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ci/official/debug_tfci.sh
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/tensorflow/c/eager @qqfish /tensorflow/core/common_runtime/eager @qqfish /tenosrflow/core/debug @caisq /tensorflow/core/kernels/mkl/ @penpornk /tensorflow/core/kernels/sparse/ @penpornk /tensorflow/core/nccl/ @azaks2 @chsigg /tensorflow/python/autograph/ @mdanatg /tensorflow/python/debug @caisq /tensorflow/python/eager @rohan100jain /tensorflow/tools/docs/ @markdaoust /tensorflow/compiler/mlir/ @aminim
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CONTRIBUTING.md
debugging information with `--config=dbg`, as issues occur on Linux if there is too much debug info (see [this GitHub issue](https://github.com/tensorflow/tensorflow/issues/48919) for context). If you want to debug a kernel, you can compile specific files with `-g` using the `--per_file_copt` bazel option. For example, if you want to debug the Identity op, which are in files starting with `identity_op`, you can run ```bash
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tensorflow/c/eager/c_api.h
// that produces `handle` has completed. TF_CAPI_EXPORT extern TFE_TensorDebugInfo* TFE_TensorHandleTensorDebugInfo( TFE_TensorHandle* h, TF_Status* status); // Deletes `debug_info`. TF_CAPI_EXPORT extern void TFE_DeleteTensorDebugInfo( TFE_TensorDebugInfo* debug_info); // Returns the number of dimensions used to represent the tensor on its device. // The number of dimensions used to represent the tensor on device can be
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tensorflow/c/eager/abstract_tensor_handle.h
// can be used to set a FullTypeDef based on dtype in a derived class if // appropriate. virtual tensorflow::FullTypeDef FullType() const = 0; // The default debug string includes a shape, dtype and FullType. // Implementations are free to override it with something more informative. virtual std::string DebugString() const; AbstractTensorHandleKind getKind() const { return kind_; }
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tensorflow/c/eager/BUILD
], deps = [ ":immediate_execution_operation", "//tensorflow/c:conversion_macros", ], ) cc_library( name = "tfe_tensor_debug_info_internal", hdrs = ["tfe_tensor_debug_info_internal.h"], visibility = ["//visibility:private"], deps = [ "//tensorflow/core:lib", ], ) cc_library( name = "tfe_tensorhandle_internal",
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tensorflow/c/c_api_experimental.cc
tensorflow::mutex_lock c(graph->mu); const auto& debug_str = graph->graph.ToGraphDefDebug().DebugString(); *len = debug_str.size(); char* ret = static_cast<char*>(malloc(*len + 1)); memcpy(ret, debug_str.c_str(), *len + 1); return ret; } char* TF_FunctionDebugString(TF_Function* func, size_t* len) { const auto& debug_str = DebugString(func->record->fdef()); *len = debug_str.size();
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tensorflow/c/eager/c_api_internal.h
#include "tensorflow/c/eager/tfe_monitoring_internal.h" // IWYU pragma: export #include "tensorflow/c/eager/tfe_op_attrs_internal.h" // IWYU pragma: export #include "tensorflow/c/eager/tfe_tensor_debug_info_internal.h" // IWYU pragma: export // TODO(b/154564140): Move this to its own header. This requires splitting // c_api_experimental.h struct TFE_ContextOptions { TF_SessionOptions session_options;
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.bazelrc
build:nvcc_clang --@local_config_cuda//:cuda_compiler=nvcc # Debug config build:dbg -c dbg # Only include debug info for files under tensorflow/, excluding kernels, to # reduce the size of the debug info in the binary. This is because if the debug # sections in the ELF binary are too large, errors can occur. See # https://github.com/tensorflow/tensorflow/issues/48919. # Users can still include debug info for a specific kernel, e.g. with:
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tensorflow/c/eager/c_api_experimental.cc
"Unable to find function with name: ", function_name); return; } tensorflow::GraphDebugInfo debug_info = tensorflow::StackTracesMapToGraphDebugInfo( function_record->stack_traces()); string str = debug_info.SerializeAsString(); void* data = tensorflow::port::Malloc(str.length()); str.copy(static_cast<char*>(data), str.length(), 0); buf->data = data;
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