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CONTRIBUTING.md
your response for more than 2 weeks. **4. Approved** - Once the PR is approved, it gets `kokoro:force-run` label applied and it initiates CI/CD tests. - We can't move forward if these tests fail. - In such situations, we may request you to make further changes to your PR for the tests to pass. - Once the tests pass, we now bring all the code into the internal code base,
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tensorflow/c/experimental/gradients/math_grad.cc
C++ - Registered: Tue Mar 26 12:39:09 GMT 2024 - Last Modified: Wed Feb 28 13:53:47 GMT 2024 - 15.2K bytes - Viewed (0) -
tensorflow/c/eager/gradients.h
// } // ~AddGradientFunction() override {} // }; // // GradientFunction* AddRegisterer(const ForwardOperation& op) { // // More complex gradient functions can use inputs/attrs etc. from the // // forward `op`. // return new AddGradientFunction; // } // // Status RegisterGradients(GradientRegistry* registry) { // return registry->Register("Add", AddRegisterer); // } class GradientFunction { public:
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Mon Sep 26 10:27:05 GMT 2022 - 6.9K bytes - Viewed (0) -
tensorflow/c/eager/gradient_checker_test.cc
ASSERT_EQ(errors::OK, s.code()) << s.message(); ctx_.reset(ctx_raw); } // Computing numerical gradients with TensorFloat-32 is numerically // unstable. Some forward pass tests also fail with TensorFloat-32 due to // low tolerances enable_tensor_float_32_execution(false); } AbstractContextPtr ctx_; public:
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) -
RELEASE.md
backwards. See PR [47925](https://github.com/tensorflow/tensorflow/pull/47925). * `tf.image.crop_and_resize` gradient w.r.t. either `image` or `boxes`. See PR [48905](https://github.com/tensorflow/tensorflow/pull/48905). * `tf.sparse.sparse_dense_matmul` forwards. See PR
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tensorflow/c/eager/tape.h
forward_grads.resize(output_tensors.size()); TF_RETURN_IF_ERROR(ForwardpropFromTape( op_type, output_tensors, backward_function_getter, backward_function_deleter, in_grads, absl::MakeSpan(forward_grads))); } else { TF_RETURN_IF_ERROR( (*forward_function)(in_grads, &forward_grads, use_batch_)); } for (int i = 0; i < forward_grads.size(); ++i) { if (forward_grads[i] != nullptr) {
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tensorflow/c/experimental/gradients/grad_test_helper.cc
ASSERT_NEAR(manuals[j], danalytical[j], abs_error); } } TF_DeleteTensor(analytical_tensor); delete[] danalytical; } Model BuildGradModel(Model forward, GradientRegistry registry) { return [forward_model = std::move(forward), grad_registry = std::move(registry)]( AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> inputs,
C++ - Registered: Tue Mar 26 12:39:09 GMT 2024 - Last Modified: Wed Feb 28 13:53:47 GMT 2024 - 5K bytes - Viewed (0) -
tensorflow/c/experimental/gradients/tape/tape_operation.h
// For LLVM style RTTI. static bool classof(const AbstractOperation* ptr) { return ptr->getKind() == kTape; } ~TapeOperation() override; private: AbstractOperation* parent_op_; ForwardOperation forward_op_; Tape* tape_; const GradientRegistry& registry_; }; } // namespace gradients } // namespace tensorflow
C - Registered: Tue Feb 27 12:39:08 GMT 2024 - Last Modified: Wed Sep 23 23:12:39 GMT 2020 - 3.7K bytes - Viewed (1) -
tensorflow/c/experimental/gradients/math_grad_test.cc
ASSERT_EQ(errors::OK, status_.code()) << status_.message(); immediate_execution_ctx_.reset(ctx_raw); } // Computing numerical gradients with TensorFloat-32 is numerically // unstable. Some forward pass tests also fail with TensorFloat-32 due to // low tolerances enable_tensor_float_32_execution(false); } AbstractContextPtr immediate_execution_ctx_; GradientRegistry registry_;
C++ - Registered: Tue Mar 26 12:39:09 GMT 2024 - Last Modified: Thu Apr 13 17:32:14 GMT 2023 - 16.3K bytes - Viewed (0) -
.bazelrc
# This is the same as the official TensorFlow builds. # See https://developer.nvidia.com/cuda-gpus#compute # `compute_XY` enables PTX embedding in addition to SASS. PTX # is forward compatible beyond the current compute capability major # release while SASS is only forward compatible inside the current # major release. Example: sm_80 kernels can run on sm_89 GPUs but # not on sm_90 GPUs. compute_80 kernels though can also run on sm_90 GPUs.
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