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Add op definitions for unary kernels which already can be generated.

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PiperOrigin-RevId: 329907244
Change-Id: Ibda80685eeb6bbe34818fba12a2f46500a038ee3
This commit is contained in:
Adrian Kuegel 2020-09-03 06:29:50 -07:00 committed by TensorFlower Gardener
parent 73a37969bf
commit d74cd4a2a0
9 changed files with 136 additions and 0 deletions
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96
tensorflow/core/kernels/mlir_generated/BUILD
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@ -132,3 +132,99 @@ gen_kernel_library(
],
unroll_factors = "4",
)
gen_kernel_library(
name = "ceil",
same_shape = "0,1",
tile_size = "256",
types = [
"f16",
"f32",
"f64",
],
unroll_factors = "4",
)
gen_kernel_library(
name = "cos",
same_shape = "0,1",
tile_size = "256",
types = [
"f16",
"f32",
"f64",
],
unroll_factors = "4",
)
gen_kernel_library(
name = "exp",
same_shape = "0,1",
tile_size = "256",
types = [
"f16",
"f32",
"f64",
],
unroll_factors = "4",
)
gen_kernel_library(
name = "floor",
same_shape = "0,1",
tile_size = "256",
types = [
"f16",
"f32",
"f64",
],
unroll_factors = "4",
)
gen_kernel_library(
name = "log",
same_shape = "0,1",
tile_size = "256",
types = [
"f16",
"f32",
"f64",
],
unroll_factors = "4",
)
gen_kernel_library(
name = "neg",
same_shape = "0,1",
tile_size = "256",
types = [
"f16",
"f32",
"f64",
],
unroll_factors = "4",
)
gen_kernel_library(
name = "rsqrt",
same_shape = "0,1",
tile_size = "256",
types = [
"f16",
"f32",
"f64",
],
unroll_factors = "4",
)
gen_kernel_library(
name = "sqrt",
same_shape = "0,1",
tile_size = "256",
types = [
"f16",
"f32",
"f64",
],
unroll_factors = "4",
)

5
tensorflow/core/kernels/mlir_generated/op_definitions/ceil.mlir.tmpl Normal file
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@ -0,0 +1,5 @@
func @ceil(%arg0: tensor<?xelem_type>) -> tensor<?xelem_type> {
%0 = "tf.Ceil"(%arg0) { }
: (tensor<?xelem_type>) -> tensor<?xelem_type>
return %0 : tensor<?xelem_type>
}

5
tensorflow/core/kernels/mlir_generated/op_definitions/cos.mlir.tmpl Normal file
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@ -0,0 +1,5 @@
func @cos(%arg0: tensor<?xelem_type>) -> tensor<?xelem_type> {
%0 = "tf.Cos"(%arg0) { }
: (tensor<?xelem_type>) -> tensor<?xelem_type>
return %0 : tensor<?xelem_type>
}

5
tensorflow/core/kernels/mlir_generated/op_definitions/exp.mlir.tmpl Normal file
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@ -0,0 +1,5 @@
func @exp(%arg0: tensor<?xelem_type>) -> tensor<?xelem_type> {
%0 = "tf.Exp"(%arg0) { }
: (tensor<?xelem_type>) -> tensor<?xelem_type>
return %0 : tensor<?xelem_type>
}

5
tensorflow/core/kernels/mlir_generated/op_definitions/floor.mlir.tmpl Normal file
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@ -0,0 +1,5 @@
func @floor(%arg0: tensor<?xelem_type>) -> tensor<?xelem_type> {
%0 = "tf.Floor"(%arg0) { }
: (tensor<?xelem_type>) -> tensor<?xelem_type>
return %0 : tensor<?xelem_type>
}

5
tensorflow/core/kernels/mlir_generated/op_definitions/log.mlir.tmpl Normal file
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@ -0,0 +1,5 @@
func @log(%arg0: tensor<?xelem_type>) -> tensor<?xelem_type> {
%0 = "tf.Log"(%arg0) { }
: (tensor<?xelem_type>) -> tensor<?xelem_type>
return %0 : tensor<?xelem_type>
}

5
tensorflow/core/kernels/mlir_generated/op_definitions/neg.mlir.tmpl Normal file
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@ -0,0 +1,5 @@
func @neg(%arg0: tensor<?xelem_type>) -> tensor<?xelem_type> {
%0 = "tf.Neg"(%arg0) { }
: (tensor<?xelem_type>) -> tensor<?xelem_type>
return %0 : tensor<?xelem_type>
}

5
tensorflow/core/kernels/mlir_generated/op_definitions/rsqrt.mlir.tmpl Normal file
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@ -0,0 +1,5 @@
func @rsqrt(%arg0: tensor<?xelem_type>) -> tensor<?xelem_type> {
%0 = "tf.Rsqrt"(%arg0) { }
: (tensor<?xelem_type>) -> tensor<?xelem_type>
return %0 : tensor<?xelem_type>
}

5
tensorflow/core/kernels/mlir_generated/op_definitions/sqrt.mlir.tmpl Normal file
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@ -0,0 +1,5 @@
func @sqrt(%arg0: tensor<?xelem_type>) -> tensor<?xelem_type> {
%0 = "tf.Sqrt"(%arg0) { }
: (tensor<?xelem_type>) -> tensor<?xelem_type>
return %0 : tensor<?xelem_type>
}