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-rw-r--r--tensorflow/core/kernels/conv_ops_test.cc242
1 files changed, 145 insertions, 97 deletions
diff --git a/tensorflow/core/kernels/conv_ops_test.cc b/tensorflow/core/kernels/conv_ops_test.cc
index 9acc725ba8..c281153795 100644
--- a/tensorflow/core/kernels/conv_ops_test.cc
+++ b/tensorflow/core/kernels/conv_ops_test.cc
@@ -44,41 +44,43 @@ struct ConvParametersPeer {
TEST(ConvParameters, WinogradNonfusedAlgoSize) {
ConvParametersPeer conv_params_small = {{
- 1, // batch
- 32, // in_depths
- {{300, // in_rows
- 300}}, // in_cols
- 128, // out_depths
- {{3, // filter_rows
- 3}}, // filter_cols
- {{1, // dilation_rows
- 1}}, // dilation_cols
- {{1, // stride_rows
- 1}}, // stride_cols
- {{0, // padding_rows
- 0}}, // padding_cols
- DT_FLOAT, // tensor datatype
- 0, // device_id
+ 1, // batch
+ 32, // in_depths
+ {{300, // in_rows
+ 300}}, // in_cols
+ FORMAT_NCHW, // compute_data_format
+ 128, // out_depths
+ {{3, // filter_rows
+ 3}}, // filter_cols
+ {{1, // dilation_rows
+ 1}}, // dilation_cols
+ {{1, // stride_rows
+ 1}}, // stride_cols
+ {{0, // padding_rows
+ 0}}, // padding_cols
+ DT_FLOAT, // tensor datatype
+ 0, // device_id
}};
EXPECT_TRUE(
conv_params_small.ShouldIncludeWinogradNonfusedAlgoPreCudnn7<float>());
ConvParametersPeer conv_params_large = {{
- 1, // batch
- 128, // in_depths
- {{300, // in_rows
- 300}}, // in_cols
- 768, // out_depths
- {{3, // filter_rows
- 3}}, // filter_cols
- {{1, // dilation_rows
- 1}}, // dilation_cols
- {{1, // stride_rows
- 1}}, // stride_cols
- {{0, // padding_rows
- 0}}, // padding_cols
- DT_FLOAT, // tensor datatype
- 0, // device_id
+ 1, // batch
+ 128, // in_depths
+ {{300, // in_rows
+ 300}}, // in_cols
+ FORMAT_NCHW, // compute_data_format
+ 768, // out_depths
+ {{3, // filter_rows
+ 3}}, // filter_cols
+ {{1, // dilation_rows
+ 1}}, // dilation_cols
+ {{1, // stride_rows
+ 1}}, // stride_cols
+ {{0, // padding_rows
+ 0}}, // padding_cols
+ DT_FLOAT, // tensor datatype
+ 0, // device_id
}};
EXPECT_FALSE(
conv_params_large.ShouldIncludeWinogradNonfusedAlgoPreCudnn7<float>());
@@ -88,14 +90,15 @@ TEST(ConvParameters, WinogradNonfusedAlgoSize) {
class FusedResizePadConvOpTest : public OpsTestBase {
protected:
- void HandwrittenConv() {
+ template <typename T>
+ void HandwrittenConv(DataType dtype) {
const int stride = 1;
TF_EXPECT_OK(NodeDefBuilder("fused_resize_op", "FusedResizeAndPadConv2D")
- .Input(FakeInput(DT_FLOAT))
+ .Input(FakeInput(dtype))
.Input(FakeInput(DT_INT32))
.Input(FakeInput(DT_INT32))
- .Input(FakeInput(DT_FLOAT))
- .Attr("T", DT_FLOAT)
+ .Input(FakeInput(dtype))
+ .Attr("T", dtype)
.Attr("resize_align_corners", false)
.Attr("mode", "REFLECT")
.Attr("strides", {1, stride, stride, 1})
@@ -110,9 +113,8 @@ class FusedResizePadConvOpTest : public OpsTestBase {
// | 1 | 2 | 3 | 4 |
// | 5 | 6 | 7 | 8 |
// | 9 | 10 | 11 | 12 |
- Tensor image(DT_FLOAT,
- {image_batch_count, image_height, image_width, depth});
- test::FillValues<float>(&image, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12});
+ Tensor image(dtype, {image_batch_count, image_height, image_width, depth});
+ test::FillValues<T>(&image, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12});
// The filter matrix is:
// | 1 | 4 | 7 |
@@ -120,8 +122,8 @@ class FusedResizePadConvOpTest : public OpsTestBase {
// | 3 | 6 | 9 |
const int filter_size = 3;
const int filter_count = 1;
- Tensor filter(DT_FLOAT, {filter_size, filter_size, depth, filter_count});
- test::FillValues<float>(&filter, {1, 4, 7, 2, 5, 8, 3, 6, 9});
+ Tensor filter(dtype, {filter_size, filter_size, depth, filter_count});
+ test::FillValues<T>(&filter, {1, 4, 7, 2, 5, 8, 3, 6, 9});
const int resized_width = image_width;
const int resized_height = image_height;
@@ -131,12 +133,12 @@ class FusedResizePadConvOpTest : public OpsTestBase {
const int left_padding = 0;
const int right_padding = 0;
- AddInputFromArray<float>(image.shape(), image.flat<float>());
+ AddInputFromArray<T>(image.shape(), image.flat<T>());
AddInputFromArray<int32>(TensorShape({2}), {resized_height, resized_width});
AddInputFromArray<int32>(
TensorShape({4, 2}),
{0, 0, top_padding, bottom_padding, left_padding, right_padding, 0, 0});
- AddInputFromArray<float>(filter.shape(), filter.flat<float>());
+ AddInputFromArray<T>(filter.shape(), filter.flat<T>());
TF_ASSERT_OK(RunOpKernel());
// We're sliding the 3x3 filter across the 3x4 image, with accesses outside
@@ -160,21 +162,22 @@ class FusedResizePadConvOpTest : public OpsTestBase {
// | 187 | 234 | 261 | 121 |
const int expected_width = image_width;
const int expected_height = image_height * filter_count;
- Tensor expected(DT_FLOAT, TensorShape({image_batch_count, expected_height,
- expected_width, filter_count}));
- test::FillValues<float>(
+ Tensor expected(dtype, TensorShape({image_batch_count, expected_height,
+ expected_width, filter_count}));
+ test::FillValues<T>(
&expected, {105, 150, 183, 95, 235, 312, 357, 178, 187, 234, 261, 121});
const Tensor& output = *GetOutput(0);
- test::ExpectTensorNear<float>(expected, output, 1e-5);
+ test::ExpectTensorNear<T>(expected, output, 1e-5);
}
+ template <typename T>
void CompareFusedAndSeparate(int input_width, int input_height,
int input_depth, int resize_width,
int resize_height, int y_padding, int x_padding,
int filter_size, int filter_count,
bool resize_align_corners,
const string& pad_mode, int stride,
- const string& padding) {
+ const string& padding, DataType dtype) {
auto root = tensorflow::Scope::NewRootScope();
using namespace ::tensorflow::ops; // NOLINT(build/namespaces)
@@ -183,29 +186,34 @@ class FusedResizePadConvOpTest : public OpsTestBase {
test::FillIota<float>(&input_data, 1.0f);
Output input =
Const(root.WithOpName("input"), Input::Initializer(input_data));
+ Output casted_input = Cast(root.WithOpName("casted_input"), input, dtype);
Tensor filter_data(DT_FLOAT, TensorShape({filter_size, filter_size,
input_depth, filter_count}));
test::FillIota<float>(&filter_data, 1.0f);
Output filter =
Const(root.WithOpName("filter"), Input::Initializer(filter_data));
+ Output casted_filter =
+ Cast(root.WithOpName("casted_filter"), filter, dtype);
Output resize_size =
Const(root.WithOpName("resize_size"), {resize_height, resize_width});
Output resize =
ResizeBilinear(root.WithOpName("resize"), input, resize_size,
ResizeBilinear::AlignCorners(resize_align_corners));
+ // Bilinear resize only output float, cast it to dtype to match the input.
+ Output casted_resize = Cast(root.WithOpName("cast"), resize, dtype);
Output paddings =
Const(root.WithOpName("paddings"),
{{0, 0}, {y_padding, y_padding}, {x_padding, x_padding}, {0, 0}});
- Output mirror_pad =
- MirrorPad(root.WithOpName("mirror_pad"), resize, paddings, pad_mode);
- Output conv = Conv2D(root.WithOpName("conv"), mirror_pad, filter,
+ Output mirror_pad = MirrorPad(root.WithOpName("mirror_pad"), casted_resize,
+ paddings, pad_mode);
+ Output conv = Conv2D(root.WithOpName("conv"), mirror_pad, casted_filter,
{1, stride, stride, 1}, padding);
Output fused_conv = FusedResizeAndPadConv2D(
- root.WithOpName("fused_conv"), input, resize_size, paddings, filter,
- pad_mode, {1, stride, stride, 1}, padding,
+ root.WithOpName("fused_conv"), casted_input, resize_size, paddings,
+ casted_filter, pad_mode, {1, stride, stride, 1}, padding,
FusedResizeAndPadConv2D::ResizeAlignCorners(resize_align_corners));
tensorflow::GraphDef graph;
@@ -221,14 +229,16 @@ class FusedResizePadConvOpTest : public OpsTestBase {
std::vector<Tensor> fused_tensors;
TF_ASSERT_OK(session->Run({}, {"fused_conv"}, {}, &fused_tensors));
- test::ExpectClose(unfused_tensors[0], fused_tensors[0]);
+ test::ExpectTensorNear<T>(unfused_tensors[0], fused_tensors[0], 1e-5);
}
+ template <typename T>
void CompareFusedPadOnlyAndSeparate(int input_width, int input_height,
int input_depth, int y_padding,
int x_padding, int filter_size,
int filter_count, const string& pad_mode,
- int stride, const string& padding) {
+ int stride, const string& padding,
+ DataType dtype) {
auto root = tensorflow::Scope::NewRootScope();
using namespace ::tensorflow::ops; // NOLINT(build/namespaces)
@@ -237,24 +247,27 @@ class FusedResizePadConvOpTest : public OpsTestBase {
test::FillIota<float>(&input_data, 1.0f);
Output input =
Const(root.WithOpName("input"), Input::Initializer(input_data));
+ Output casted_input = Cast(root.WithOpName("casted_input"), input, dtype);
Tensor filter_data(DT_FLOAT, TensorShape({filter_size, filter_size,
input_depth, filter_count}));
test::FillIota<float>(&filter_data, 1.0f);
Output filter =
Const(root.WithOpName("filter"), Input::Initializer(filter_data));
+ Output casted_filter =
+ Cast(root.WithOpName("casted_filter"), filter, dtype);
Output paddings =
Const(root.WithOpName("paddings"),
{{0, 0}, {y_padding, y_padding}, {x_padding, x_padding}, {0, 0}});
- Output mirror_pad =
- MirrorPad(root.WithOpName("mirror_pad"), input, paddings, pad_mode);
- Output conv = Conv2D(root.WithOpName("conv"), mirror_pad, filter,
+ Output mirror_pad = MirrorPad(root.WithOpName("mirror_pad"), casted_input,
+ paddings, pad_mode);
+ Output conv = Conv2D(root.WithOpName("conv"), mirror_pad, casted_filter,
{1, stride, stride, 1}, padding);
- Output fused_conv =
- FusedPadConv2D(root.WithOpName("fused_conv"), input, paddings, filter,
- pad_mode, {1, stride, stride, 1}, padding);
+ Output fused_conv = FusedPadConv2D(
+ root.WithOpName("fused_conv"), casted_input, paddings, casted_filter,
+ pad_mode, {1, stride, stride, 1}, padding);
tensorflow::GraphDef graph;
TF_ASSERT_OK(root.ToGraphDef(&graph));
@@ -269,95 +282,130 @@ class FusedResizePadConvOpTest : public OpsTestBase {
std::vector<Tensor> fused_tensors;
TF_ASSERT_OK(session->Run({}, {"fused_conv"}, {}, &fused_tensors));
- test::ExpectClose(unfused_tensors[0], fused_tensors[0]);
+ test::ExpectTensorNear<T>(unfused_tensors[0], fused_tensors[0], 1e-5);
}
};
-TEST_F(FusedResizePadConvOpTest, HandwrittenConv) { HandwrittenConv(); }
+TEST_F(FusedResizePadConvOpTest, HandwrittenConvHalf) {
+ HandwrittenConv<Eigen::half>(DT_HALF);
+}
-TEST_F(FusedResizePadConvOpTest, IdentityComparative) {
- CompareFusedAndSeparate(10, 10, 1, 10, 10, 0, 0, 1, 1, false, "REFLECT", 1,
- "SAME");
+TEST_F(FusedResizePadConvOpTest, HandwrittenConvFloat) {
+ HandwrittenConv<float>(DT_FLOAT);
+}
+
+TEST_F(FusedResizePadConvOpTest, HandwrittenConvDouble) {
+ HandwrittenConv<double>(DT_DOUBLE);
+}
+
+TEST_F(FusedResizePadConvOpTest, IdentityComparativeHalf) {
+ CompareFusedAndSeparate<Eigen::half>(10, 10, 1, 10, 10, 0, 0, 1, 1, false,
+ "REFLECT", 1, "SAME", DT_HALF);
+}
+
+TEST_F(FusedResizePadConvOpTest, IdentityComparativeFloat) {
+ CompareFusedAndSeparate<float>(10, 10, 1, 10, 10, 0, 0, 1, 1, false,
+ "REFLECT", 1, "SAME", DT_FLOAT);
+}
+
+TEST_F(FusedResizePadConvOpTest, IdentityComparativeDouble) {
+ CompareFusedAndSeparate<double>(10, 10, 1, 10, 10, 0, 0, 1, 1, false,
+ "REFLECT", 1, "SAME", DT_DOUBLE);
}
TEST_F(FusedResizePadConvOpTest, ConvOnlyComparative) {
- CompareFusedAndSeparate(10, 10, 3, 10, 10, 0, 0, 4, 4, false, "REFLECT", 1,
- "SAME");
+ CompareFusedAndSeparate<float>(10, 10, 3, 10, 10, 0, 0, 4, 4, false,
+ "REFLECT", 1, "SAME", DT_FLOAT);
}
TEST_F(FusedResizePadConvOpTest, ResizeOnlyComparative) {
- CompareFusedAndSeparate(10, 10, 1, 20, 20, 0, 0, 1, 1, false, "REFLECT", 1,
- "SAME");
+ CompareFusedAndSeparate<float>(10, 10, 1, 20, 20, 0, 0, 1, 1, false,
+ "REFLECT", 1, "SAME", DT_FLOAT);
}
TEST_F(FusedResizePadConvOpTest, ResizeAndConvComparative) {
- CompareFusedAndSeparate(2, 2, 4, 4, 2, 0, 0, 2, 2, false, "REFLECT", 1,
- "SAME");
+ CompareFusedAndSeparate<float>(2, 2, 4, 4, 2, 0, 0, 2, 2, false, "REFLECT", 1,
+ "SAME", DT_FLOAT);
}
TEST_F(FusedResizePadConvOpTest, ResizeAlignAndConvComparative) {
- CompareFusedAndSeparate(2, 2, 4, 4, 2, 0, 0, 2, 2, true, "REFLECT", 1,
- "SAME");
+ CompareFusedAndSeparate<float>(2, 2, 4, 4, 2, 0, 0, 2, 2, true, "REFLECT", 1,
+ "SAME", DT_FLOAT);
}
TEST_F(FusedResizePadConvOpTest, ResizeAndConvStridedComparative) {
- CompareFusedAndSeparate(2, 2, 4, 4, 2, 0, 0, 2, 2, false, "REFLECT", 2,
- "SAME");
+ CompareFusedAndSeparate<float>(2, 2, 4, 4, 2, 0, 0, 2, 2, false, "REFLECT", 2,
+ "SAME", DT_FLOAT);
}
TEST_F(FusedResizePadConvOpTest, ResizeAlignAndConvValidComparative) {
- CompareFusedAndSeparate(2, 2, 4, 4, 2, 0, 0, 2, 2, true, "REFLECT", 1,
- "VALID");
+ CompareFusedAndSeparate<float>(2, 2, 4, 4, 2, 0, 0, 2, 2, true, "REFLECT", 1,
+ "VALID", DT_FLOAT);
}
TEST_F(FusedResizePadConvOpTest, PadOnlyComparative) {
- CompareFusedAndSeparate(4, 4, 1, 4, 4, 2, 2, 1, 1, false, "REFLECT", 1,
- "SAME");
+ CompareFusedAndSeparate<float>(4, 4, 1, 4, 4, 2, 2, 1, 1, false, "REFLECT", 1,
+ "SAME", DT_FLOAT);
}
TEST_F(FusedResizePadConvOpTest, PadOnlyWithChannelsComparative) {
- CompareFusedAndSeparate(4, 4, 3, 4, 4, 2, 2, 1, 1, false, "REFLECT", 1,
- "SAME");
+ CompareFusedAndSeparate<float>(4, 4, 3, 4, 4, 2, 2, 1, 1, false, "REFLECT", 1,
+ "SAME", DT_FLOAT);
}
TEST_F(FusedResizePadConvOpTest, ResizeAndPadComparative) {
- CompareFusedAndSeparate(4, 4, 1, 6, 6, 2, 2, 1, 1, false, "REFLECT", 1,
- "SAME");
+ CompareFusedAndSeparate<float>(4, 4, 1, 6, 6, 2, 2, 1, 1, false, "REFLECT", 1,
+ "SAME", DT_FLOAT);
}
TEST_F(FusedResizePadConvOpTest, PadOnlySymmetricComparative) {
- CompareFusedAndSeparate(4, 4, 1, 4, 4, 2, 2, 1, 1, false, "SYMMETRIC", 1,
- "SAME");
+ CompareFusedAndSeparate<float>(4, 4, 1, 4, 4, 2, 2, 1, 1, false, "SYMMETRIC",
+ 1, "SAME", DT_FLOAT);
}
TEST_F(FusedResizePadConvOpTest, ResizeAndPadSymmetricComparative) {
- CompareFusedAndSeparate(4, 4, 3, 6, 6, 2, 2, 1, 1, false, "SYMMETRIC", 1,
- "SAME");
+ CompareFusedAndSeparate<float>(4, 4, 3, 6, 6, 2, 2, 1, 1, false, "SYMMETRIC",
+ 1, "SAME", DT_FLOAT);
+}
+
+TEST_F(FusedResizePadConvOpTest, ResizeAndPadSymmetricComparativeLarge) {
+ CompareFusedAndSeparate<float>(1000, 1000, 3, 1006, 1006, 2, 2, 1, 1, false,
+ "SYMMETRIC", 1, "SAME", DT_FLOAT);
}
-TEST_F(FusedResizePadConvOpTest, NoResizeIdentityComparative) {
- CompareFusedPadOnlyAndSeparate(10, 10, 1, 0, 0, 1, 1, "REFLECT", 1, "SAME");
+TEST_F(FusedResizePadConvOpTest, NoResizeIdentityComparativeHalf) {
+ CompareFusedPadOnlyAndSeparate<Eigen::half>(10, 10, 1, 0, 0, 1, 1, "REFLECT",
+ 1, "SAME", DT_HALF);
+}
+
+TEST_F(FusedResizePadConvOpTest, NoResizeIdentityComparativeFloat) {
+ CompareFusedPadOnlyAndSeparate<float>(10, 10, 1, 0, 0, 1, 1, "REFLECT", 1,
+ "SAME", DT_FLOAT);
+}
+
+TEST_F(FusedResizePadConvOpTest, NoResizeIdentityComparativeDouble) {
+ CompareFusedPadOnlyAndSeparate<double>(10, 10, 1, 0, 0, 1, 1, "REFLECT", 1,
+ "SAME", DT_DOUBLE);
}
TEST_F(FusedResizePadConvOpTest, NoResizeConvOnlyComparative) {
- CompareFusedPadOnlyAndSeparate(10, 10, 3, 0, 0, 4, 4, "REFLECT", 1, "SAME");
+ CompareFusedPadOnlyAndSeparate<float>(10, 10, 3, 0, 0, 4, 4, "REFLECT", 1,
+ "SAME", DT_FLOAT);
}
TEST_F(FusedResizePadConvOpTest, NoResizePadOnlyComparative) {
- CompareFusedPadOnlyAndSeparate(4, 4, 1, 2, 2, 1, 1, "REFLECT", 1, "SAME");
+ CompareFusedPadOnlyAndSeparate<float>(4, 4, 1, 2, 2, 1, 1, "REFLECT", 1,
+ "SAME", DT_FLOAT);
}
TEST_F(FusedResizePadConvOpTest, NoResizePadOnlyWithChannelsComparative) {
- CompareFusedPadOnlyAndSeparate(4, 4, 3, 2, 2, 1, 1, "REFLECT", 1, "SAME");
+ CompareFusedPadOnlyAndSeparate<float>(4, 4, 3, 2, 2, 1, 1, "REFLECT", 1,
+ "SAME", DT_FLOAT);
}
TEST_F(FusedResizePadConvOpTest, NoResizePadOnlySymmetricComparative) {
- CompareFusedPadOnlyAndSeparate(4, 4, 1, 2, 2, 1, 1, "SYMMETRIC", 1, "SAME");
-}
-
-TEST_F(FusedResizePadConvOpTest, ResizeAndPadSymmetricComparativeLarge) {
- CompareFusedAndSeparate(1000, 1000, 3, 1006, 1006, 2, 2, 1, 1, false,
- "SYMMETRIC", 1, "SAME");
+ CompareFusedPadOnlyAndSeparate<float>(4, 4, 1, 2, 2, 1, 1, "SYMMETRIC", 1,
+ "SAME", DT_FLOAT);
}
class ConvOpTest : public OpsTestBase {
generated by cgit v1.2.3 (git 2.39.1) at 2024-06-04 20:58:58 +0000