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tensorflow/c/eager/tfe_context_internal.h
==============================================================================*/ #ifndef TENSORFLOW_C_EAGER_TFE_CONTEXT_INTERNAL_H_ #define TENSORFLOW_C_EAGER_TFE_CONTEXT_INTERNAL_H_ #include "tensorflow/c/conversion_macros.h" #include "tensorflow/c/eager/immediate_execution_context.h" // Wraps a pointer to a context implementation. // // WARNING: Since the underlying object could be ref-counted a user of this
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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/eager/tfe_op_internal.h
// TFE_DeleteOp who calls Release() on the operation pointer and deletes // the TFE_Op structure. typedef struct TFE_Op TFE_Op; namespace tensorflow { DEFINE_CONVERSION_FUNCTIONS(tensorflow::ImmediateExecutionOperation, TFE_Op); DEFINE_CONVERSION_FUNCTIONS(tensorflow::ImmediateExecutionOperation*, TFE_Op*); } // namespace tensorflow
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tensorflow/c/eager/tfe_tensorhandle_internal.h
// the TFE_TensorHandle structure. typedef struct TFE_TensorHandle TFE_TensorHandle; namespace tensorflow { DEFINE_CONVERSION_FUNCTIONS(tensorflow::ImmediateExecutionTensorHandle, TFE_TensorHandle); DEFINE_CONVERSION_FUNCTIONS(tensorflow::ImmediateExecutionTensorHandle*, TFE_TensorHandle*); } // namespace tensorflow
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tensorflow/c/eager/tfe_cancellation_manager_internal.h
#include "tensorflow/c/conversion_macros.h" #include "tensorflow/core/framework/cancellation.h" struct TFE_CancellationManager; typedef struct TFE_CancellationManager TFE_CancellationManager; namespace tensorflow { DEFINE_CONVERSION_FUNCTIONS(tensorflow::CancellationManager, TFE_CancellationManager); DEFINE_CONVERSION_FUNCTIONS(tensorflow::CancellationManager*,
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tensorflow/c/eager/tfe_op_attrs_internal.h
==============================================================================*/ #ifndef TENSORFLOW_C_EAGER_TFE_OP_ATTRS_INTERNAL_H_ #define TENSORFLOW_C_EAGER_TFE_OP_ATTRS_INTERNAL_H_ #include "tensorflow/c/conversion_macros.h" #include "tensorflow/c/eager/abstract_op_attrs.h" #include "tensorflow/c/tf_status.h" #include "tensorflow/core/framework/attr_value.pb.h"
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tensorflow/c/BUILD
"//tensorflow/core:protos_all_cc", # TODO(b/74620627): remove when _USE_C_SHAPES is removed ], alwayslink = 1, ) cc_library( name = "conversion_macros", hdrs = [ "conversion_macros.h", ], visibility = ["//tensorflow:__subpackages__"], ) cc_library( name = "c_op_requires", hdrs = ["c_op_requires.h"],
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tensorflow/c/conversion_macros.h
limitations under the License. ==============================================================================*/ #ifndef TENSORFLOW_C_CONVERSION_MACROS_H_ #define TENSORFLOW_C_CONVERSION_MACROS_H_ #define DEFINE_CONVERSION_FUNCTIONS(cpp_impl, wrapper) \ inline cpp_impl *unwrap(wrapper *w) { \
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tensorflow/c/eager/c_api.h
TF_CAPI_EXPORT extern void TFE_ContextEndStep(TFE_Context* ctx); #ifdef __cplusplus } /* end extern "C" */ #endif #ifdef __cplusplus // A workaround to ease conversion to and from numpy objects and // TFE_TensorHandle's. // // TODO(ashankar): Figure out an alternative scheme that precludes the need for // these API-boundary breaking methods. namespace tensorflow { class Tensor;
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tensorflow/c/c_api.cc
// DT_RESOURCE. The string serialization is converted back to a // ResourceHandle during Session run where the TF_Tensor is converted to a // Tensor. // TFv2 does not depend on this conversion. There is no matching // TF_TensorFromTensorV1 because the conversion to string is performed by the // python side of Session. static Status TF_TensorToTensorV1(const TF_Tensor* src, Tensor* dst) { Status status = TF_TensorToTensor(src, dst);
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