diff --git a/tensorflow/c/eager/c_api.cc b/tensorflow/c/eager/c_api.cc
index 2920c94b4c2..6528d21dc36 100644
--- a/tensorflow/c/eager/c_api.cc
+++ b/tensorflow/c/eager/c_api.cc
@@ -1553,8 +1553,67 @@ void SetOpAttrValueScalar(TFE_Context* ctx, TFE_Op* op,
TFE_OpSetAttrFunction(op, attr_name, func_op);
TFE_DeleteOp(func_op);
} break;
- case tensorflow::AttrValue::kList:
- TF_FALLTHROUGH_INTENDED;
+ case tensorflow::AttrValue::kList: {
+ // String
+ if (const int s_size = default_value.list().s_size()) {
+ absl::InlinedVector<const void*, 4> values_vector;
+ absl::InlinedVector<size_t, 4> lengths_vector;
+ for (int i = 0; i < s_size; ++i) {
+ const string& v = default_value.list().s(i);
+ values_vector.push_back(v.data());
+ lengths_vector.push_back(v.size());
+ }
+ TFE_OpSetAttrStringList(op, attr_name, values_vector.data(),
+ lengths_vector.data(), s_size);
+ }
+
+ // Int
+ if (const int i_size = default_value.list().i_size()) {
+ absl::InlinedVector<int64_t, 4> i_vector;
+ for (int i = 0; i < i_size; ++i) {
+ i_vector.push_back(default_value.list().i(i));
+ }
+ TFE_OpSetAttrIntList(op, attr_name, i_vector.data(), i_size);
+ }
+ // Float
+ if (const int f_size = default_value.list().f_size()) {
+ absl::InlinedVector<float, 4> f_vector;
+ for (int i = 0; i < f_size; ++i) {
+ f_vector.push_back(default_value.list().f(i));
+ }
+ TFE_OpSetAttrFloatList(op, attr_name, f_vector.data(), f_size);
+ }
+ // Bool
+ if (const int b_size = default_value.list().b_size()) {
+ absl::InlinedVector<unsigned char, 4> b_vector;
+ for (int i = 0; i < b_size; i++) {
+ b_vector.push_back(default_value.list().b(i));
+ }
+ TFE_OpSetAttrBoolList(op, attr_name, b_vector.data(), b_size);
+ }
+ // Type
+ if (const int type_size = default_value.list().type_size()) {
+ absl::InlinedVector<unsigned int, 4> type_vector;
+ for (int i = 0; i < type_size; ++i) {
+ type_vector.push_back(default_value.list().type(i));
+ }
+ TFE_OpSetAttrTypeList(
+ op, attr_name,
+ reinterpret_cast<const TF_DataType*>(type_vector.data()),
+ type_size);
+ }
+
+ // Rest are not supported.
+ if (default_value.list().shape_size() > 0 ||
+ default_value.list().func_size() > 0 ||
+ default_value.list().tensor_size() > 0) {
+ TF_SetStatus(
+ status, TF_UNIMPLEMENTED,
+ tensorflow::strings::StrCat("Unable to get setfor default value: ",
+ default_value.DebugString())
+ .data());
+ }
+ } break;
case tensorflow::AttrValue::kTensor:
TF_FALLTHROUGH_INTENDED;
case tensorflow::AttrValue::kPlaceholder:
diff --git a/tensorflow/c/eager/c_api_test.cc b/tensorflow/c/eager/c_api_test.cc
index 37bb9c5f16b..fd208c6770d 100644
--- a/tensorflow/c/eager/c_api_test.cc
+++ b/tensorflow/c/eager/c_api_test.cc
@@ -20,6 +20,7 @@ limitations under the License.
#include <string>
// clang-format off
+#include "tensorflow/core/framework/attr_value.pb.h"
#include "tensorflow/core/platform/platform.h"
// clang-format on
@@ -1191,6 +1192,68 @@ TEST(CAPI, StringAttributes) {
TF_DeleteStatus(status);
}
+// Same test as above, expect use SetOpAttrValueScalar to set attrs.
+TEST(CAPI, TestTFE_SetOpAttrs) {
+ // Test that TFE_OpSetAttrString doesn't hold on to the value after it
+ // returns.
+ TF_Status* status = TF_NewStatus();
+ TFE_ContextOptions* opts = TFE_NewContextOptions();
+ TFE_Context* ctx = TFE_NewContext(opts, status);
+ ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
+ TFE_DeleteContextOptions(opts);
+
+ std::vector<int64_t> dims(4, 1);
+ TFE_Op* op = TFE_NewOp(ctx, "AvgPool", status);
+ ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
+
+ TF_Tensor* tensor =
+ TF_AllocateTensor(TF_FLOAT, dims.data(), dims.size(), sizeof(float));
+ float tensor_data[] = {1};
+ memcpy(TF_TensorData(tensor), tensor_data, TF_TensorByteSize(tensor));
+ TFE_TensorHandle* tensor_handle = TFE_NewTensorHandle(tensor, status);
+ ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
+ TFE_OpAddInput(op, tensor_handle, status);
+ TF_DeleteTensor(tensor);
+ TFE_DeleteTensorHandle(tensor_handle);
+
+ tensorflow::AttrValue i_list_values;
+ for (int i = 0; i < 4; ++i) {
+ i_list_values.mutable_list()->add_i(1);
+ }
+ SetOpAttrValueScalar(ctx, op, i_list_values, "ksize", status);
+ SetOpAttrValueScalar(ctx, op, i_list_values, "strides", status);
+
+ tensorflow::AttrValue padding_value;
+ *padding_value.mutable_s() = "VALID";
+ tensorflow::SetOpAttrValueScalar(ctx, op, padding_value, "padding", status);
+
+ tensorflow::AttrValue data_format_value;
+ *data_format_value.mutable_s() = "NHWC";
+ tensorflow::SetOpAttrValueScalar(ctx, op, data_format_value, "data_format",
+ status);
+
+ TFE_OpSetAttrType(op, "T", TF_FLOAT);
+
+ ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
+
+ TFE_TensorHandle* retvals[1];
+ int num_retvals = 1;
+ TFE_Execute(op, &retvals[0], &num_retvals, status);
+ ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
+ ASSERT_EQ(1, num_retvals);
+
+ tensor = TFE_TensorHandleResolve(retvals[0], status);
+ ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
+ EXPECT_EQ(4, TF_TensorByteSize(tensor));
+ TF_DeleteTensor(tensor);
+ TFE_DeleteTensorHandle(retvals[0]);
+
+ TFE_DeleteOp(op);
+
+ TFE_DeleteContext(ctx);
+ TF_DeleteStatus(status);
+}
+
TEST(CAPI, TestTFE_TensorHandleCopySharingUnderlyingTensorHandle) {
std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status(
TF_NewStatus(), TF_DeleteStatus);
diff --git a/tensorflow/compiler/mlir/tensorflow/tests/constant-fold.mlir b/tensorflow/compiler/mlir/tensorflow/tests/constant-fold.mlir
index f114d1724f2..fff985efa6f 100644
--- a/tensorflow/compiler/mlir/tensorflow/tests/constant-fold.mlir
+++ b/tensorflow/compiler/mlir/tensorflow/tests/constant-fold.mlir
@@ -492,3 +492,13 @@ func @DontFoldTile() -> (tensor<8x10000xi32>) {
return %3 : tensor<8x10000xi32>
}
// LINT.ThenChange(../transforms/constant_fold.cc:folding-policy)
+
+func @fold_conv() -> tensor<1x520x520x1xf32> {
+ %0 = "tf.Const"() {value = dense<0.111111112> : tensor<3x3x1x1xf32>} : () -> tensor<3x3x1x1xf32>
+ %1 = "tf.Const"() {value = dense<1.000000e+00> : tensor<1x520x520x1xf32>} : () -> tensor<1x520x520x1xf32>
+ %2 = "tf.DepthwiseConv2dNative"(%1, %0) {data_format = "NHWC", device = "", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 1, 1]} : (tensor<1x520x520x1xf32>, tensor<3x3x1x1xf32>) -> tensor<1x520x520x1xf32>
+ return %2 : tensor<1x520x520x1xf32>
+
+ // CHECK: tf.Const
+ // CHECK-NOT: tf.DepthwiseConv2dNative
+}