specs.
// Warning: The API is experimental and subject to change.
bool run_tac(const std::string& model_file_path,
             const std::vector<std::string>& device_specs,
             const std::string& model_output_path);

}  // namespace tflite

# FastAPI helfen – Hilfe erhalten

Gefällt Ihnen **FastAPI**?

Möchten Sie FastAPI, anderen Benutzern und dem Autor helfen?

Oder möchten Sie Hilfe zu **FastAPI** erhalten?

Es gibt sehr einfache Möglichkeiten zu helfen (manche erfordern nur ein oder zwei Klicks).

Und es gibt auch viele Möglichkeiten, Hilfe zu bekommen.

## Newsletter abonnieren

    assertThat(TWO_VALUES_PAIRED_STATS.populationCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(TWO_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / 2);
    // For datasets of many double values, we test many combinations of finite and non-finite
    // x-values:
    for (ManyValues values : ALL_MANY_VALUES) {
      PairedStats stats = createPairedStatsOf(values.asIterable(), OTHER_MANY_VALUES);
      double populationCovariance = stats.populationCovariance();

// Pattern definition file for direct lowering of mhlo composites to tflite ops.
include "mlir/IR/OpBase.td"
include "mlir/Dialect/Arith/IR/ArithOps.td"
include "mlir/Dialect/Func/IR/FuncOps.td"
include "mhlo/IR/hlo_ops.td"
include "tensorflow/compiler/mlir/lite/ir/tfl_ops.td"
include "tensorflow/compiler/mlir/lite/stablehlo/transforms/composite_utils.td"
include "tensorflow/compiler/mlir/lite/stablehlo/transforms/composite_avg_pool_patterns.td"

// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -emit-select-tf-ops=true -emit-builtin-tflite-ops=false -o - | flatbuffer_to_string - | FileCheck %s

func.func @main(%arg0: tensor<3x2xf32>) -> tensor<3x2xf32> {
// CHECK:  {
// CHECK-NEXT:    version: 3,
// CHECK-NEXT:    operator_codes: [ {
// CHECK-NEXT:      deprecated_builtin_code: 32,
// CHECK-NEXT:      custom_code: "FlexAddV2"
// CHECK-NEXT:      builtin_code: CUSTOM
// CHECK-NEXT:    } ],