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.github/ISSUE_TEMPLATE/tflite-converter-issue.md
``` ### 3. Failure after conversion If the conversion is successful, but the generated model is wrong, then state what is wrong: - Model produces wrong results and/or has lesser accuracy. - Model produces correct results, but it is slower than expected. ### 4. (optional) RNN conversion support If converting TF RNN to TFLite fused RNN ops, please prefix [RNN] in the title.
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tensorflow/c/experimental/filesystem/modular_filesystem.h
#include "tensorflow/core/platform/file_system.h" /// This file builds classes needed to hold a filesystem implementation in the /// modular world. Once all TensorFlow filesystems are converted to use the /// plugin based approach, this file will replace the one in core/platform and /// the names will lose the `Modular` part. Until that point, the `Modular*` /// classes here are experimental and subject to breaking changes.
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tensorflow/c/eager/c_api_unified_experimental_internal.h
// ============================================================================= // Implementation detail for the unified execution APIs for Eager and tracing // backends (graph/MLIR). // // This defines a set of abstract classes that are intended to provide the // functionality of the opaque C types exposed in the public APIs defined in the // `c_api_unified_experimental.h` header.
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tensorflow/c/eager/c_api_unified_experimental.cc
// Public C API entry points // // These are only the generic entry points for the C API. This file does not // have any visibility into the graph/eager implementation and is only providing // C bindings to the abstract classes defined in the // c_api_unified_experimental_internal.h header. // // ============================================================================= using tensorflow::AbstractFunction;
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tensorflow/c/experimental/grappler/grappler_internal.h
See the License for the specific language governing permissions and limitations under the License. ==============================================================================*/ // Classes and utilities that work with Graph C API for internal use. // This includes functions used for optimizer registration and interfaces needed // for testing. #ifndef TENSORFLOW_C_EXPERIMENTAL_GRAPPLER_GRAPPLER_INTERNAL_H_
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