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-rw-r--r--tensorflow/compiler/xla/tools/parser/hlo_parser_test.cc432
1 files changed, 9 insertions, 423 deletions
diff --git a/tensorflow/compiler/xla/tools/parser/hlo_parser_test.cc b/tensorflow/compiler/xla/tools/parser/hlo_parser_test.cc
index d19c6e1877..359256f064 100644
--- a/tensorflow/compiler/xla/tools/parser/hlo_parser_test.cc
+++ b/tensorflow/compiler/xla/tools/parser/hlo_parser_test.cc
@@ -25,7 +25,6 @@ namespace tools {
namespace {
using tensorflow::StringPiece;
-using tensorflow::strings::StrCat;
struct TestData {
string test_name;
@@ -36,10 +35,6 @@ string TestDataToString(const ::testing::TestParamInfo<TestData>& data) {
return data.param.test_name;
}
-// For each string below, we check that:
-// - we parse it to an HloModule successfully, and
-// - the stringification of the resulting HloModule is equal to our original
-// string.
std::vector<TestData> CreateTestCases() {
// clang-format off
return std::vector<TestData>({
@@ -48,11 +43,10 @@ std::vector<TestData> CreateTestCases() {
"AxpyParam",
R"(HloModule axpy_module:
-ENTRY %axpy.v5 (alpha: f32[], x: f32[2,4], y: f32[2,4]) -> f32[2,4] {
- %alpha = f32[] parameter(0)
- %broadcast = f32[2,4]{1,0} broadcast(f32[] %alpha), dimensions={}
+ENTRY %axpy.v5 (alpha: f32[2,4], x: f32[2,4], y: f32[2,4]) -> f32[2,4] {
+ %alpha = f32[2,4]{1,0} parameter(0)
%x = f32[2,4]{1,0} parameter(1)
- %multiply = f32[2,4]{1,0} multiply(f32[2,4]{1,0} %broadcast, f32[2,4]{1,0} %x)
+ %multiply = f32[2,4]{1,0} multiply(f32[2,4]{1,0} %alpha, f32[2,4]{1,0} %x)
%y = f32[2,4]{1,0} parameter(2)
ROOT %add = f32[2,4]{1,0} add(f32[2,4]{1,0} %multiply, f32[2,4]{1,0} %y)
}
@@ -157,7 +151,7 @@ ENTRY %SelectR1F32WithCmpR1F32sFromParamsSmall.v4 (v1: f32[4], v2: f32[4]) -> f3
%v1 = f32[4]{0} parameter(0), sharding={maximal device=1}
%v2 = f32[4]{0} parameter(1), sharding={maximal device=1}
%greater-than = pred[4]{0} greater-than(f32[4]{0} %v1, f32[4]{0} %v2), sharding={replicated}
- ROOT %select = f32[4]{0} select(pred[4]{0} %greater-than, f32[4]{0} %v1, f32[4]{0} %v2), sharding={}
+ ROOT %select = f32[4]{0} select(pred[4]{0} %greater-than, f32[4]{0} %v1, f32[4]{0} %v2)
}
)"
@@ -187,19 +181,6 @@ ENTRY %TupleCreate.v4 (v1: f32[], v2: f32[3], v3: f32[2,3]) -> (f32[], f32[3], f
)"
},
-{
-"ShardedTupleCreate",
-R"(HloModule ShardedTupleCreate_module:
-
-ENTRY %ShardedTupleCreate.v4 (v1: f32[], v2: f32[3], v3: f32[2,3]) -> (f32[], f32[3], f32[2,3]) {
- %v1 = f32[] parameter(0)
- %v2 = f32[3]{0} parameter(1)
- %v3 = f32[2,3]{1,0} parameter(2)
- ROOT %tuple = (f32[], f32[3]{0}, f32[2,3]{1,0}) tuple(f32[] %v1, f32[3]{0} %v2, f32[2,3]{1,0} %v3), sharding={{replicated}, {maximal device=0}, {replicated}}
-}
-
-)"
-},
// int32 result = 0;
// while (result < 5) { result = result + 1; }
{
@@ -231,11 +212,9 @@ ENTRY %WhileWithScalarS32Result.v2 () -> s32[] {
R"(HloModule TwoSendRecvBothWayRecvFist_module:
ENTRY %TwoSendRecvBothWayRecvFist.v3 () -> f32[] {
- %recv = (f32[], u32[]) recv(), channel_id=15, sharding={maximal device=1}
- ROOT %recv-done = f32[] recv-done((f32[], u32[]) %recv), channel_id=15, sharding={maximal device=1}
- %constant = f32[] constant(2.1), sharding={maximal device=0}
- %send = (f32[], u32[]) send(f32[] %constant), channel_id=16, sharding={maximal device=0}, control-predecessors={%recv}
- %send-done = () send-done((f32[], u32[]) %send), channel_id=16, sharding={maximal device=0}
+ %recv = f32[] recv(), channel_id=15, sharding={maximal device=1}
+ ROOT %constant = f32[] constant(2.1), sharding={maximal device=0}
+ %send = () send(f32[] %constant), channel_id=16, sharding={maximal device=0}, control-predecessors={%recv}
}
)"
@@ -269,277 +248,6 @@ ENTRY %CallR0F32IdentityScalar.v2 () -> f32[] {
}
)"
-},
-// reduce window
-{
-"ReduceWindow",
-R"(HloModule R4UnitWindow_module:
-
-%add_F32.v3 (lhs: f32[], rhs: f32[]) -> f32[] {
- %lhs = f32[] parameter(0)
- %rhs = f32[] parameter(1)
- ROOT %add = f32[] add(f32[] %lhs, f32[] %rhs)
-}
-
-ENTRY %R4UnitWindow.v3 (operand: f32[13,12,8,15]) -> f32[13,3,8,15] {
- %operand = f32[13,12,8,15]{0,3,2,1} parameter(0)
- %constant = f32[] constant(0)
- ROOT %reduce-window = f32[13,3,8,15]{0,3,2,1} reduce-window(f32[13,12,8,15]{0,3,2,1} %operand, f32[] %constant), window={size=1x1x7x1 stride=1x4x1x1 pad=0_0x0_0x3_3x0_0}, to_apply=%add_F32.v3
-}
-
-)"
-},
-// convolution
-{
-"Convolution",
-R"(HloModule Convolve1D1Window_0_module:
-
-ENTRY %Convolve1D1Window_0.v3 (input: f32[1,2,1], filter: f32[1,1,1]) -> f32[1,2,1] {
- %input = f32[1,2,1]{2,1,0} parameter(0)
- %copy = f32[1,2,1]{2,0,1} copy(f32[1,2,1]{2,1,0} %input)
- %filter = f32[1,1,1]{2,1,0} parameter(1)
- ROOT %convolution = f32[1,2,1]{2,0,1} convolution(f32[1,2,1]{2,0,1} %copy, f32[1,1,1]{2,1,0} %filter), window={size=1}, dim_labels=b0f_0io->b0f
-}
-
-)"
-},
-// reverse(constant)
-{
-"Reverse4D",
-R"(HloModule Reverse4DFloatArrayOnDim01_module:
-
-ENTRY %Reverse4DFloatArrayOnDim01.v2 () -> f32[4,3,2,1] {
- %constant = f32[4,3,2,1]{0,1,2,3} constant(f32[4,3,2,1] { { /*i0=0*/ { /*i1=0*/ {1}, {2} }, { /*i1=1*/ {3}, {4} }, { /*i1=2*/ {5}, {6} } }, { /*i0=1*/ { /*i1=0*/ {7}, {8} }, { /*i1=1*/ {9}, {10} }, { /*i1=2*/ {11}, {12} } }, { /*i0=2*/ { /*i1=0*/ {13}, {14} }, { /*i1=1*/ {15}, {16} }, { /*i1=2*/ {17}, {18} } }, { /*i0=3*/ { /*i1=0*/ {19}, {20} }, { /*i1=1*/ {21}, {22} }, { /*i1=2*/ {23}, {24} } } })
- ROOT %reverse = f32[4,3,2,1]{0,1,2,3} reverse(f32[4,3,2,1]{0,1,2,3} %constant), dimensions={0,1}
-}
-
-)"
-},
-// concat
-{
-"Concat",
-R"(HloModule Concat2x3With2x5_module:
-
-ENTRY %Concat2x3With2x5.v3 () -> f32[2,8] {
- %constant = f32[2,3]{1,0} constant(f32[2,3] { { 0, 1, 2 }, { 1000, 1001, 1002 } })
- %constant.1 = f32[2,5]{1,0} constant(f32[2,5] { { 64, 65, 66, 67, 68 }, { 1064, 1065, 1066, 1067, 1068 } })
- ROOT %concatenate = f32[2,8]{1,0} concatenate(f32[2,3]{1,0} %constant, f32[2,5]{1,0} %constant.1), dimensions={1}
-}
-
-)"
-},
-// map
-{
-"Map",
-R"(HloModule MapBinaryAdder_module:
-
-%add_F32.v3 (lhs: f32[], rhs: f32[]) -> f32[] {
- %lhs = f32[] parameter(0)
- %rhs = f32[] parameter(1)
- ROOT %add = f32[] add(f32[] %lhs, f32[] %rhs)
-}
-
-ENTRY %MapBinaryAdder.v3 (param0: f32[4], param1: f32[4]) -> f32[4] {
- %param0 = f32[4]{0} parameter(0)
- %param1 = f32[4]{0} parameter(1)
- ROOT %map = f32[4]{0} map(f32[4]{0} %param0, f32[4]{0} %param1), to_apply=%add_F32.v3
-}
-
-)"
-},
-// reduce
-{
-"Reduce",
-R"(HloModule ReduceR3ToR2_module:
-
-%add_F32.v3 (lhs: f32[], rhs: f32[]) -> f32[] {
- %lhs = f32[] parameter(0)
- %rhs = f32[] parameter(1)
- ROOT %add = f32[] add(f32[] %lhs, f32[] %rhs)
-}
-
-ENTRY %ReduceR3ToR2.v3 (input: f32[8,16,256]) -> f32[8,16] {
- %input = f32[8,16,256]{2,1,0} parameter(0)
- %constant = f32[] constant(0)
- ROOT %reduce = f32[8,16]{1,0} reduce(f32[8,16,256]{2,1,0} %input, f32[] %constant), dimensions={2}, to_apply=%add_F32.v3
-}
-
-)"
-},
-// select and scatter
-{
-"SelectAndScatter",
-R"(HloModule R4F32OverlapSmall_module:
-
-%ge_F32.v3 (lhs: f32[], rhs: f32[]) -> pred[] {
- %lhs = f32[] parameter(0)
- %rhs = f32[] parameter(1)
- ROOT %greater-than-or-equal-to = pred[] greater-than-or-equal-to(f32[] %lhs, f32[] %rhs)
-}
-
-%add_F32.v3 (lhs.1: f32[], rhs.1: f32[]) -> f32[] {
- %lhs.1 = f32[] parameter(0)
- %rhs.1 = f32[] parameter(1)
- ROOT %add = f32[] add(f32[] %lhs.1, f32[] %rhs.1)
-}
-
-ENTRY %R4F32OverlapSmall.v4 () -> f32[4,5,1,1] {
- %constant = f32[4,5,1,1]{3,2,1,0} constant(f32[4,5,1,1] { { /*i0=0*/ { /*i1=0*/ {7} }, { /*i1=1*/ {2} }, { /*i1=2*/ {5} }, { /*i1=3*/ {3} }, { /*i1=4*/ {8} } }, { /*i0=1*/ { /*i1=0*/ {3} }, { /*i1=1*/ {8} }, { /*i1=2*/ {9} }, { /*i1=3*/ {3} }, { /*i1=4*/ {4} } }, { /*i0=2*/ { /*i1=0*/ {1} }, { /*i1=1*/ {5} }, { /*i1=2*/ {7} }, { /*i1=3*/ {5} }, { /*i1=4*/ {6} } }, { /*i0=3*/ { /*i1=0*/ {0} }, { /*i1=1*/ {6} }, { /*i1=2*/ {2} }, { /*i1=3*/ {10} }, { /*i1=4*/ {2} } } })
- %constant.1 = f32[2,2,1,1]{3,2,1,0} constant(f32[2,2,1,1] { { /*i0=0*/ { /*i1=0*/ {2} }, { /*i1=1*/ {6} } }, { /*i0=1*/ { /*i1=0*/ {3} }, { /*i1=1*/ {1} } } })
- %constant.2 = f32[] constant(0)
- ROOT %select-and-scatter = f32[4,5,1,1]{3,2,1,0} select-and-scatter(f32[4,5,1,1]{3,2,1,0} %constant, f32[2,2,1,1]{3,2,1,0} %constant.1, f32[] %constant.2), window={size=2x3x1x1 stride=2x2x1x1}, select=%ge_F32.v3, scatter=%add_F32.v3
-}
-
-)"
-},
-// slice
-{
-"Slice",
-R"(HloModule slice_module:
-
-ENTRY %slice.v2 (p0: f32[3,3,4,4]) -> f32[3,3,2,4] {
- %p0 = f32[3,3,4,4]{3,2,1,0} parameter(0)
- ROOT %slice = f32[3,3,2,4]{3,2,1,0} slice(f32[3,3,4,4]{3,2,1,0} %p0), slice={[0:3:1], [0:3:1], [0:4:2], [0:4:1]}
-}
-
-)"
-},
-// slice, no stride
-{
-"SliceNoStride",
-R"(HloModule Slice3x3x3_To_1x3x3_F32_module:
-
-ENTRY %Slice3x3x3_To_1x3x3_F32.v2 () -> f32[1,3,3] {
- %constant = f32[3,3,3]{2,1,0} constant(f32[3,3,3] { { { 0, 1, 2 }, { 3, 4, 5 }, { 6, 7, 8 } }, { { 9, 10, 11 }, { 12, 13, 14 }, { 15, 16, 17 } }, { { 18, 19, 20 }, { 21, 22, 23 }, { 24, 25, 26 } } })
- ROOT %slice = f32[1,3,3]{2,1,0} slice(f32[3,3,3]{2,1,0} %constant), slice={[0:1], [0:3], [0:3]}
-}
-
-)"
-},
-// slice R0
-{
-"SliceR0",
-R"(HloModule SliceR0_module:
-
-ENTRY %SliceR0.v2 () -> s32[] {
- %constant = s32[] constant(1)
- ROOT %slice = s32[] slice(s32[] %constant), slice={}
-}
-
-)"
-},
-// transpose
-{
-"Transpose",
-R"(HloModule Transpose_module:
-
-ENTRY %Transpose.v2 () -> s32[1,2,3] {
- %constant = s32[1,2,3]{2,1,0} constant(s32[1,2,3] { { { 1, 2, 3 }, { 4, 5, 6 } } })
- ROOT %transpose = s32[1,2,3]{2,1,0} transpose(s32[1,2,3]{2,1,0} %constant), dimensions={0,1,2}
-}
-
-)"
-},
-// Dynamic slice
-{
-"DynamicSlice",
-R"(HloModule DynamicSlice_module:
-
-ENTRY %DynamicSlice.v5 (original_parameter: s32[2,2,258], start_index: s32[1]) -> s32[2,2,258] {
- %original_parameter = s32[2,2,258]{2,1,0} parameter(0)
- %constant = s32[1]{0} constant({0})
- %start_index = s32[1]{0} parameter(1)
- %concatenate = s32[3]{0} concatenate(s32[1]{0} %constant, s32[1]{0} %constant, s32[1]{0} %start_index), dimensions={0}
- ROOT %dynamic-slice = s32[2,2,258]{2,1,0} dynamic-slice(s32[2,2,258]{2,1,0} %original_parameter, s32[3]{0} %concatenate), dynamic_slice_sizes={2,2,258}
-}
-
-)"
-},
-// Dynamic update slice
-{
-"DynamicUpdateSlice",
-R"(HloModule DynamicUpdateSlice_module:
-
-ENTRY %DynamicUpdateSlice.v4 (input: s32[1,1,25,1], update: s32[1,1,2,1], start_indices: s32[4]) -> s32[1,1,25,1] {
- %input = s32[1,1,25,1]{3,2,1,0} parameter(0)
- %update = s32[1,1,2,1]{3,2,1,0} parameter(1)
- %start_indices = s32[4]{0} parameter(2)
- ROOT %dynamic-update-slice = s32[1,1,25,1]{3,2,1,0} dynamic-update-slice(s32[1,1,25,1]{3,2,1,0} %input, s32[1,1,2,1]{3,2,1,0} %update, s32[4]{0} %start_indices)
-}
-
-)"
-},
-// batch norm training
-{
-"BatchNormTraining",
-R"(HloModule BasicTraining_module:
-
-ENTRY %BasicTraining.v4 () -> (f32[2,2,1,2], f32[2], f32[2]) {
- %constant = f32[2,2,1,2]{3,2,1,0} constant(f32[2,2,1,2] { { /*i0=0*/ { /*i1=0*/ {1, 2} }, { /*i1=1*/ {3, 4} } }, { /*i0=1*/ { /*i1=0*/ {5, 6} }, { /*i1=1*/ {7, 8} } } })
- %constant.1 = f32[2]{0} constant({2, 3})
- %constant.2 = f32[2]{0} constant({1, 2})
- ROOT %batch-norm-training = (f32[2,2,1,2]{3,2,1,0}, f32[2]{0}, f32[2]{0}) batch-norm-training(f32[2,2,1,2]{3,2,1,0} %constant, f32[2]{0} %constant.1, f32[2]{0} %constant.2), epsilon=0.001, feature_index=3
-}
-
-)"
-},
-// batch norm inference
-{
-"BatchNormInference",
-R"(HloModule BatchNormInference_module:
-
-ENTRY %BatchNormInference.v6 (input: f32[2,2,2,2], offset: f32[2], scale: f32[2], mean: f32[2], variance: f32[2]) -> f32[2,2,2,2] {
- %input = f32[2,2,2,2]{3,2,1,0} parameter(0)
- %offset = f32[2]{0} parameter(1)
- %scale = f32[2]{0} parameter(2)
- %mean = f32[2]{0} parameter(3)
- %variance = f32[2]{0} parameter(4)
- ROOT %batch-norm-inference = f32[2,2,2,2]{3,2,1,0} batch-norm-inference(f32[2,2,2,2]{3,2,1,0} %input, f32[2]{0} %offset, f32[2]{0} %scale, f32[2]{0} %mean, f32[2]{0} %variance), epsilon=0.001, feature_index=0
-}
-
-)"
-},
-// batch norm grad
-{
-"BatchNormGrad",
-R"(HloModule BatchNormGrad_module:
-
-ENTRY %BatchNormGrad.v4 (input: f32[2,2,2,2], scale: f32[2], mean: f32[2], variance: f32[2], grad_output: f32[2,2,2,2]) -> (f32[2,2,2,2], f32[2], f32[2]) {
- %input = f32[2,2,2,2]{3,2,1,0} parameter(0)
- %scale = f32[2]{0} parameter(1)
- %mean = f32[2]{0} parameter(2)
- %variance = f32[2]{0} parameter(3)
- %grad_output = f32[2,2,2,2]{3,2,1,0} parameter(4)
- ROOT %batch-norm-grad = (f32[2,2,2,2]{3,2,1,0}, f32[2]{0}, f32[2]{0}) batch-norm-grad(f32[2,2,2,2]{3,2,1,0} %input, f32[2]{0} %scale, f32[2]{0} %mean, f32[2]{0} %variance, f32[2,2,2,2]{3,2,1,0} %grad_output), epsilon=0.001, feature_index=0
-}
-
-)"
-},
-// pad
-{
-"Pad",
-R"(HloModule Pad1DS3Array_module:
-
-ENTRY %Pad1DS3Array.v3 () -> f32[8] {
- %constant = f32[3]{0} constant({1, 2, 3})
- %constant.1 = f32[] constant(0.1)
- ROOT %pad = f32[8]{0} pad(f32[3]{0} %constant, f32[] %constant.1), padding=3_1
-}
-
-)"
-},
-// pad has interior
-{
-"PadHasInterior",
-R"(HloModule PadHasInterior_module:
-
-ENTRY %PadHasInterior.v3 (input: f32[1,25,7,7]) -> f32[1,25,17,11] {
- %input = f32[1,25,7,7]{3,2,1,0} parameter(0)
- %constant = f32[] constant(-5.123)
- ROOT %pad = f32[1,25,17,11]{3,2,1,0} pad(f32[1,25,7,7]{3,2,1,0} %input, f32[] %constant), padding=0_0_0x0_0_0x2_2_1x2_2_0
-}
-
-)"
}
});
// clang-format on
@@ -553,10 +261,7 @@ class HloParserTest : public ::testing::Test,
<< "'" << s << "' does not contain '" << expected << "'";
}
- // Expects "ToString(Parse(string)) == string", that is, parses the string,
- // asserts that it succeeded, stringifies the parsed module, and checks that
- // the it equals the original string.
- void ExpectEqual() {
+ void ExpectSuccess() {
const string& original = GetParam().module_string;
auto result = Parse(original);
TF_EXPECT_OK(result.status());
@@ -565,7 +270,7 @@ class HloParserTest : public ::testing::Test,
}
};
-TEST_P(HloParserTest, Run) { ExpectEqual(); }
+TEST_P(HloParserTest, Run) { ExpectSuccess(); }
INSTANTIATE_TEST_CASE_P(HloParserTestSuccessInstantiation, HloParserTest,
::testing::ValuesIn(CreateTestCases()),
@@ -722,125 +427,6 @@ ENTRY %ConstantWithExp.v4 () -> f32[] {
// printed as "300".
}
-TEST_F(HloParserTest, AttibutesAnyOrder) {
- const string original = R"(HloModule any_order_module:
-
-ENTRY %Convolve1D1Window_0.v3 (input: f32[1,2,1], filter: f32[1,1,1]) -> f32[1,2,1] {
- %input = f32[1,2,1]{2,1,0} parameter(0)
- %copy = f32[1,2,1]{2,0,1} copy(f32[1,2,1]{2,1,0} %input)
- %filter = f32[1,1,1]{2,1,0} parameter(1)
- ROOT %convolution = f32[1,2,1]{2,0,1} convolution(f32[1,2,1]{2,0,1} %copy, f32[1,1,1]{2,1,0} %filter), sharding={maximal device=1}, dim_labels=b0f_0io->b0f, window={pad=1_1 size=2}
-}
-
-)";
- TF_EXPECT_OK(Parse(original).status());
-}
-
-TEST_F(HloParserTest, InvalidDimLabels) {
- string prefix = R"(HloModule invalid_dim_labels_module:
-
-ENTRY %Convolve1D1Window_0.v3 (input: f32[1,2,1], filter: f32[1,1,1]) -> f32[1,2,1] {
- %input = f32[1,2,1]{2,1,0} parameter(0)
- %copy = f32[1,2,1]{2,0,1} copy(f32[1,2,1]{2,1,0} %input)
- %filter = f32[1,1,1]{2,1,0} parameter(1)
- ROOT %convolution = f32[1,2,1]{2,0,1} convolution(f32[1,2,1]{2,0,1} %copy, f32[1,1,1]{2,1,0} %filter), window={size=1} )";
- string suffix = R"(
-}
-
-)";
-
- ExpectHasSubstr(Parse(StrCat(prefix, ",dim_labels=00_01_10", suffix))
- .status()
- .error_message(),
- "expects dim labels pattern");
-
- ExpectHasSubstr(Parse(StrCat(prefix, ",dim_labels=010_1100->010", suffix))
- .status()
- .error_message(),
- "must have the same rank");
-
- ExpectHasSubstr(Parse(StrCat(prefix, ",dim_labels=0bf_io0->b0f", suffix))
- .status()
- .error_message(),
- "output spatial dimensions should be the same as input "
- "spatial dimensions");
-}
-
-TEST_F(HloParserTest, UnexpectedAttribute) {
- const string original = R"(HloModule unexpected_attr_module:
-
-ENTRY %TwoSendRecvBothWayRecvFist.v3 () -> f32[] {
- %recv = (f32[], u32[]) recv(), channel_id=15
- %recv-done = f32[] recv-done((f32[], u32[]) %recv), channel_id=15
- ROOT %constant = f32[] constant(2.1)
- %send = (f32[], u32[]) send(f32[] %constant), channel_id=16, calls=%recv
- %send-done = () send-done((f32[], u32[]) %send), channel_id=16
-}
-
-)";
- ExpectHasSubstr(Parse(original).status().error_message(),
- "unexpected attribute calls");
-}
-
-TEST_F(HloParserTest, MissingAttribute) {
- const string original = R"(HloModule missing_attr_module:
-
-ENTRY %TwoSendRecvBothWayRecvFist.v3 () -> f32[] {
- %recv = (f32[], u32[]) recv(), channel_id=15
- %recv-done = f32[] recv-done((f32[], u32[]) %recv), channel_id=15
- ROOT %constant = f32[] constant(-2.1)
- %send = (f32[], u32[]) send(f32[] %constant)
- %send-done = () send-done((f32[], u32[]) %send), channel_id=16
-}
-
-)";
- ExpectHasSubstr(Parse(original).status().error_message(),
- "attribute channel_id is expected but not seen");
-}
-
-TEST_F(HloParserTest, PredecessorUndefined) {
- const string original = R"(HloModule pre_not_found_module:
-
-ENTRY %TwoSendRecvBothWayRecvFist.v3 () -> f32[] {
- %recv = (f32[], u32[]) recv(), channel_id=15
- %recv-done = f32[] recv-done((f32[], u32[]) %recv), channel_id=15
- ROOT %constant = f32[] constant(2.1)
- %send = (f32[], u32[]) send(f32[] %constant), channel_id=16, control-predecessors={%done}
- %send-done = () send-done((f32[], u32[]) %send), channel_id=16
-}
-
-)";
- ExpectHasSubstr(Parse(original).status().error_message(),
- "'done' is not defined");
-}
-
-TEST_F(HloParserTest, SliceAllowOmitStride1) {
- const string original = R"(HloModule slice_module:
-
-ENTRY %slice.v2 (p0: f32[3,3,4,4]) -> f32[3,3,2,4] {
- %p0 = f32[3,3,4,4]{3,2,1,0} parameter(0)
- ROOT %slice = f32[3,3,2,4]{3,2,1,0} slice(f32[3,3,4,4]{3,2,1,0} %p0), slice={[0:3], [0:3], [0:4:2], [0:4]}
-}
-
-)";
- TF_EXPECT_OK(Parse(original).status());
-}
-
-TEST_F(HloParserTest, PaddingConfigIsNotWindowPad) {
- const string original = R"(HloModule window_pad_module:
-
-ENTRY %Convolve1D1Window_0.v3 (input: f32[1,2,1], filter: f32[1,1,1]) -> f32[1,2,1] {
- %input = f32[1,2,1]{2,1,0} parameter(0)
- %copy = f32[1,2,1]{2,0,1} copy(f32[1,2,1]{2,1,0} %input)
- %filter = f32[1,1,1]{2,1,0} parameter(1)
- ROOT %convolution = f32[1,2,1]{2,0,1} convolution(f32[1,2,1]{2,0,1} %copy, f32[1,1,1]{2,1,0} %filter), dim_labels=b0f_0io->b0f, window={pad=1_1_0 size=1}
-}
-
-)";
- ExpectHasSubstr(Parse(original).status().error_message(),
- "expects padding_low and padding_high separated by '_'");
-}
-
} // namespace
} // namespace tools
} // namespace xla
generated by cgit v1.2.3 (git 2.39.1) at 2024-05-28 23:27:51 +0000