1 /* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
2
3 Licensed under the Apache License, Version 2.0 (the "License");
4 you may not use this file except in compliance with the License.
5 You may obtain a copy of the License at
6
7 http://www.apache.org/licenses/LICENSE-2.0
8
9 Unless required by applicable law or agreed to in writing, software
10 distributed under the License is distributed on an "AS IS" BASIS,
11 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12 See the License for the specific language governing permissions and
13 limitations under the License.
14 ==============================================================================*/
15 #include "tensorflow/c/eager/unified_api_testutil.h"
16
17 #include "absl/container/flat_hash_set.h"
18 #include "tensorflow/c/eager/c_api_experimental.h"
19 #include "tensorflow/c/eager/c_api_test_util.h"
20 #include "tensorflow/c/eager/c_api_unified_experimental.h"
21 #include "tensorflow/c/eager/c_api_unified_experimental_internal.h"
22 #include "tensorflow/c/tf_status.h"
23 #include "tensorflow/c/tf_status_helper.h"
24 #include "tensorflow/core/framework/tensor_shape.h"
25 #include "tensorflow/core/lib/llvm_rtti/llvm_rtti.h"
26 #include "tensorflow/core/platform/errors.h"
27
28 namespace tensorflow {
29
BuildFunction(const char * fn_name)30 AbstractContext* BuildFunction(const char* fn_name) {
31 std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status(
32 TF_NewStatus(), TF_DeleteStatus);
33 TF_ExecutionContext* graph_ctx = TF_CreateFunction(fn_name, status.get());
34 return unwrap(graph_ctx);
35 }
36
CreateParamsForInputs(AbstractContext * ctx,absl::Span<AbstractTensorHandle * const> inputs,std::vector<AbstractTensorHandle * > * params)37 Status CreateParamsForInputs(AbstractContext* ctx,
38 absl::Span<AbstractTensorHandle* const> inputs,
39 std::vector<AbstractTensorHandle*>* params) {
40 tracing::TracingTensorHandle* handle = nullptr;
41 for (auto input : inputs) {
42 PartialTensorShape shape;
43 TF_RETURN_IF_ERROR(input->Shape(&shape));
44 TF_RETURN_IF_ERROR(dyn_cast<tracing::TracingContext>(ctx)->AddParameter(
45 input->DataType(), shape, &handle));
46 params->emplace_back(handle);
47 }
48 return OkStatus();
49 }
50
51 // Runs `model` maybe wrapped in a function.
RunModel(Model model,AbstractContext * ctx,absl::Span<AbstractTensorHandle * const> inputs,absl::Span<AbstractTensorHandle * > outputs,bool use_function)52 Status RunModel(Model model, AbstractContext* ctx,
53 absl::Span<AbstractTensorHandle* const> inputs,
54 absl::Span<AbstractTensorHandle*> outputs, bool use_function) {
55 if (use_function) {
56 const char* fn_name = "test_fn";
57 core::RefCountPtr<AbstractFunction> scoped_func;
58 // Returning null tensors from a tf.function is not supported, so we keep
59 // track of indices in the model's outputs are nullptr in this set.
60 // The FunctionDef only outputs the non-null tensors. We later pad the
61 // function op outputs to have nullptrs at the `null_indices`.
62 absl::flat_hash_set<int> null_indices;
63 {
64 AbstractContextPtr func_ctx(BuildFunction(fn_name));
65 std::vector<AbstractTensorHandle*> func_inputs;
66 func_inputs.reserve(inputs.size());
67 TF_RETURN_IF_ERROR(
68 CreateParamsForInputs(func_ctx.get(), inputs, &func_inputs));
69 std::vector<AbstractTensorHandle*> model_outputs;
70 model_outputs.resize(outputs.size());
71 TF_RETURN_IF_ERROR(model(func_ctx.get(), absl::MakeSpan(func_inputs),
72 absl::MakeSpan(model_outputs)));
73 for (auto func_input : func_inputs) {
74 func_input->Unref();
75 }
76 AbstractFunction* func = nullptr;
77 OutputList output_list;
78 output_list.expected_num_outputs = 0;
79 output_list.outputs.reserve(outputs.size());
80 for (int i = 0; i < model_outputs.size(); i++) {
81 if (model_outputs[i]) {
82 output_list.outputs.emplace_back(model_outputs[i]);
83 output_list.expected_num_outputs += 1;
84 } else {
85 null_indices.insert(i);
86 }
87 }
88 TF_RETURN_IF_ERROR(dyn_cast<tracing::TracingContext>(func_ctx.get())
89 ->Finalize(&output_list, &func));
90 scoped_func.reset(func);
91 for (auto output : output_list.outputs) {
92 output->Unref();
93 }
94 TF_RETURN_IF_ERROR(ctx->RegisterFunction(func));
95 }
96
97 AbstractOperationPtr fn_op(ctx->CreateOperation());
98 TF_RETURN_IF_ERROR(fn_op->Reset(fn_name, /*raw_device_name=*/nullptr));
99 for (auto input : inputs) {
100 TF_RETURN_IF_ERROR(fn_op->AddInput(input));
101 }
102 int retvals = outputs.size() - null_indices.size();
103 std::vector<AbstractTensorHandle*> fn_outputs(retvals);
104 TF_RETURN_IF_ERROR(fn_op->Execute(
105 absl::Span<AbstractTensorHandle*>(fn_outputs.data(), fn_outputs.size()),
106 &retvals));
107 int skipped_indices = 0;
108 for (int i = 0; i < outputs.size(); i++) {
109 if (!null_indices.contains(i)) {
110 outputs[i] = fn_outputs[i - skipped_indices];
111 } else {
112 skipped_indices += 1;
113 }
114 }
115 TF_RETURN_IF_ERROR(ctx->RemoveFunction(fn_name));
116 return OkStatus();
117 } else {
118 return model(ctx, inputs, outputs);
119 }
120 }
121
BuildImmediateExecutionContext(bool use_tfrt,AbstractContext ** ctx)122 Status BuildImmediateExecutionContext(bool use_tfrt, AbstractContext** ctx) {
123 std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status(
124 TF_NewStatus(), TF_DeleteStatus);
125 TFE_ContextOptions* opts = TFE_NewContextOptions();
126 TFE_ContextOptionsSetTfrt(opts, use_tfrt);
127 *ctx = unwrap(TF_NewEagerExecutionContext(opts, status.get()));
128 TF_RETURN_IF_ERROR(StatusFromTF_Status(status.get()));
129 TFE_DeleteContextOptions(opts);
130 return OkStatus();
131 }
132
GetValue(AbstractTensorHandle * t,TF_Tensor ** result_tensor)133 Status GetValue(AbstractTensorHandle* t, TF_Tensor** result_tensor) {
134 std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status(
135 TF_NewStatus(), TF_DeleteStatus);
136 TFE_TensorHandle* result_t =
137 TF_AbstractTensorGetEagerTensor(wrap(t), status.get());
138 TF_RETURN_IF_ERROR(StatusFromTF_Status(status.get()));
139 *result_tensor = TFE_TensorHandleResolve(result_t, status.get());
140 return StatusFromTF_Status(status.get());
141 }
142
143 } // namespace tensorflow
144