experiments/STT-tensorflow
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updating rebase

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This commit is contained in:
amturati 2020-07-17 21:07:46 +00:00
parent 083e5f48fd
commit 0926d6f238
3 changed files with 30 additions and 23 deletions
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27
tensorflow/c/eager/BUILD
View File

@ -428,6 +428,32 @@ tf_cuda_cc_test(
],
)
cc_library(
name = "mnist_gradients_util",
srcs = [
"mnist_gradients_util.cc",
"mnist_gradients_util.h",
],
hdrs = [
"gradients.h",
],
visibility = [
"//tensorflow:internal",
],
deps = [
":abstract_context",
":abstract_operation",
":abstract_tensor_handle",
":c_api_unified_internal",
":gradients_internal",
":tape",
"//tensorflow/core/common_runtime/eager:attr_builder",
"//tensorflow/core/lib/llvm_rtti",
"@com_google_absl//absl/container:flat_hash_map",
"@com_google_absl//absl/strings",
],
)
tf_cuda_cc_test(
name = "mnist_gradients_test",
size = "small",
@ -444,6 +470,7 @@ tf_cuda_cc_test(
":c_api_test_util",
":c_api_unified_internal",
":gradients_internal",
":mnist_gradients_util",
"//tensorflow/c:c_api",
"//tensorflow/c:c_test_util",
"//tensorflow/c:tf_status_helper",

1
tensorflow/c/eager/mnist_gradients.cc
View File

@ -29,7 +29,6 @@ limitations under the License.
#include "tensorflow/core/lib/llvm_rtti/llvm_rtti.h"
namespace tensorflow {
namespace gradients {
namespace internal {

25
tensorflow/c/eager/mnist_gradients_test.cc
View File

@ -460,6 +460,9 @@ TEST_P(CppGradients, TestMatMulGrad) {
s = MatMulGradModel(ctx.get(), {A.get(), B.get()}, absl::MakeSpan(outputs), registry);
ASSERT_EQ(errors::OK, s.code()) << s.error_message();
// s = MatMulGradModel(ctx.get(), {A.get(), B.get()}, absl::MakeSpan(outputs), registry);
// ASSERT_EQ(errors::OK, s.code()) << s.error_message();
TF_Tensor* dA_tensor;
s = getValue(outputs[0], &dA_tensor);
ASSERT_EQ(errors::OK, s.code()) << s.error_message();
@ -584,13 +587,9 @@ TEST_P(CppGradients, TestMNISTForward2) {
// Run the Forward Pass
std::vector<AbstractTensorHandle*> outputs(2);
<<<<<<< HEAD
Status s = RunModel(MNISTForwardModel, ctx.get(), {X.get(), W1.get(), W2.get(), y.get()},
absl::MakeSpan(outputs),
/*use_function=*/!std::get<2>(GetParam()), registry);
=======
Status s = MNISTForwardModel(ctx.get(), {X.get(), W1.get(), W2.get(), y.get()}, absl::MakeSpan(outputs), registry);
>>>>>>> 37eefa1df8... Adding tests for matmul grad, memory error
ASSERT_EQ(errors::OK, s.code()) << s.error_message();
// Verify the Results
@ -601,10 +600,6 @@ TEST_P(CppGradients, TestMNISTForward2) {
float result_data[6] = {0};
memcpy(&result_data[0], TF_TensorData(scores_tensor), TF_TensorByteSize(scores_tensor));
<<<<<<< HEAD
=======
//float expected_scores [6] = {0f, 12.0f, -1.0f, -17.0f, 16.8f, -28.0f};
>>>>>>> 37eefa1df8... Adding tests for matmul grad, memory error
float expected_scores [6] = {3.6f, -6.0f, 10.2f, -17.0f, 16.8f, -28.0f};
float tolerance = 1e-3;
for(int j = 0; j < 6; j++){
@ -638,10 +633,7 @@ Status MatMulTransposeModel(AbstractContext* ctx,
TapeVSpace vspace(ctx);
auto tape = new Tape(/*persistent=*/false);
<<<<<<< HEAD
tape->Watch(ToId(X));
=======
>>>>>>> 37eefa1df8... Adding tests for matmul grad, memory error
tape->Watch(ToId(W1)); // Watch W1.
std::vector<AbstractTensorHandle*> temp_outputs(1);
@ -682,15 +674,11 @@ TEST_P(CppGradients, TestMatMulTranspose) {
// Run the MatMul Op
std::vector<AbstractTensorHandle*> outputs(1);
<<<<<<< HEAD
Status s = RunModel(MatMulTransposeModel, ctx.get(), {X.get(), W1.get()},
absl::MakeSpan(outputs),
/*use_function=*/!std::get<2>(GetParam()), registry);
=======
Status s = MatMulTransposeModel(ctx.get(), {X.get(), W1.get()}, absl::MakeSpan(outputs), registry);
>>>>>>> 37eefa1df8... Adding tests for matmul grad, memory error
ASSERT_EQ(errors::OK, s.code()) << s.error_message();
// Verify the Results
@ -701,10 +689,6 @@ TEST_P(CppGradients, TestMatMulTranspose) {
float result_data[6] = {0};
memcpy(&result_data[0], TF_TensorData(scores_tensor), TF_TensorByteSize(scores_tensor));
<<<<<<< HEAD
=======
>>>>>>> 37eefa1df8... Adding tests for matmul grad, memory error
float expected_scores [6] = {13.0f, 18.0f, 17.0f, 24.0f, 21.0f, 30.0f};
float tolerance = 1e-3;
@ -714,7 +698,6 @@ TEST_P(CppGradients, TestMatMulTranspose) {
}
<<<<<<< HEAD
// Test Model to verify ReluGrad functionality
Status ReluGradModel(AbstractContext* ctx,
absl::Span<AbstractTensorHandle* const> inputs,
@ -927,8 +910,6 @@ TEST_P(CppGradients, TestSoftmaxLossGrad) {
TF_DeleteTensor(dX_tensor);
}
=======
>>>>>>> 37eefa1df8... Adding tests for matmul grad, memory error
// TODO(b/160888630): Enable this test with mlir after AddInputList is
// supported. It is needed for AddN op which is used for gradient aggregation.