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tensorflow/c/eager/tfe_monitoring_internal.h
template <int NumLabels> struct TFE_MonitoringCounter { template <typename... LabelDesc> TFE_MonitoringCounter(const char* name, const char* description, LabelDesc&&... label) { counter = absl::WrapUnique(tensorflow::monitoring::Counter<NumLabels>::New( name, description, label...)); } std::unique_ptr<tensorflow::monitoring::Counter<NumLabels>> counter; };
C - Registered: Tue Apr 23 12:39:09 GMT 2024 - Last Modified: Wed Aug 11 01:20:50 GMT 2021 - 5.2K bytes - Viewed (0) -
tensorflow/c/eager/c_api_experimental.h
// the object. Using duplicate metric name will crash the program with fatal // error. TF_CAPI_EXPORT extern TFE_MonitoringCounter0* TFE_MonitoringNewCounter0( const char* name, TF_Status* status, const char* description); // Deletes the Counter object. TF_CAPI_EXPORT extern void TFE_MonitoringDeleteCounter0( TFE_MonitoringCounter0* counter); // Retrieves the cell from the Counter object. The Counter object will manage
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tensorflow/c/eager/c_api_experimental_reader_test.cc
CHECK_EQ(actual, 1); } TFE_MonitoringCounter0* CreateCounter0(const char* counter_name) { TF_Status* status = TF_NewStatus(); auto* counter = TFE_MonitoringNewCounter0(counter_name, status, "description"); TF_DeleteStatus(status); return counter; } void IncrementCounter0(TFE_MonitoringCounter0* counter, int64_t delta) { auto* cell = TFE_MonitoringGetCellCounter0(counter);
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.github/workflows/release-branch-cherrypick.yml
# on that branch for a workflow.yml file, and we'd have to cherry-pick # this file into those branches. release_branch: description: 'Release branch name (e.g. r2.9)' required: true type: string git_commit: description: 'Git commit to cherry-pick' required: true type: string permissions: contents: read jobs: cherrypick:
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.github/ISSUE_TEMPLATE/tflite-other.md
- type: dropdown id: source attributes: label: Source description: Tensorflow installed from options: - source - binary validations: required: true - type: input id: tfversion attributes: label: Tensorflow Version description: placeholder: ex,. tf 2.8 validations: required: true - type: dropdown id: Code attributes: label: Custom Code description: options: - "Yes" - "No" validations: required: true
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tensorflow/c/experimental/grappler/BUILD
# Description: # Graph C API. load("//tensorflow/core/platform:rules_cc.bzl", "cc_library") load( "//tensorflow:tensorflow.bzl", "tf_cc_test", ) package( # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"], licenses = ["notice"], ) cc_library( name = "grappler_hdrs", hdrs = ["grappler.h"], visibility = ["//tensorflow:internal"], deps = [
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.github/ISSUE_TEMPLATE/tensorflow_issue_template.yaml
label: Bazel version description: If compiling from source - type: input id: Compiler attributes: label: GCC/compiler version description: If compiling from source - type: input id: Cuda attributes: label: CUDA/cuDNN version - type: input id: Gpu attributes: label: GPU model and memory description: If compiling from source - type: textarea
Others - Registered: Tue Apr 23 12:39:09 GMT 2024 - Last Modified: Wed Jun 28 18:25:42 GMT 2023 - 3.7K bytes - Viewed (0) -
ci/official/wheel_test/README.md
to the `../wheel_test/` directory. ### How it Works in the Presubmit Job `_requirements_lock` files will be generated by the presubmit job. A detailed description will be provided once it's integrated into presubmit. ### test_import_api_packages This Python test verifies whether the API v2 packages can be imported from the
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CONTRIBUTING.md
`comp:` etc. At this stage we check if the PR is valid and meets certain quality requirements. For example, we check if the CLA is signed, PR has sufficient description, if applicable unit tests are added, if it is a reasonable contribution (meaning it is not a single liner cosmetic PR). **2. Valid?** - If the PR passes all the quality checks then we go ahead and assign a
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tensorflow/c/eager/c_api.h
// The return value was current at the time of TFE_TensorDebugInfo creation. TF_CAPI_EXPORT extern int64_t TFE_TensorDebugInfoOnDeviceDim( TFE_TensorDebugInfo* debug_info, int dim_index); // Description of the TensorFlow op to execute. // // Assumes that the provided 'ctx' outlives the returned TFE_Op, i.e., // TFE_DeleteOp() is called before TFE_DeleteContext(). //
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