TEST_P(Test_TensorFlow_layers, resize_nearest_neighbor)
{
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target != DNN_TARGET_MYRIAD)
throw SkipTestException("");
runTensorFlowNet("resize_nearest_neighbor");
runTensorFlowNet("keras_upsampling2d");
}
TEST_P(Test_TensorFlow_layers, reshape)
{
int targetId = GetParam();
runTensorFlowNet("shift_reshape_no_reorder", targetId);
runTensorFlowNet("reshape_reduce", targetId);
runTensorFlowNet("flatten", targetId, true);
}
TEST_P(Test_TensorFlow_layers, padding)
{
int targetId = GetParam();
runTensorFlowNet("padding_same", targetId);
runTensorFlowNet("padding_valid", targetId);
runTensorFlowNet("spatial_padding", targetId);
}
TEST_P(Test_TensorFlow_layers, pooling)
{
runTensorFlowNet("max_pool_even");
runTensorFlowNet("max_pool_odd_valid");
runTensorFlowNet("max_pool_odd_same");
runTensorFlowNet("reduce_mean"); // an average pooling over all spatial dimensions.
}
TEST_P(Test_TensorFlow_layers, matmul)
{
int targetId = GetParam();
runTensorFlowNet("matmul", targetId);
runTensorFlowNet("nhwc_reshape_matmul", targetId);
runTensorFlowNet("nhwc_transpose_reshape_matmul", targetId);
}
TEST_P(Test_TensorFlow_layers, matmul)
{
if (backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16)
throw SkipTestException("");
runTensorFlowNet("matmul");
runTensorFlowNet("nhwc_reshape_matmul");
runTensorFlowNet("nhwc_transpose_reshape_matmul");
}
TEST_P(Test_TensorFlow_layers, unfused_flatten)
{
if (backend == DNN_BACKEND_INFERENCE_ENGINE &&
(target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16))
throw SkipTestException("");
runTensorFlowNet("unfused_flatten");
runTensorFlowNet("unfused_flatten_unknown_batch");
}
TEST_P(Test_TensorFlow_layers, lstm)
{
if (backend == DNN_BACKEND_INFERENCE_ENGINE ||
(backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16))
throw SkipTestException("");
runTensorFlowNet("lstm", true);
runTensorFlowNet("lstm", true, 0.0, 0.0, true);
}
TEST_P(Test_TensorFlow_layers, conv)
{
int targetId = GetParam();
runTensorFlowNet("single_conv", targetId);
runTensorFlowNet("atrous_conv2d_valid", targetId);
runTensorFlowNet("atrous_conv2d_same", targetId);
runTensorFlowNet("depthwise_conv2d", targetId);
}
TEST_P(Test_TensorFlow_layers, pooling)
{
int targetId = GetParam();
runTensorFlowNet("max_pool_even", targetId);
runTensorFlowNet("max_pool_odd_valid", targetId);
runTensorFlowNet("ave_pool_same", targetId);
runTensorFlowNet("max_pool_odd_same", targetId);
}
TEST_P(Test_TensorFlow_layers, deconvolution)
{
int targetId = GetParam();
runTensorFlowNet("deconvolution", targetId);
runTensorFlowNet("deconvolution_same", targetId);
runTensorFlowNet("deconvolution_stride_2_same", targetId);
runTensorFlowNet("deconvolution_adj_pad_valid", targetId);
runTensorFlowNet("deconvolution_adj_pad_same", targetId);
}
TEST_P(Test_TensorFlow_layers, batch_norm)
{
int targetId = GetParam();
runTensorFlowNet("batch_norm", targetId);
runTensorFlowNet("fused_batch_norm", targetId);
runTensorFlowNet("batch_norm_text", targetId, true);
runTensorFlowNet("mvn_batch_norm", targetId);
runTensorFlowNet("mvn_batch_norm_1x1", targetId);
}
TEST_P(Test_TensorFlow_layers, reshape)
{
if (backend == DNN_BACKEND_INFERENCE_ENGINE)
throw SkipTestException("");
runTensorFlowNet("shift_reshape_no_reorder");
runTensorFlowNet("reshape_no_reorder");
runTensorFlowNet("reshape_reduce");
runTensorFlowNet("reshape_as_shape");
}
TEST(Test_TensorFlow, memory_read)
{
double l1 = 1e-5;
double lInf = 1e-4;
runTensorFlowNet("lstm", DNN_TARGET_CPU, true, l1, lInf, true);
runTensorFlowNet("batch_norm", DNN_TARGET_CPU, false, l1, lInf, true);
runTensorFlowNet("fused_batch_norm", DNN_TARGET_CPU, false, l1, lInf, true);
runTensorFlowNet("batch_norm_text", DNN_TARGET_CPU, true, l1, lInf, true);
}
TEST_P(Test_TensorFlow_layers, slice)
{
if (backend == DNN_BACKEND_INFERENCE_ENGINE &&
(target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16))
throw SkipTestException("");
runTensorFlowNet("slice_4d");
}
TEST_P(Test_TensorFlow_layers, flatten)
{
if (backend == DNN_BACKEND_INFERENCE_ENGINE &&
(target == DNN_TARGET_OPENCL || target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD))
throw SkipTestException("");
runTensorFlowNet("flatten", true);
}
// TODO: fix tests and replace to pooling
TEST_P(Test_TensorFlow_layers, ave_pool_same)
{
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE < 2018030000
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
throw SkipTestException("Test is enabled starts from OpenVINO 2018R3");
#endif
runTensorFlowNet("ave_pool_same");
}
TEST(Test_TensorFlow, fp16)
{
const float l1 = 1e-3;
const float lInf = 1e-2;
runTensorFlowNet("fp16_single_conv", DNN_TARGET_CPU, false, l1, lInf);
runTensorFlowNet("fp16_deconvolution", DNN_TARGET_CPU, false, l1, lInf);
runTensorFlowNet("fp16_max_pool_odd_same", DNN_TARGET_CPU, false, l1, lInf);
runTensorFlowNet("fp16_padding_valid", DNN_TARGET_CPU, false, l1, lInf);
runTensorFlowNet("fp16_eltwise_add_mul", DNN_TARGET_CPU, false, l1, lInf);
runTensorFlowNet("fp16_max_pool_odd_valid", DNN_TARGET_CPU, false, l1, lInf);
runTensorFlowNet("fp16_pad_and_concat", DNN_TARGET_CPU, false, l1, lInf);
runTensorFlowNet("fp16_max_pool_even", DNN_TARGET_CPU, false, l1, lInf);
runTensorFlowNet("fp16_padding_same", DNN_TARGET_CPU, false, l1, lInf);
}
// TODO: fix pad_and_concat and add this test case to fp16_weights
TEST_P(Test_TensorFlow_layers, fp16_pad_and_concat)
{
const float l1 = 0.00071;
const float lInf = 0.012;
#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_RELEASE < 2018030000
if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD)
throw SkipTestException("Test is enabled starts from OpenVINO 2018R3");
#endif
runTensorFlowNet("fp16_pad_and_concat", false, l1, lInf);
}
TEST_P(Test_TensorFlow_layers, fp16_weights)
{
const float l1 = 0.00071;
const float lInf = 0.012;
runTensorFlowNet("fp16_single_conv", false, l1, lInf);
runTensorFlowNet("fp16_deconvolution", false, l1, lInf);
runTensorFlowNet("fp16_max_pool_odd_same", false, l1, lInf);
runTensorFlowNet("fp16_padding_valid", false, l1, lInf);
runTensorFlowNet("fp16_eltwise_add_mul", false, l1, lInf);
runTensorFlowNet("fp16_max_pool_odd_valid", false, l1, lInf);
runTensorFlowNet("fp16_max_pool_even", false, l1, lInf);
runTensorFlowNet("fp16_padding_same", false, l1, lInf);
}
TEST_P(Test_TensorFlow_layers, deconvolution)
{
runTensorFlowNet("deconvolution");
runTensorFlowNet("deconvolution_same");
runTensorFlowNet("deconvolution_stride_2_same");
runTensorFlowNet("deconvolution_adj_pad_valid");
runTensorFlowNet("deconvolution_adj_pad_same");
runTensorFlowNet("keras_deconv_valid");
runTensorFlowNet("keras_deconv_same");
}
TEST_P(Test_TensorFlow_layers, conv)
{
runTensorFlowNet("single_conv");
runTensorFlowNet("atrous_conv2d_valid");
runTensorFlowNet("atrous_conv2d_same");
runTensorFlowNet("depthwise_conv2d");
runTensorFlowNet("keras_atrous_conv2d_same");
runTensorFlowNet("conv_pool_nchw");
}
TEST_P(Test_TensorFlow_layers, eltwise_add_mul)
{
runTensorFlowNet("eltwise_add_mul", GetParam());
}
TEST(Test_TensorFlow, resize_nearest_neighbor)
{
runTensorFlowNet("resize_nearest_neighbor");
}
TEST(Test_TensorFlow, slice)
{
runTensorFlowNet("slice_4d");
}
TEST(Test_TensorFlow, split)
{
runTensorFlowNet("split_equals");
}
TEST(Test_TensorFlow, lstm)
{
runTensorFlowNet("lstm", DNN_TARGET_CPU, true);
}
TEST(Test_TensorFlow, quantized)
{
runTensorFlowNet("uint8_single_conv");
}
TEST_P(Test_TensorFlow_layers, pad_and_concat)
{
runTensorFlowNet("pad_and_concat", GetParam());
}
TEST(Test_TensorFlow, defun)
{
runTensorFlowNet("defun_dropout");
}
