- Sort Score
- Result 10 results
- Languages All
Results 1 - 4 of 4 for Howard (0.31 sec)
-
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) -
tensorflow/c/eager/gradients.cc
const char* raw_device_name, ForwardOperation* forward_op_) { forward_op_->op_name = op; forward_op_->attrs.Reset(op); return op_->Reset(op, raw_device_name); } Status AddInput(AbstractOperation* op_, AbstractTensorHandle* input, ForwardOperation* forward_op_) { TF_RETURN_IF_ERROR(op_->AddInput(input)); forward_op_->inputs.push_back(input); return absl::OkStatus(); }
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Feb 15 09:49:45 GMT 2024 - 19.3K bytes - Viewed (0) -
tensorflow/c/eager/parallel_device/parallel_device_lib.cc
device_threads_.emplace_back(new DeviceThread( devices[device_index].c_str(), is_async, in_flight_nodes_limit)); } } // Necessary for a unique_ptr to a forward-declared type. ParallelDevice::~ParallelDevice() = default; std::unique_ptr<ParallelTensor> ParallelDevice::CopyToParallelDevice( TFE_Context* context, TFE_TensorHandle* tensor, TF_Status* status) const {
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Fri Feb 09 07:47:20 GMT 2024 - 25.4K bytes - Viewed (1) -
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)