[MLIR][TOSA] Fix f16/bf16 support for MaxPool2D (llvm#69332)

Currently, the MaxPool2D operation in the TOSA MLIR dialect does not
accept half-precision Fp16 and Bf16 tensors, converse to what is stated
in the [TOSA
Specification](https://www.mlplatform.org/tosa/tosa_spec.html#_max_pool2d).

This patch fixes the verifier to accept the two datatypes for
input/output tensors, and adds related LIT test cases in Tosa/ops.mlir

mlir/lib/Conversion/TosaToLinalg/TosaToLinalgNamed.cpp

@@ -768,7 +768,7 @@ class MaxPool2dConverter : public OpRewritePattern<tosa::MaxPool2dOp> {
 
     // Determine what the initial value needs to be for the max pool op.
     TypedAttr initialAttr;
-    if (resultETy.isF32())
+    if (resultETy.isF32() || resultETy.isBF16() || resultETy.isF16())
       initialAttr = rewriter.getFloatAttr(
           resultETy, APFloat::getLargest(
                          cast<FloatType>(resultETy).getFloatSemantics(), true));

mlir/test/Dialect/Tosa/ops.mlir

@@ -83,12 +83,26 @@ func.func @test_matmul(%arg0: tensor<1x14x19xf32>, %arg1: tensor<1x19x28xf32>) -
 }
 
 // -----
-// CHECK-LABEL: max_pool2d
-func.func @test_max_pool2d(%arg0: tensor<1x32x32x8xf32>) -> tensor<1x32x32x8xf32> {
+// CHECK-LABEL: max_pool2d_f32
+func.func @test_max_pool2d_f32(%arg0: tensor<1x32x32x8xf32>) -> tensor<1x32x32x8xf32> {
   %0 = tosa.max_pool2d %arg0 {kernel = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x32x32x8xf32>) -> tensor<1x32x32x8xf32>
   return %0 : tensor<1x32x32x8xf32>
 }
 
+// -----
+// CHECK-LABEL: max_pool2d_bf16
+func.func @test_max_pool2d_bf16(%arg0: tensor<1x32x32x8xbf16>) -> tensor<1x32x32x8xbf16> {
+  %0 = tosa.max_pool2d %arg0 {kernel = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x32x32x8xbf16>) -> tensor<1x32x32x8xbf16>
+  return %0 : tensor<1x32x32x8xbf16>
+}
+
+// -----
+// CHECK-LABEL: max_pool2d_f16
+func.func @test_max_pool2d_f16(%arg0: tensor<1x32x32x8xf16>) -> tensor<1x32x32x8xf16> {
+  %0 = tosa.max_pool2d %arg0 {kernel = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x32x32x8xf16>) -> tensor<1x32x32x8xf16>
+  return %0 : tensor<1x32x32x8xf16>
+}
+
 // -----
 // CHECK-LABEL: rfft2d
 func.func @test_rfft2d(%arg0: tensor<13x8x16xf32>) -> (tensor<13x8x9xf32>, tensor<13x8x9xf32>) {