[mlir][tosa] Fixed shape inference for tosa.transpose_conv2d

[rsuderman]

Summary

Transpose conv2d shape inference was incorrect, tests did not properly validate
that the shape inference was executing. Corrected shape inference, and extended
tests to actually execute.

mlir/lib/Dialect/Tosa/IR/TosaOps.cpp

if (inputShape.hasRank()) {
     outputShape[0] = ShapedType::isDynamic(outputShape[0])
                          ? inputShape.getDimSize(0)
                          : outputShape[0];
     inputHeight = inputShape.getDimSize(1);
     inputWidth = inputShape.getDimSize(2);
   }
 
   // Weight shapes describes the filter width/height and the output channels.
-  ShapeAdaptor weightShape = operands.getShape(adaptor.input());
+  ShapeAdaptor weightShape = operands.getShape(adaptor.filter());
   if (weightShape.hasRank()) {
     outputShape[3] = ShapedType::isDynamic(outputShape[3])
                          ? weightShape.getDimSize(0)
                          : outputShape[3];
     weightHeight = weightShape.getDimSize(1);
     weightWidth = weightShape.getDimSize(2);
   }
 

mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir

func @transpose_conv2d_out_shape(%arg0: tensor<2x?x?x3xf32>, %arg1: tensor<5x3x6x3xf32>, %arg2: tensor<5xf32>) {
   // CHECK: -> tensor<2x8x9x5xf32>
   %0 = "tosa.transpose_conv2d"(%arg0, %arg1, %arg2) {dilation = [1, 1], out_pad = [0, 0], out_shape = [-1, 8, 9, -1], stride = [1, 1]} : (tensor<2x?x?x3xf32>, tensor<5x3x6x3xf32>, tensor<5xf32>) -> tensor<2x8x9x5xf32>
   return
 }
 
 // -----
 
 // CHECK-LABEL: @transpose_conv2d_static
-func @transpose_conv2d_static(%arg0: tensor<2x6x4x3xf32>, %arg1: tensor<5x3x6x3xf32>, %arg2: tensor<5xf32>) {
-  // CHECK: -> tensor<2x8x9x5xf32>
-  %0 = "tosa.transpose_conv2d"(%arg0, %arg1, %arg2) {dilation = [1, 1], out_pad = [0, 0], out_shape = [-1, -1, -1, -1], stride = [1, 1]} : (tensor<2x6x4x3xf32>, tensor<5x3x6x3xf32>, tensor<5xf32>) -> tensor<2x8x9x5xf32>
+func @transpose_conv2d_static(%arg0: tensor<2x16x14x3xf32>, %arg1: tensor<5x3x6x3xf32>, %arg2: tensor<5xf32>) {
+  // CHECK: -> tensor<2x18x19x5xf32>
+  %0 = "tosa.transpose_conv2d"(%arg0, %arg1, %arg2) {dilation = [1, 1], out_pad = [0, 0], out_shape = [-1, -1, -1, -1], stride = [1, 1]} : (tensor<2x16x14x3xf32>, tensor<5x3x6x3xf32>, tensor<5xf32>) -> tensor<2x?x?x5xf32>
+  return
+}
+
+// -----
+
+// CHECK-LABEL: @transpose_conv2d_static_dilated
+func @transpose_conv2d_static_dilated(%arg0: tensor<2x16x14x3xf32>, %arg1: tensor<5x3x6x3xf32>, %arg2: tensor<5xf32>) {
+  // CHECK: -> tensor<2x20x29x5xf32>
+  %0 = "tosa.transpose_conv2d"(%arg0, %arg1, %arg2) {dilation = [2, 3], out_pad = [0, 0], out_shape = [-1, -1, -1, -1], stride = [1, 1]} : (tensor<2x16x14x3xf32>, tensor<5x3x6x3xf32>, tensor<5xf32>) -> tensor<2x?x?x5xf32>
+  return
+}
+
+// -----
+
+// CHECK-LABEL: @transpose_conv2d_static_strided
+func @transpose_conv2d_static_strided(%arg0: tensor<2x16x14x3xf32>, %arg1: tensor<5x3x6x3xf32>, %arg2: tensor<5xf32>) {
+  // CHECK: -> tensor<2x33x45x5xf32>
+  %0 = "tosa.transpose_conv2d"(%arg0, %arg1, %arg2) {dilation = [1, 1], out_pad = [0, 0], out_shape = [-1, -1, -1, -1], stride = [2, 3]} : (tensor<2x16x14x3xf32>, tensor<5x3x6x3xf32>, tensor<5xf32>) -> tensor<2x?x?x5xf32>
   return
 }
 
 // -----
 
 // CHECK-LABEL: @transpose_conv2d_dynamic_input
 func @transpose_conv2d_dynamic_input(%arg0: tensor<?x?x?x?xf32>, %arg1: tensor<5x3x6x3xf32>, %arg2: tensor<5xf32>) {
   // CHECK: -> tensor<?x?x?x5xf32>