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models.BUILD
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tensorflow/c/eager/unified_api_testutil.h
// outputs = tf.function(model)(inputs) // else: // outputs = model(inputs) Status RunModel(Model model, AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> inputs, absl::Span<AbstractTensorHandle*> outputs, bool use_function); Status BuildImmediateExecutionContext(bool use_tfrt, AbstractContext** ctx); // Return a tensor handle with given type, values and dimensions.
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tensorflow/c/experimental/gradients/grad_test_helper.h
void CompareNumericalAndAutodiffGradients( Model model, Model grad_model, AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> inputs, bool use_function, double abs_error = 1e-2); void CheckTensorValue(AbstractTensorHandle* t, absl::Span<const float> manuals, absl::Span<const int64_t> dims, double abs_error = 1e-2); Model BuildGradModel(Model forward, GradientRegistry registry);
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.github/ISSUE_TEMPLATE/tflite-other.md
false - type: input id: Cuda attributes: label: CUDA/cuDNN version description: placeholder: validations: required: false - type: input id: Gpu attributes: label: GPU model and memory description: if compiling from source placeholder: validations: required: false - type: textarea id: what-happened attributes: label: Current Behaviour?
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ci/official/containers/linux_arm64/devel.usertools/code_check_full.bats
cat > $BATS_TEST_TMPDIR/ignore_these_deps <<EOF benchmark _test$ _test.py$ _test_cpu$ _test_cpu.py$ _test_gpu$ _test_gpu.py$ _test_lib$ //tensorflow/cc/saved_model:saved_model_test_files //tensorflow/cc/saved_model:saved_model_half_plus_two //tensorflow:no_tensorflow_py_deps //tensorflow/tools/pip_package:win_pip_package_marker //tensorflow/core:image_testdata //tensorflow/core/lib/lmdb:lmdb_testdata
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tensorflow/c/experimental/gradients/nn_grad_test.cc
TF_RETURN_IF_ERROR(ops::SparseSoftmaxCrossEntropyWithLogits( ctx, inputs[0], inputs[1], &loss, &backprop, "SparseSoftmaxCrossEntropyWithLogits")); // `gradient_checker` only works with model that returns only 1 tensor. // Although, `ops::SparseSoftmaxCrossEntropyWithLogits` returns 2 tensors, the // second tensor isn't needed for computing gradient so we could safely drop // it. outputs[0] = loss;
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tensorflow/c/eager/gradient_checker.cc
RunModel(forward, ctx, inputs, model_outputs, use_function)); AbstractTensorHandlePtr model_out(model_outputs[0]); TF_Tensor* model_out_tensor; TF_RETURN_IF_ERROR(GetValue(model_out.get(), &model_out_tensor)); int num_dims_out = TF_NumDims(model_out_tensor); TF_DeleteTensor(model_out_tensor); // If the output is a scalar, then return the scalar output if (num_dims_out == 0) { outputs[0] = model_out.release();
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tensorflow/c/c_api_test.cc
SetViaProto(desc_, {}); FinishAndVerify(desc_, {}); } TEST(CAPI, SavedModel) { // Load the saved model. const string saved_model_dir = tensorflow::GetDataDependencyFilepath( tensorflow::io::JoinPath("tensorflow", "cc", "saved_model", "testdata", "half_plus_two", "00000123")); TF_SessionOptions* opt = TF_NewSessionOptions();
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.github/ISSUE_TEMPLATE/tflite-op-request.md
Provide a reproducible test case that is the bare minimum necessary to generate the problem. If possible, please share a link to Colab/Jupyter/any notebook. Also, please include a link to a GraphDef or the model if possible. **Any other info / logs** Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files
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README.md
* [TensorFlow Twitter](https://twitter.com/tensorflow) * [TensorFlow YouTube](https://www.youtube.com/channel/UC0rqucBdTuFTjJiefW5t-IQ) * [TensorFlow model optimization roadmap](https://www.tensorflow.org/model_optimization/guide/roadmap) * [TensorFlow White Papers](https://www.tensorflow.org/about/bib) * [TensorBoard Visualization Toolkit](https://github.com/tensorflow/tensorboard)
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