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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/c_api_experimental_test.cc
const std::vector<TF_Tensor*>& input_tensors, const absl::optional<std::vector<int64_t>>& expected_shape) { // Create input_shapes. TF_ShapeAndTypeList* input_shapes = TF_NewShapeAndTypeList(input_shapes_vec.size()); for (size_t i = 0; i < input_shapes_vec.size(); ++i) { const auto& input_shape = input_shapes_vec[i];
C++ - Registered: Tue Apr 23 12:39:09 GMT 2024 - Last Modified: Tue Jan 17 22:27:52 GMT 2023 - 13.1K bytes - Viewed (1) -
tensorflow/c/c_test_util.cc
void CSession::Run(TF_Status* s) { if (inputs_.size() != input_values_.size()) { ADD_FAILURE() << "Call SetInputs() before Run()"; return; } ResetOutputValues(); output_values_.resize(outputs_.size(), nullptr); const TF_Output* inputs_ptr = inputs_.empty() ? nullptr : &inputs_[0]; TF_Tensor* const* input_values_ptr = input_values_.empty() ? nullptr : &input_values_[0];
C++ - Registered: Tue Apr 23 12:39:09 GMT 2024 - Last Modified: Fri Oct 15 03:16:52 GMT 2021 - 17.8K bytes - Viewed (2) -
tensorflow/c/eager/unified_api_testutil.cc
std::vector<AbstractTensorHandle*> func_inputs; func_inputs.reserve(inputs.size()); TF_RETURN_IF_ERROR( CreateParamsForInputs(func_ctx.get(), inputs, &func_inputs)); std::vector<AbstractTensorHandle*> model_outputs; model_outputs.resize(outputs.size()); TF_RETURN_IF_ERROR(model(func_ctx.get(), absl::MakeSpan(func_inputs), absl::MakeSpan(model_outputs)));
C++ - Registered: Tue Apr 23 12:39:09 GMT 2024 - Last Modified: Tue Feb 27 13:57:45 GMT 2024 - 5.7K bytes - Viewed (0) -
tensorflow/c/eager/gradient_checker.h
namespace tensorflow { namespace gradients { /* Returns numerical grad inside `dtheta_approx` given `forward` model and * parameter specified by `input_index`. * * I.e. if y = <output of the forward model> and w = inputs[input_index], * this will calculate dy/dw numerically. * * `use_function` indicates whether to use graph mode(true) or eager(false). *
C - Registered: Tue Apr 23 12:39:09 GMT 2024 - Last Modified: Fri Dec 11 02:34:32 GMT 2020 - 1.8K bytes - Viewed (0) -
tensorflow/c/eager/c_api_remote_function_test.cc
bool has_packed_input = false) { return TestRemoteExecuteSilentCopies(async, remote, /*func=*/true, heavy_load_on_streaming_rpc, remote_func_outputs, has_packed_input); } TEST(CAPI, RemoteExecuteSilentCopiesAsyncFunc) {
C++ - Registered: Tue Apr 23 12:39:09 GMT 2024 - Last Modified: Fri Dec 11 22:56:03 GMT 2020 - 3.6K bytes - Viewed (0) -
tensorflow/c/eager/c_api_test.cc
int num_inputs = TFE_OpGetFlatInputCount(other, status); CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status); for (int input_index = 0; input_index < num_inputs; ++input_index) { TFE_TensorHandle* input = TFE_OpGetFlatInput(other, input_index, status); CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status); TFE_OpAddInput(ret, input, status);
C++ - Registered: Tue Apr 23 12:39:09 GMT 2024 - Last Modified: Thu Aug 03 20:50:20 GMT 2023 - 94.6K bytes - Viewed (1) -
tensorflow/c/eager/gradients.cc
void Tape::RecordOperation(absl::Span<AbstractTensorHandle* const> inputs, absl::Span<AbstractTensorHandle* const> outputs, GradientFunction* gradient_function, const string& op_name) { std::vector<int64_t> input_ids(inputs.size()); std::vector<tensorflow::DataType> input_dtypes(inputs.size()); for (int i = 0; i < inputs.size(); i++) { input_ids[i] = ToId(inputs[i]);
C++ - Registered: Tue Apr 23 12:39:09 GMT 2024 - Last Modified: Thu Feb 15 09:49:45 GMT 2024 - 19.3K bytes - Viewed (0) -
.github/ISSUE_TEMPLATE/tflite-other.md
false - type: input id: Mobile attributes: label: Mobile device description: placeholder: e.g., Linux Ubuntu 16.04 validations: required: false - type: input id: Python attributes: label: Python version description: placeholder: e.g., 3.9 validations: required: false - type: input id: Bazel attributes: label: Bazel version description: if
Plain Text - Registered: Tue Apr 23 12:39:09 GMT 2024 - Last Modified: Thu Dec 29 22:28:29 GMT 2022 - 3.4K bytes - Viewed (1) -
tensorflow/c/eager/unified_api_testutil.h
// Creates parameters (placeholders) in the tracing `ctx` using the shape and // dtype of `inputs`. Status CreateParamsForInputs(AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> inputs, std::vector<AbstractTensorHandle*>* params); // A callable that takes tensor inputs and returns zero or more tensor outputs. using Model = std::function<Status(AbstractContext*,
C - Registered: Tue Apr 23 12:39:09 GMT 2024 - Last Modified: Tue Feb 27 13:57:45 GMT 2024 - 4K bytes - Viewed (0)