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.gitignore
.idea/** /build/ [Bb]uild/ /build_output/ /tensorflow/core/util/version_info.cc /tensorflow/python/framework/fast_tensor_util.cpp /tensorflow/lite/gen/** /tensorflow/lite/tools/make/downloads/** /tensorflow/lite/tools/make/gen/** /api_init_files_list.txt /estimator_api_init_files_list.txt *.whl # Android .gradle .idea *.iml local.properties gradleBuild # iOS *.pbxproj *.xcworkspace
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tensorflow/c/experimental/filesystem/modular_filesystem.cc
auto file = std::make_unique<TF_RandomAccessFile>(); std::string translated_name = TranslateName(fname); ops_->new_random_access_file(filesystem_.get(), translated_name.c_str(), file.get(), plugin_status.get()); if (TF_GetCode(plugin_status.get()) == TF_OK) *result = std::make_unique<ModularRandomAccessFile>(
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Wed Sep 06 19:12:29 GMT 2023 - 23.1K bytes - Viewed (0) -
ISSUES.md
If you open a GitHub Issue, here is our policy: 1. It must be a bug/performance issue or a feature request or a build issue or a documentation issue (for small doc fixes please send a PR instead). 1. Make sure the Issue Template is filled out. 1. The issue should be related to the repo it is created in. **Here's why we have this policy:** We want to focus on the work that benefits the whole community, e.g., fixing bugs and adding features. Individual support
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ci/official/envs/disk_cache
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.github/ISSUE_TEMPLATE/tflite-other.md
Build/Install - Performance - Support - Feature Request - Documentation Feature Request - Documentation Bug - Others validations: required: true - type: markdown attributes: value: | Please make sure that this is a bug. As per our [GitHub Policy](https://github.com/tensorflow/tensorflow/blob/master/ISSUES.md),we only address code/doc bugs, performance issues, feature requests and build/installation issues on GitHub.
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tensorflow/c/eager/unified_api_testutil.h
Status CreateParamsForInputs(AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> inputs, std::vector<AbstractTensorHandle*>* params); // A callable that takes tensor inputs and returns zero or more tensor outputs. using Model = std::function<Status(AbstractContext*, absl::Span<AbstractTensorHandle* const>,
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tensorflow/c/checkpoint_reader.cc
(*var_to_shape_map)[key] = TensorShape(entry.shape()); (*var_to_data_type_map)[key] = DataType(entry.dtype()); } // The returned pointers are owned by the caller. return std::make_pair(std::move(var_to_shape_map), std::move(var_to_data_type_map)); } } // namespace checkpoint
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tensorflow/c/eager/gradient_checker.cc
theta_inputs[input_index] = thetaMinus.get(); TF_RETURN_IF_ERROR( RunAndMaybeSum(ctx, forward, theta_inputs, f_outputs, use_function)); AbstractTensorHandlePtr fMinus(f_outputs[0]); // Take Difference of both estimates: (f(theta + eps) - f(theta - eps)). TF_RETURN_IF_ERROR( ops::Sub(ctx, fPlus.get(), fMinus.get(), f_outputs, "sub_top")); AbstractTensorHandlePtr fDiff(f_outputs[0]);
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Feb 15 09:49:45 GMT 2024 - 7.3K bytes - Viewed (0) -
tensorflow/c/eager/parallel_device/parallel_device_lib_test.cc
ParallelTensor::FromTensorHandles(parallel_device, std::move(mixed_handles), status.get()); ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK); // Can't take the shape of a parallel tensor with varying numbers of axes, but // running operations on them is OK. TF_ASSERT_OK(unknown_length_vector->Shape(&shape)); EXPECT_THAT(*shape, ElementsAre(-1));
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tensorflow/c/eager/tape.h
tensor_stack.pop_back(); auto op_id_it = tensor_tape.find(tensor_id); if (op_id_it == tensor_tape.end()) { continue; } int64_t op_id = op_id_it->second; auto op_it = op_tape->find(op_id); auto result_op_it = result.op_tape.find(op_id); if (op_id == -1 || op_it == op_tape->end() || result_op_it != result.op_tape.end()) { continue; }
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