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Results 1 - 6 of 6 for Howard (0.23 sec)
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tensorflow/c/experimental/gradients/nn_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_; Status status_;
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/experimental/gradients/nn_grad.cc
namespace gradients { namespace { class ReluGradientFunction : public GradientFunction { public: explicit ReluGradientFunction(vector<AbstractTensorHandle*> f_outputs) : forward_outputs_(f_outputs) { for (auto output : forward_outputs_) { if (output) { output->Ref(); } } } Status Compute(AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> grad_outputs,
C++ - Registered: Tue Mar 26 12:39:09 GMT 2024 - Last Modified: Wed Feb 28 13:53:47 GMT 2024 - 5.7K bytes - Viewed (0) -
tensorflow/c/experimental/gradients/array_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_; Status status_;
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/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/eager/gradients_test.cc
t.reset(x_raw); } AbstractOperationPtr check_numerics_op(ctx->CreateOperation()); ForwardOperation forward_op; Status s = Reset(check_numerics_op.get(), "CheckNumerics", /*raw_device_name=*/nullptr, &forward_op); ASSERT_EQ(errors::OK, s.code()) << s.message(); if (isa<TracingOperation>(check_numerics_op.get())) {
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Feb 15 09:49:45 GMT 2024 - 7K bytes - Viewed (0) -
tensorflow/c/eager/gradient_checker.cc
Status RunAndMaybeSum(AbstractContext* ctx, Model forward, absl::Span<AbstractTensorHandle* const> inputs, absl::Span<AbstractTensorHandle*> outputs, bool use_function) { AbstractTensorHandle* model_outputs[1]; // Run the model. TF_RETURN_IF_ERROR( RunModel(forward, ctx, inputs, model_outputs, use_function));
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)