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serizbaserizba
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Merge pull request #77 from ljn917/cppflow2-refactor-tensor
Add tensor::get_tensor() and tensor::get_eager_handle()
2 parents d1aad32 + f9bd7a1 commit ce847d5

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-81
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7 files changed

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‎examples/tensor/CMakeLists.txt

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Original file line numberDiff line numberDiff line change
@@ -0,0 +1,10 @@
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cmake_minimum_required(VERSION 3.10)
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project(example)
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find_library(TENSORFLOW_LIB tensorflow HINT $ENV{HOME}/libtensorflow2/lib)
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set(CMAKE_CXX_STANDARD 17)
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add_executable(example main.cpp)
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target_include_directories(example PRIVATE ../../include $ENV{HOME}/libtensorflow2/include)
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target_link_libraries(example "${TENSORFLOW_LIB}")

‎examples/tensor/main.cpp

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#include <cmath>
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#include <vector>
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#include <iostream>
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#include <stdexcept>
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#include "cppflow/cppflow.h"
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bool float_equal(const float f1, const float f2) {
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return std::abs(f1/f2-1.0f) < 1e-6;
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}
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void test1(const bool is_cpu) {
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std::cout << "test1 starts: is_cpu=" << is_cpu << std::endl;
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float target = 1.0;
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int64_t ndim = 2;
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cppflow::tensor t1;
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if(is_cpu) {
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std::vector<float> _data(ndim, target);
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t1 = cppflow::tensor(_data, {ndim});
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} else {
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t1 = cppflow::fill({ndim}, target);
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}
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std::cout << "tensor::device(true) : " << t1.device(true) << std::endl;
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std::cout << "tensor::device(false) : " << t1.device(false) << std::endl;
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auto t1_tensor = t1.get_tensor();
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auto raw_data = static_cast<float*>(TF_TensorData(t1_tensor.get()));
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float result_value = raw_data[0];
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if(float_equal(result_value, target)) {
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std::cout << "tensor::get_tensor() test1-1: pass" << std::endl;
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} else {
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std::cout << "tensor::get_tensor() test1-1: result_value=" << result_value << ", target=" << target << std::endl;
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throw std::runtime_error("tensor::get_tensor() test1-1: failed");
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}
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// IMPORTANT NOTE: CANNOT modify the returned cache
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float target2 = target + 10.0;
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raw_data[1] = target2;
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result_value = t1.get_data<float>()[0];
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float result_value2 = t1.get_data<float>()[1];
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if(float_equal(result_value, target)) {
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std::cout << "tensor::get_tensor() test1-2: pass" << std::endl;
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} else {
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std::cout << "tensor::get_tensor() test1-2: failed, result_value=" << result_value << ", target=" << target << std::endl;
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throw std::runtime_error("tensor::get_tensor() test1-2: failed");
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}
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if(float_equal(result_value2, target2)) {
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std::cout << "tensor::get_tensor() test1-3: pass" << std::endl;
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} else {
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std::cout << "The failure of test1-3 is not considered as a bug." << std::endl;
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std::cout << "tensor::get_tensor() test1-3: failed, result_value=" << result_value2 << ", target2=" << target2 << std::endl;
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}
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auto t2 = t1 + cppflow::tensor(0.f);
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std::cout << "Can NOT modify the cache!" << std::endl;
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std::cout << "t2: " << t2 << std::endl;
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auto dt = cppflow::to_string(t1.dtype());
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std::string expected_dtype{"TF_FLOAT"};
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if(dt == expected_dtype) {
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std::cout << "tensor::get_tensor() test1-4: pass" << std::endl;
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} else {
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std::cout << "tensor::get_tensor() test1-4: dtype=" << dt << ", expected_dtype=" << expected_dtype << std::endl;
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throw std::runtime_error("tensor::get_tensor() test1-4: failed");
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}
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auto shape_tensor = t1.shape();
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auto shape = shape_tensor.get_data<int32_t>()[0];
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if(shape == ndim) {
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std::cout << "tensor::get_tensor() test1-5: pass" << std::endl;
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} else {
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std::cout << "tensor::get_tensor() test1-5: shape_tensor.dtype()=" << cppflow::to_string(shape_tensor.dtype()) << std::endl;
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std::cout << "tensor::get_tensor() test1-5: shape_tensor=" << shape_tensor << std::endl;
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std::cout << "tensor::get_tensor() test1-5: shape()=" << shape << ", ndim=" << ndim << std::endl;
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throw std::runtime_error("tensor::get_tensor() test1-5: failed");
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}
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std::cout << std::endl;
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}
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int main() {
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test1(true);
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test1(false);
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return 0;
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}

‎include/cppflow/model.h

+1-8
Original file line numberDiff line numberDiff line change
@@ -86,11 +86,6 @@ namespace cppflow {
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std::vector<TF_Output> inp_ops(inputs.size());
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std::vector<TF_Tensor*> inp_val(inputs.size(), nullptr);
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defer d([&inp_val]{
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for (auto* tf_tensor : inp_val) {
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TF_DeleteTensor(tf_tensor);
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}
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});
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for (int i=0; i<inputs.size(); i++) {
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// Operations
@@ -102,9 +97,7 @@ namespace cppflow {
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throw std::runtime_error("No operation named \"" + op_name + "\" exists");
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// Values
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auto inp_tensor = TFE_TensorHandleResolve(std::get<1>(inputs[i]).tfe_handle.get(), context::get_status());
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status_check(context::get_status());
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inp_val[i] = inp_tensor;
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inp_val[i] = std::get<1>(inputs[i]).get_tensor().get();
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}
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std::vector<TF_Output> out_ops(outputs.size());

‎include/cppflow/ops.h

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Original file line numberDiff line numberDiff line change
@@ -80,24 +80,21 @@ namespace cppflow {
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std::string to_string(const tensor &t) {
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auto res_tensor = string_format({t.shape(), t}, "(tensor: shape=%s, data=\n%s)");
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auto res_tensor_h = TFE_TensorHandleResolve(res_tensor.tfe_handle.get(), context::get_status());
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status_check(context::get_status());
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auto res_tensor_h = res_tensor.get_tensor();
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#ifdef TENSORFLOW_C_TF_TSTRING_H_
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// For future version TensorFlow 2.4
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//auto *t_str = reinterpret_cast<TF_TString *>(TF_TensorData(res_tensor_h));
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auto *t_str = (TF_TString *)(TF_TensorData(res_tensor_h));
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//auto *t_str = reinterpret_cast<TF_TString *>(TF_TensorData(res_tensor_h.get()));
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auto *t_str = (TF_TString *)(TF_TensorData(res_tensor_h.get()));
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auto result = std::string(TF_TString_GetDataPointer(t_str), TF_TString_GetSize(t_str));
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#else
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const char* dst[1] = {nullptr};
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size_t dst_len[1] = {3};
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TF_StringDecode(static_cast<char*>(TF_TensorData(res_tensor_h)) + 8, TF_TensorByteSize(res_tensor_h), dst, dst_len, context::get_status());
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TF_StringDecode(static_cast<char*>(TF_TensorData(res_tensor_h.get())) + 8, TF_TensorByteSize(res_tensor_h.get()), dst, dst_len, context::get_status());
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status_check(context::get_status());
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auto result = std::string(dst[0], *dst_len);
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#endif // TENSORFLOW_C_TF_TSTRING_H_
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99-
TF_DeleteTensor(res_tensor_h);
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return result;
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}
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‎include/cppflow/ops_generator/generator.py

+2-2
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@@ -106,7 +106,7 @@ def code(self):
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'type' : 'TFE_OpSetAttrType(op.get(), "{orig:}", {0});',
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'bool' : 'TFE_OpSetAttrBool(op.get(), "{orig:}", (unsigned char){0});',
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'tensor': '''
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TFE_OpSetAttrTensor(op.get(), "{orig:}", {0}.tf_tensor.get(), context::get_status());
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TFE_OpSetAttrTensor(op.get(), "{orig:}", {0}.get_tensor().get(), context::get_status());
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status_check(context::get_status());
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''',
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'n_attr': 'TFE_OpSetAttrInt(op.get(), "{orig:}", {n_attr:}.size());'
@@ -268,4 +268,4 @@ def code(self):
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with open('../raw_ops.h', 'w') as f:
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f.write(ops_file.format(ops_code))
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f.write(ops_file.format(ops_code))

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