[Mlir-commits] [mlir] [mlir][spirv] Add Activation operators to TOSA Extended Instruction S… (PR #178620)

[Jakub Kuderski]

================
@@ -694,4 +694,182 @@ def SPIRV_TosaTransposeConv2DOp : SPIRV_TosaOpWithResult<"TransposeConv2D", 9, [
 }
 
 
+def SPIRV_TosaClampOp : SPIRV_TosaOpWithResult<"Clamp", 10, [Pure,
+  AllTypesMatch<["input", "output"]>,
+  AllElementTypesMatch<["input", "output", "min_val", "max_val"]>]> {
+  let summary = "Computes Clamp(min, max).";
+
+  let description = [{
+    Clamp to an arbitrary minimum and maximum value.
+    Maximum and minimum values are specified as values in the range of the
+    input type.
+    No zero point subtraction is done to the values, thus to clamp to the zero
+    point value, the zero point itself should be supplied as the minimum value.
+
+    References:
+      * https://github.khronos.org/SPIRV-Registry/extended/TOSA.001000.1.html#_clamp
+      * https://www.mlplatform.org/tosa/tosa_spec_1_0_1.html#_clamp
+
+    #### Example:
+    ```mlir
+    %3 = spirv.Tosa.Clamp min_val = -102 : i8, max_val = -100 : i8, nan_mode = <Propagate>, %arg0 : !spirv.arm.tensor<27x44x55xi8> -> !spirv.arm.tensor<27x44x55xi8>
+    %3 = spirv.Tosa.Clamp min_val = -1.19339396E+38 : f32, max_val = 2.38255944E+38 : f32, nan_mode = <Ignore>, %arg0 : !spirv.arm.tensor<18x5x17x6xf32> -> !spirv.arm.tensor<18x5x17x6xf32>
+    ```
+  }];
+
+  let arguments = (ins
+    SPIRV_TosaNumericalAttr: $min_val,
+    SPIRV_TosaNumericalAttr: $max_val,
+    SPIRV_TosaExtNaNPropagationModeAttr: $nan_mode,
+    SPIRV_TosaNumerical_TensorArm: $input
+  );
+
+  let results = (outs
+    SPIRV_TosaNumerical_TensorArm: $output
+  );
+
+  let assemblyFormat = [{
+    `min_val` `=` $min_val `,`
+    `max_val` `=` $max_val `,`
+    `nan_mode` `=` $nan_mode `,`
+    $input
+    attr-dict `:` type(operands) `->` type(results)
+  }];
+
+  let extraClassDeclaration = extraBaseClassDeclaration#[{
+    ::mlir::spirv::TensorArmType getInputType() {
+      return cast<::mlir::spirv::TensorArmType>(getInput().getType());
+    }
+  }];
+}
+
+
+def SPIRV_TosaErfOp : SPIRV_TosaOpWithResult<"Erf", 11, [Pure,
+  AllTypesMatch<["input", "output"]>]> {
+  let summary = "Computes Gauss Error Function of input.";
+
+  let description = [{
+    Gauss Error Function: $ erf(x) = \frac{2}{\sqrt{\pi}} \int_{0}^{x} e^{-t^2} dt $
+    For quantized integer data types, the table operator should be used instead
+    with the following definition. The ERF table has 513 entries each of
+    16-bit precision and covering the input range -4.0 to +4.0 in steps of 1/64.
+
+    References:
+      * https://github.khronos.org/SPIRV-Registry/extended/TOSA.001000.1.html#_erf
+      * https://www.mlplatform.org/tosa/tosa_spec_1_0_1.html#_erf
+
+    #### Example:
+    ```mlir
+    %0 = spirv.Tosa.Erf %arg0 : !spirv.arm.tensor<47x38x51xf32> -> !spirv.arm.tensor<47x38x51xf32>
+    ```
+  }];
+
+  let arguments = (ins
+    SPIRV_TosaFloat_TensorArm: $input
+  );
+
+  let results = (outs
+    SPIRV_TosaFloat_TensorArm: $output
+  );
+
+  let assemblyFormat = [{
+    $input
+    attr-dict `:` type(operands) `->` type(results)
+  }];
+
+  let extraClassDeclaration = extraBaseClassDeclaration#[{
+    ::mlir::spirv::TensorArmType getInputType() {
+      return cast<::mlir::spirv::TensorArmType>(getInput().getType());
+    }
+  }];
+}
+
+
+def SPIRV_TosaSigmoidOp : SPIRV_TosaOpWithResult<"Sigmoid", 12, [Pure,
+  AllTypesMatch<["input", "output"]>]> {
+  let summary = "Computes elementwise sigmoid of input.";
+
+  let description = [{
+    Applies the sigmoid logistic function to each element of the input tensor:
+    $ sigmoid(x) = \frac{1}{1 + e^{-x}} $.
----------------
kuhar wrote:

also here

https://github.com/llvm/llvm-project/pull/178620