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Merge pull request from yongtang:26069-equal-qint8-qint16-quint8-quint16

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PiperOrigin-RevId: 333868852
Change-Id: I584cbb81c18e596af4dd363b1f16432260d432f1
This commit is contained in:
TensorFlower Gardener 2020-09-25 22:33:57 -07:00
commit 065f6f6b59
5 changed files with 46 additions and 29 deletions
tensorflow
compiler/mlir/tensorflow/ir
tf_generated_ops.td
core
kernels
cwise_op_equal_to_1.cccwise_op_not_equal_to_1.cc
ops
math_ops.cc
python/kernel_tests
cwise_ops_binary_test.py

10
tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td
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@ -3229,8 +3229,8 @@ tf.math.equal(x, y) ==> array([True, True])
}];
let arguments = (ins
TensorOf<[TF_Bfloat16, TF_Bool, TF_Complex128, TF_Complex64, TF_Float16, TF_Float32, TF_Float64, TF_Int16, TF_Int32, TF_Int64, TF_Int8, TF_Qint32, TF_Qint8, TF_Quint8, TF_Str, TF_Uint16, TF_Uint32, TF_Uint64, TF_Uint8]>:$x,
TensorOf<[TF_Bfloat16, TF_Bool, TF_Complex128, TF_Complex64, TF_Float16, TF_Float32, TF_Float64, TF_Int16, TF_Int32, TF_Int64, TF_Int8, TF_Qint32, TF_Qint8, TF_Quint8, TF_Str, TF_Uint16, TF_Uint32, TF_Uint64, TF_Uint8]>:$y,
TensorOf<[TF_Bfloat16, TF_Bool, TF_Complex128, TF_Complex64, TF_Float16, TF_Float32, TF_Float64, TF_Int16, TF_Int32, TF_Int64, TF_Int8, TF_Qint16, TF_Quint16, TF_Qint32, TF_Qint8, TF_Quint8, TF_Str, TF_Uint16, TF_Uint32, TF_Uint64, TF_Uint8]>:$x,
TensorOf<[TF_Bfloat16, TF_Bool, TF_Complex128, TF_Complex64, TF_Float16, TF_Float32, TF_Float64, TF_Int16, TF_Int32, TF_Int64, TF_Int8, TF_Qint16, TF_Quint16, TF_Qint32, TF_Qint8, TF_Quint8, TF_Str, TF_Uint16, TF_Uint32, TF_Uint64, TF_Uint8]>:$y,
DefaultValuedAttr<BoolAttr, "true">:$incompatible_shape_error
);
@ -7083,8 +7083,8 @@ def TF_NotEqualOp : TF_Op<"NotEqual", [Commutative, NoSideEffect]> {
}];
let arguments = (ins
TensorOf<[TF_Bfloat16, TF_Bool, TF_Complex128, TF_Complex64, TF_Float16, TF_Float32, TF_Float64, TF_Int16, TF_Int32, TF_Int64, TF_Int8, TF_Qint32, TF_Qint8, TF_Quint8, TF_Str, TF_Uint16, TF_Uint32, TF_Uint64, TF_Uint8]>:$x,
TensorOf<[TF_Bfloat16, TF_Bool, TF_Complex128, TF_Complex64, TF_Float16, TF_Float32, TF_Float64, TF_Int16, TF_Int32, TF_Int64, TF_Int8, TF_Qint32, TF_Qint8, TF_Quint8, TF_Str, TF_Uint16, TF_Uint32, TF_Uint64, TF_Uint8]>:$y,
TensorOf<[TF_Bfloat16, TF_Bool, TF_Complex128, TF_Complex64, TF_Float16, TF_Float32, TF_Float64, TF_Int16, TF_Int32, TF_Int64, TF_Int8, TF_Qint16, TF_Quint16, TF_Qint32, TF_Qint8, TF_Quint8, TF_Str, TF_Uint16, TF_Uint32, TF_Uint64, TF_Uint8]>:$x,
TensorOf<[TF_Bfloat16, TF_Bool, TF_Complex128, TF_Complex64, TF_Float16, TF_Float32, TF_Float64, TF_Int16, TF_Int32, TF_Int64, TF_Int8, TF_Qint16, TF_Quint16, TF_Qint32, TF_Qint8, TF_Quint8, TF_Str, TF_Uint16, TF_Uint32, TF_Uint64, TF_Uint8]>:$y,
DefaultValuedAttr<BoolAttr, "true">:$incompatible_shape_error
);
@ -14110,4 +14110,4 @@ execution the transfer corresponds to.}]>:$dynamic_key,
let results = (outs);
TF_DerivedOperandTypeListAttr Tinputs = TF_DerivedOperandTypeListAttr<0>;
}
}

3
tensorflow/core/kernels/cwise_op_equal_to_1.cc
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@ -18,7 +18,8 @@ limitations under the License.
namespace tensorflow {
REGISTER7(BinaryOp, CPU, "Equal", functor::equal_to, float, Eigen::half, double,
uint8, int8, int16, bfloat16);
REGISTER3(BinaryOp, CPU, "Equal", functor::equal_to, uint16, uint32, uint64);
REGISTER7(BinaryOp, CPU, "Equal", functor::equal_to, uint16, uint32, uint64,
qint8, qint16, quint8, quint16);
REGISTER_KERNEL_BUILDER(
Name("ApproximateEqual").Device(DEVICE_CPU).TypeConstraint<float>("T"),
ApproximateEqualOp<CPUDevice, float>);

4
tensorflow/core/kernels/cwise_op_not_equal_to_1.cc
View File

@ -18,8 +18,8 @@ limitations under the License.
namespace tensorflow {
REGISTER7(BinaryOp, CPU, "NotEqual", functor::not_equal_to, float, Eigen::half,
double, uint8, int8, int16, bfloat16);
REGISTER3(BinaryOp, CPU, "NotEqual", functor::not_equal_to, uint16, uint32,
uint64);
REGISTER7(BinaryOp, CPU, "NotEqual", functor::not_equal_to, uint16, uint32,
uint64, qint8, qint16, quint8, quint16);
#if GOOGLE_CUDA || TENSORFLOW_USE_ROCM
REGISTER4(BinaryOp, GPU, "NotEqual", functor::not_equal_to, float, Eigen::half,
double, uint8);

39
tensorflow/core/ops/math_ops.cc
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@ -703,27 +703,24 @@ REGISTER_OP("GreaterEqual").COMPARISON();
// --------------------------------------------------------------------------
#define EQUALITY_COMPARISON() \
Input("x: T") \
.Input("y: T") \
.Output("z: bool") \
.SetIsCommutative() \
.Attr( \
"T: {bfloat16, half, float, double, uint8, int8, int16, int32, " \
"int64, uint16, uint32, uint64, complex64, " \
"quint8, qint8, qint32, string, bool, complex128}") \
.Attr("incompatible_shape_error: bool = true") \
.SetShapeFn([](InferenceContext* c) { \
ShapeHandle x = c->input(0); \
ShapeHandle y = c->input(1); \
ShapeHandle output; \
bool incompatible_shape_error; \
TF_RETURN_IF_ERROR(c->GetAttr("incompatible_shape_error", \
&incompatible_shape_error)); \
TF_RETURN_IF_ERROR(BroadcastBinaryOpOutputShapeFnHelper( \
c, x, y, incompatible_shape_error, &output)); \
c->set_output(0, output); \
return Status::OK(); \
#define EQUALITY_COMPARISON() \
Input("x: T") \
.Input("y: T") \
.Output("z: bool") \
.SetIsCommutative() \
.Attr("T: type") \
.Attr("incompatible_shape_error: bool = true") \
.SetShapeFn([](InferenceContext* c) { \
ShapeHandle x = c->input(0); \
ShapeHandle y = c->input(1); \
ShapeHandle output; \
bool incompatible_shape_error; \
TF_RETURN_IF_ERROR(c->GetAttr("incompatible_shape_error", \
&incompatible_shape_error)); \
TF_RETURN_IF_ERROR(BroadcastBinaryOpOutputShapeFnHelper( \
c, x, y, incompatible_shape_error, &output)); \
c->set_output(0, output); \
return Status::OK(); \
})
REGISTER_OP("Equal").EQUALITY_COMPARISON();

19
tensorflow/python/kernel_tests/cwise_ops_binary_test.py
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@ -991,6 +991,25 @@ class ComparisonOpTest(test.TestCase):
[[True, True, True, True, True], [False, False, False, False, False]],
values)
def testEqualQuantizeDType(self):
dtypes = [
dtypes_lib.qint8,
dtypes_lib.qint16,
dtypes_lib.quint8,
dtypes_lib.quint16,
]
x = np.asarray([0, 1, 2, 3, 4])
y = np.asarray([0, 1, 2, 3, 4])
for dtype in dtypes:
xt = x.astype(dtype.as_numpy_dtype)
yt = y.astype(dtype.as_numpy_dtype)
cmp_eq = math_ops.equal(xt, yt)
cmp_ne = math_ops.not_equal(xt, yt)
values = self.evaluate([cmp_eq, cmp_ne])
self.assertAllEqual(
[[True, True, True, True, True], [False, False, False, False, False]],
values)
if __name__ == "__main__":
test.main()