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tensorflow/c/eager/gradient_checker_test.cc
// These tests should not be confused with `[*]_grad_test` which compare the // result of `gradient_checker` and `[*]_grad`. The tests here test the // functionality of `gradient_checker` by comparing the result with expected // manual user-provided gradients. class GradientCheckerTest : public ::testing::TestWithParam<std::tuple<const char*, bool, bool>> { protected: void SetUp() override {
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Fri Apr 14 10:03:59 GMT 2023 - 6.5K bytes - Viewed (0) -
.github/ISSUE_TEMPLATE/tflite-other.md
placeholder: e.g., 3.9 validations: required: false - type: input id: Bazel attributes: label: Bazel version description: if compiling from source placeholder: validations: required: false - type: input id: Compiler attributes: label: GCC/Compiler version description: if compiling from source placeholder: validations: required: false - type: input id: Cuda attributes: label: CUDA/cuDNN version description:
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tensorflow/c/experimental/gradients/nn_grad_test.cc
// `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; backprop->Unref(); return absl::OkStatus(); } Status BiasAddModel(AbstractContext* ctx,
C++ - Registered: Tue Mar 26 12:39:09 GMT 2024 - Last Modified: Wed Feb 28 13:53:47 GMT 2024 - 8.3K bytes - Viewed (0) -
tensorflow/c/eager/immediate_execution_tensor_handle.h
// Returns size of specified dimension // // -1 indicates an unknown axis length; this is unreachable for most standard // ImmediateExecutionTensorHandles, but comes up for example when computing // the shape of a parallel tensor with component shapes differing across // devices. virtual Status Dim(int dim_index, int64_t* dim) const = 0; // Returns the device which created the handle.
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tensorflow/c/eager/c_api_unified_experimental_test.cc
ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s); auto* arg1 = TF_AddFunctionParameter(graph_ctx, TF_FLOAT, {-1, nullptr}, s); ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s); // Create a first "Add" computing `arg0 + arg1`. TF_AbstractTensor* add_output1; { // Build an abstract operation, inputs and output. auto* add_op = TF_NewAbstractOp(graph_ctx); TF_AbstractOpSetOpType(add_op, "Add", s);
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Fri May 19 21:44:52 GMT 2023 - 39.1K bytes - Viewed (0) -
tensorflow/c/eager/immediate_execution_tensor_handle.cc
std::string shape_string; if (Shape(&shape).ok()) { shape_string = shape.DebugString(); } else { shape_string = "<error computing shape>"; } std::string value_string; if (!SummarizeValue(value_string).ok()) { value_string = "<error computing value>"; } if (value_string.length() > 100) { // The default NumPy-style output can be distractingly long in error // messages.
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tensorflow/c/experimental/gradients/array_grad_test.cc
TF_RETURN_IF_ERROR( ops::IdentityN(ctx, inputs, absl::MakeSpan(temp_outputs), "IdentityN")); // Although, `ops::IdentityN` returns 2 tensors, the first tensor isn't needed // for computing gradient so we could safely drop it. outputs[0] = temp_outputs[1]; temp_outputs[0]->Unref(); return absl::OkStatus(); } class CppGradients
C++ - Registered: Tue Mar 26 12:39:09 GMT 2024 - Last Modified: Wed Feb 28 13:53:47 GMT 2024 - 5K bytes - Viewed (0) -
SECURITY.md
in TensorFlow ops can be recognized as security issues only if they are reachable and exploitable through production-grade, benign models. ### Compilation Compiling models via the recommended entry points described in [XLA](https://www.tensorflow.org/xla) and [JAX](https://jax.readthedocs.io/en/latest/jax-101/02-jitting.html)
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tensorflow/c/eager/gradients.h
#include "tensorflow/c/eager/tape.h" #include "tensorflow/core/common_runtime/eager/attr_builder.h" namespace tensorflow { namespace gradients { // =============== Experimental C++ API for computing gradients =============== // Sample gradient function: // // class AddGradientFunction : public GradientFunction { // public: // Status Compute(Context* ctx,
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ci/official/utilities/setup_macos.sh
# VMs. export CLOUDSDK_PYTHON=$(which python3.11) gcloud auth activate-service-account --key-file="${GOOGLE_APPLICATION_CREDENTIALS}" fi set -x # When cross-compiling with RBE, we need to copy the macOS sysroot to be # inside the TensorFlow root directory. We then define them as a filegroup # target inside "tensorflow/tools/toolchains/cross_compile/cc" so that Bazel
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