experiments/STT-tensorflow
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

Fix compile warnings and pass the correct parameter to TestConvQuantized.

Browse Source
This commit is contained in:
Jens Elofsson 2019-04-23 13:37:01 +02:00
parent 812731d38d
commit f201da5ecd
1 changed files with 1 additions and 11 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

12
tensorflow/lite/experimental/micro/kernels/conv_test.cc
View File

@ -59,10 +59,6 @@ void TestConvFloat(std::initializer_list<int> input_dims_data,
TF_LITE_MICRO_EXPECT_NE(nullptr, registration); TF_LITE_MICRO_EXPECT_NE(nullptr, registration);
int input_depth = input_dims->data[3];
int output_depth = output_dims->data[3];
int depth_mul = output_depth / input_depth;
TfLiteConvParams builtin_data = { TfLiteConvParams builtin_data = {
.padding = kTfLitePaddingValid, .padding = kTfLitePaddingValid,
.stride_width = 2, .stride_width = 2,
@ -131,8 +127,6 @@ void TestConvQuantized(
::tflite::ops::micro::AllOpsResolver resolver; ::tflite::ops::micro::AllOpsResolver resolver;
const int intput_dims_count = ElementCount(*input_dims);
constexpr int inputs_size = 3; constexpr int inputs_size = 3;
constexpr int outputs_size = 1; constexpr int outputs_size = 1;
constexpr int tensors_size = inputs_size + outputs_size; constexpr int tensors_size = inputs_size + outputs_size;
@ -155,10 +149,6 @@ void TestConvQuantized(
TF_LITE_MICRO_EXPECT_NE(nullptr, registration); TF_LITE_MICRO_EXPECT_NE(nullptr, registration);
int input_depth = input_dims->data[3];
int output_depth = output_dims->data[3];
int depth_mul = output_depth / input_depth;
TfLiteConvParams builtin_data = { TfLiteConvParams builtin_data = {
.padding = kTfLitePaddingSame, .padding = kTfLitePaddingSame,
.stride_width = 2, .stride_width = 2,
@ -309,7 +299,7 @@ TF_LITE_MICRO_TEST(SimpleTestQuantized) {
F2Q(-1, filter_min, filter_max), F2Q(-1, filter_min, filter_max), F2Q(-1, filter_min, filter_max), F2Q(-1, filter_min, filter_max),
F2Q(1, filter_min, filter_max), F2Q(1, filter_min, filter_max), F2Q(1, filter_min, filter_max), F2Q(1, filter_min, filter_max),
}, },
input_min, input_max, {1, 3}, filter_min, filter_max, {1, 3},
{ {
F2Q32(1, bias_min, bias_max), F2Q32(2, bias_min, bias_max), F2Q32(1, bias_min, bias_max), F2Q32(2, bias_min, bias_max),
F2Q32(3, bias_min, bias_max), F2Q32(3, bias_min, bias_max),