experiments/STT-tensorflow
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rename ctx_ to immediate_execution_ctx_

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This commit is contained in:
Võ Văn Nghĩa 2021-01-20 06:47:35 +07:00
parent 1697abe35d
commit 0b41c93753
1 changed files with 54 additions and 39 deletions
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93
tensorflow/c/experimental/gradients/math_grad_test.cc
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@ -93,7 +93,7 @@ class CppGradients
Status s =
BuildImmediateExecutionContext(std::get<1>(GetParam()), &ctx_raw);
ASSERT_EQ(errors::OK, s.code()) << s.error_message();
ctx_.reset(ctx_raw);
immediate_execution_ctx_.reset(ctx_raw);
}
// Computing numerical gradients with TensorFloat-32 is numerically
@ -102,7 +102,7 @@ class CppGradients
enable_tensor_float_32_execution(false);
}
AbstractContextPtr ctx_;
AbstractContextPtr immediate_execution_ctx_;
GradientRegistry registry_;
Status status_;
@ -115,7 +115,8 @@ TEST_P(CppGradients, TestAddGrad) {
AbstractTensorHandlePtr x;
{
AbstractTensorHandle* x_raw = nullptr;
status_ = TestScalarTensorHandle(ctx_.get(), 2.0f, &x_raw);
status_ =
TestScalarTensorHandle(immediate_execution_ctx_.get(), 2.0f, &x_raw);
ASSERT_EQ(errors::OK, status_.code()) << status_.error_message();
x.reset(x_raw);
}
@ -123,7 +124,8 @@ TEST_P(CppGradients, TestAddGrad) {
AbstractTensorHandlePtr y;
{
AbstractTensorHandle* y_raw = nullptr;
status_ = TestScalarTensorHandle(ctx_.get(), 2.0f, &y_raw);
status_ =
TestScalarTensorHandle(immediate_execution_ctx_.get(), 2.0f, &y_raw);
ASSERT_EQ(errors::OK, status_.code()) << status_.error_message();
y.reset(y_raw);
}
@ -132,15 +134,16 @@ TEST_P(CppGradients, TestAddGrad) {
ASSERT_EQ(errors::OK, status_.code()) << status_.error_message();
ASSERT_NO_FATAL_FAILURE(CompareNumericalAndAutodiffGradients(
AddModel, BuildGradModel(AddModel, registry_), ctx_.get(),
{x.get(), y.get()}, UseFunction()));
AddModel, BuildGradModel(AddModel, registry_),
immediate_execution_ctx_.get(), {x.get(), y.get()}, UseFunction()));
}
TEST_P(CppGradients, TestExpGrad) {
AbstractTensorHandlePtr x;
{
AbstractTensorHandle* x_raw = nullptr;
status_ = TestScalarTensorHandle(ctx_.get(), 2.0f, &x_raw);
status_ =
TestScalarTensorHandle(immediate_execution_ctx_.get(), 2.0f, &x_raw);
ASSERT_EQ(errors::OK, status_.code()) << status_.error_message();
x.reset(x_raw);
}
@ -149,8 +152,8 @@ TEST_P(CppGradients, TestExpGrad) {
ASSERT_EQ(errors::OK, status_.code()) << status_.error_message();
ASSERT_NO_FATAL_FAILURE(CompareNumericalAndAutodiffGradients(
ExpModel, BuildGradModel(ExpModel, registry_), ctx_.get(), {x.get()},
UseFunction()));
ExpModel, BuildGradModel(ExpModel, registry_),
immediate_execution_ctx_.get(), {x.get()}, UseFunction()));
}
TEST_P(CppGradients, TestMatMulGrad) {
@ -159,8 +162,8 @@ TEST_P(CppGradients, TestMatMulGrad) {
AbstractTensorHandlePtr A;
{
AbstractTensorHandle* A_raw;
status_ =
TestTensorHandleWithDimsFloat(ctx_.get(), A_vals, A_dims, 2, &A_raw);
status_ = TestTensorHandleWithDimsFloat(immediate_execution_ctx_.get(),
A_vals, A_dims, 2, &A_raw);
ASSERT_EQ(errors::OK, status_.code()) << status_.error_message();
A.reset(A_raw);
}
@ -170,8 +173,8 @@ TEST_P(CppGradients, TestMatMulGrad) {
AbstractTensorHandlePtr B;
{
AbstractTensorHandle* B_raw;
status_ =
TestTensorHandleWithDimsFloat(ctx_.get(), B_vals, B_dims, 2, &B_raw);
status_ = TestTensorHandleWithDimsFloat(immediate_execution_ctx_.get(),
B_vals, B_dims, 2, &B_raw);
ASSERT_EQ(errors::OK, status_.code()) << status_.error_message();
B.reset(B_raw);
}
@ -193,8 +196,9 @@ TEST_P(CppGradients, TestMatMulGrad) {
// well with `MatMul` and remove `TestMatMul*` in
// `mnist_gradients_test` when done.
ASSERT_NO_FATAL_FAILURE(CompareNumericalAndAutodiffGradients(
MatMulModel, BuildGradModel(MatMulModel, registry_), ctx_.get(),
{A.get(), B.get()}, UseFunction(), /*abs_error*/ 0.4));
MatMulModel, BuildGradModel(MatMulModel, registry_),
immediate_execution_ctx_.get(), {A.get(), B.get()}, UseFunction(),
/*abs_error*/ 0.4f));
}
}
}
@ -203,7 +207,8 @@ TEST_P(CppGradients, TestSqrtGrad) {
AbstractTensorHandlePtr x;
{
AbstractTensorHandle* x_raw = nullptr;
status_ = TestScalarTensorHandle(ctx_.get(), 2.0f, &x_raw);
status_ =
TestScalarTensorHandle(immediate_execution_ctx_.get(), 2.0f, &x_raw);
ASSERT_EQ(errors::OK, status_.code()) << status_.error_message();
x.reset(x_raw);
}
@ -212,15 +217,16 @@ TEST_P(CppGradients, TestSqrtGrad) {
ASSERT_EQ(errors::OK, status_.code()) << status_.error_message();
ASSERT_NO_FATAL_FAILURE(CompareNumericalAndAutodiffGradients(
SqrtModel, BuildGradModel(SqrtModel, registry_), ctx_.get(), {x.get()},
UseFunction()));
SqrtModel, BuildGradModel(SqrtModel, registry_),
immediate_execution_ctx_.get(), {x.get()}, UseFunction()));
}
TEST_P(CppGradients, TestNegGrad) {
AbstractTensorHandlePtr x;
{
AbstractTensorHandle* x_raw = nullptr;
status_ = TestScalarTensorHandle(ctx_.get(), 2.0f, &x_raw);
status_ =
TestScalarTensorHandle(immediate_execution_ctx_.get(), 2.0f, &x_raw);
ASSERT_EQ(errors::OK, status_.code()) << status_.error_message();
x.reset(x_raw);
}
@ -229,15 +235,16 @@ TEST_P(CppGradients, TestNegGrad) {
ASSERT_EQ(errors::OK, status_.code()) << status_.error_message();
ASSERT_NO_FATAL_FAILURE(CompareNumericalAndAutodiffGradients(
NegModel, BuildGradModel(NegModel, registry_), ctx_.get(), {x.get()},
UseFunction()));
NegModel, BuildGradModel(NegModel, registry_),
immediate_execution_ctx_.get(), {x.get()}, UseFunction()));
}
TEST_P(CppGradients, TestSubGrad) {
AbstractTensorHandlePtr x;
{
AbstractTensorHandle* x_raw = nullptr;
status_ = TestScalarTensorHandle(ctx_.get(), 2.0f, &x_raw);
status_ =
TestScalarTensorHandle(immediate_execution_ctx_.get(), 2.0f, &x_raw);
ASSERT_EQ(errors::OK, status_.code()) << status_.error_message();
x.reset(x_raw);
}
@ -245,7 +252,8 @@ TEST_P(CppGradients, TestSubGrad) {
AbstractTensorHandlePtr y;
{
AbstractTensorHandle* y_raw = nullptr;
status_ = TestScalarTensorHandle(ctx_.get(), 2.0f, &y_raw);
status_ =
TestScalarTensorHandle(immediate_execution_ctx_.get(), 2.0f, &y_raw);
ASSERT_EQ(errors::OK, status_.code()) << status_.error_message();
y.reset(y_raw);
}
@ -254,15 +262,16 @@ TEST_P(CppGradients, TestSubGrad) {
ASSERT_EQ(errors::OK, status_.code()) << status_.error_message();
ASSERT_NO_FATAL_FAILURE(CompareNumericalAndAutodiffGradients(
SubModel, BuildGradModel(SubModel, registry_), ctx_.get(),
{x.get(), y.get()}, UseFunction()));
SubModel, BuildGradModel(SubModel, registry_),
immediate_execution_ctx_.get(), {x.get(), y.get()}, UseFunction()));
}
TEST_P(CppGradients, TestMulGrad) {
AbstractTensorHandlePtr x;
{
AbstractTensorHandle* x_raw = nullptr;
status_ = TestScalarTensorHandle(ctx_.get(), 2.0f, &x_raw);
status_ =
TestScalarTensorHandle(immediate_execution_ctx_.get(), 2.0f, &x_raw);
ASSERT_EQ(errors::OK, status_.code()) << status_.error_message();
x.reset(x_raw);
}
@ -270,7 +279,8 @@ TEST_P(CppGradients, TestMulGrad) {
AbstractTensorHandlePtr y;
{
AbstractTensorHandle* y_raw = nullptr;
status_ = TestScalarTensorHandle(ctx_.get(), 2.0f, &y_raw);
status_ =
TestScalarTensorHandle(immediate_execution_ctx_.get(), 2.0f, &y_raw);
ASSERT_EQ(errors::OK, status_.code()) << status_.error_message();
y.reset(y_raw);
}
@ -279,15 +289,16 @@ TEST_P(CppGradients, TestMulGrad) {
ASSERT_EQ(errors::OK, status_.code()) << status_.error_message();
ASSERT_NO_FATAL_FAILURE(CompareNumericalAndAutodiffGradients(
MulModel, BuildGradModel(MulModel, registry_), ctx_.get(),
{x.get(), y.get()}, UseFunction()));
MulModel, BuildGradModel(MulModel, registry_),
immediate_execution_ctx_.get(), {x.get(), y.get()}, UseFunction()));
}
TEST_P(CppGradients, TestLog1pGrad) {
AbstractTensorHandlePtr x;
{
AbstractTensorHandle* x_raw = nullptr;
status_ = TestScalarTensorHandle(ctx_.get(), 2.0f, &x_raw);
status_ =
TestScalarTensorHandle(immediate_execution_ctx_.get(), 2.0f, &x_raw);
ASSERT_EQ(errors::OK, status_.code()) << status_.error_message();
x.reset(x_raw);
}
@ -296,8 +307,8 @@ TEST_P(CppGradients, TestLog1pGrad) {
ASSERT_EQ(errors::OK, status_.code()) << status_.error_message();
ASSERT_NO_FATAL_FAILURE(CompareNumericalAndAutodiffGradients(
Log1pModel, BuildGradModel(Log1pModel, registry_), ctx_.get(), {x.get()},
UseFunction()));
Log1pModel, BuildGradModel(Log1pModel, registry_),
immediate_execution_ctx_.get(), {x.get()}, UseFunction()));
}
TEST_P(CppGradients, TestDivNoNanGrad) {
@ -309,7 +320,8 @@ TEST_P(CppGradients, TestDivNoNanGrad) {
AbstractTensorHandlePtr x;
{
AbstractTensorHandle* x_raw = nullptr;
status_ = TestScalarTensorHandle(ctx_.get(), 2.0f, &x_raw);
status_ =
TestScalarTensorHandle(immediate_execution_ctx_.get(), 2.0f, &x_raw);
ASSERT_EQ(errors::OK, status_.code()) << status_.error_message();
x.reset(x_raw);
}
@ -317,26 +329,29 @@ TEST_P(CppGradients, TestDivNoNanGrad) {
AbstractTensorHandlePtr y;
{
AbstractTensorHandle* y_raw = nullptr;
status_ = TestScalarTensorHandle(ctx_.get(), 2.0f, &y_raw);
status_ =
TestScalarTensorHandle(immediate_execution_ctx_.get(), 2.0f, &y_raw);
ASSERT_EQ(errors::OK, status_.code()) << status_.error_message();
y.reset(y_raw);
}
ASSERT_NO_FATAL_FAILURE(CompareNumericalAndAutodiffGradients(
DivNoNanModel, DivNoNanGradModel, ctx_.get(), {x.get(), y.get()},
UseFunction()));
DivNoNanModel, DivNoNanGradModel, immediate_execution_ctx_.get(),
{x.get(), y.get()}, UseFunction()));
// `DivNoNanGradModel` should return {`0`, `0`} when the denominator is `0`.
AbstractTensorHandlePtr z;
{
AbstractTensorHandle* z_raw = nullptr;
status_ = TestScalarTensorHandle(ctx_.get(), 0.0f, &z_raw);
status_ =
TestScalarTensorHandle(immediate_execution_ctx_.get(), 0.0f, &z_raw);
ASSERT_EQ(errors::OK, status_.code()) << status_.error_message();
z.reset(z_raw);
}
std::vector<AbstractTensorHandle*> outputs(2);
status_ = RunModel(DivNoNanGradModel, ctx_.get(), {x.get(), z.get()},
absl::MakeSpan(outputs), UseFunction());
status_ =
RunModel(DivNoNanGradModel, immediate_execution_ctx_.get(),
{x.get(), z.get()}, absl::MakeSpan(outputs), UseFunction());
ASSERT_EQ(errors::OK, status_.code()) << status_.error_message();
ASSERT_NO_FATAL_FAILURE(CheckTensorValue(outputs[0], {0.0f}, /*dims*/ {},
/*abs_error*/ 0));