Fix TransposeConv op's declaration

TransposeConv has tensor 1 as its weight, but the definition and tests sometimes assume tensor 2 as weight.

PiperOrigin-RevId: 348865651
Change-Id: I5f0aed5a17ef60778540655654726358ac7ad0a5

Author: teijeong

tensorflow/compiler/mlir/lite/ir/tfl_ops.td

@@ -592,7 +592,7 @@ def TFL_TransposeConvOp: TFL_Op<"transpose_conv", [
     PredOpTrait<"input and output must have same element type",
       TFL_TCresVTEtIsSameAsOp<0, 2>>,
     AccumulatorUniformScale<3, 1, 2>,
-    AffineQuantizedOpInterface, AffineOpCoefficient<0, 2>,
+    AffineQuantizedOpInterface, AffineOpCoefficient<0, 1>,
     TFL_SparseOp]> {
   let summary = "Transpose convolution operator";
 
@@ -620,7 +620,6 @@ def TFL_TransposeConvOp: TFL_Op<"transpose_conv", [
     // AffineQuantizedOpInterface:
     int GetChannelDimIndex() { return 0; }
     int GetQuantizationDimIndex() { return 0; }
-    int GetAffineOperandIndex() { return 2; }
     // SparseOpInterface:
     std::vector<int> GetSparseOperands() { return {1}; }
     std::vector<std::vector<int>> GetFloatBlockSize() { return {}; }

tensorflow/compiler/mlir/lite/tests/prepare-quantize-signed.mlir

@@ -153,16 +153,16 @@ func @QuantizeFullyConnected(%arg0: tensor<1x224x224x3xf32>) -> tensor<1x112x112
 func @QuantizeTransposeConv(%arg0: tensor<32x4x4x128xf32>, %arg1: tensor<4xi32>) -> tensor<1x32x42x128xf32> {
   %w = constant dense<127.0> : tensor<1x32x42x128xf32>
   %b = constant dense<0.0> : tensor<1x32x42x128xf32>
-  %tc = "tfl.transpose_conv"(%arg1, %arg0, %w, %b) {padding = "SAME", stride_h = 2 : i32, stride_w = 2 : i32} : (tensor<4xi32>, tensor<32x4x4x128xf32>, tensor<1x32x42x128xf32>, tensor<1x32x42x128xf32>) -> tensor<1x32x42x128xf32>
+  %tc = "tfl.transpose_conv"(%arg1, %w, %arg0, %b) {padding = "SAME", stride_h = 2 : i32, stride_w = 2 : i32} : (tensor<4xi32>, tensor<1x32x42x128xf32>, tensor<32x4x4x128xf32>, tensor<1x32x42x128xf32>) -> tensor<1x32x42x128xf32>
   return %tc : tensor<1x32x42x128xf32>
 
 // CHECK: %[[CST:.*]] = constant dense<1.270000e+02> : tensor<1x32x42x128xf32>
 // CHECK: %[[QUANTIZE:.*]] = "tfl.quantize"(%[[CST]]) {qtype = tensor<1x32x42x128x!quant.uniform<i8<-127:127>:f32:0, {1.000000e+00}>>, volatile}
 // CHECK: %[[DEQUANTIZE:.*]] = "tfl.dequantize"(%[[QUANTIZE]]) : (tensor<1x32x42x128x!quant.uniform<i8<-127:127>:f32:0, {1.000000e+00}>>) -> tensor<1x32x42x128xf32>
-// CHECK: "tfl.transpose_conv"(%arg1, %arg0, %[[DEQUANTIZE]]
+// CHECK: "tfl.transpose_conv"(%arg1, %[[DEQUANTIZE]], %arg0,
 
 // PerTensor: %[[CST:.*]] = constant dense<1.270000e+02> : tensor<1x32x42x128xf32>
 // PerTensor: %[[QUANTIZE:.*]] = "tfl.quantize"(%[[CST]]) {qtype = tensor<1x32x42x128x!quant.uniform<i8<-127:127>:f32, 1.000000e+00>>, volatile}
 // PerTensor: %[[DEQUANTIZE:.*]] = "tfl.dequantize"(%[[QUANTIZE]]) : (tensor<1x32x42x128x!quant.uniform<i8<-127:127>:f32, 1.000000e+00>>) -> tensor<1x32x42x128xf32>
-// PerTensor: "tfl.transpose_conv"(%arg1, %arg0, %[[DEQUANTIZE]]
+// PerTensor: "tfl.transpose_conv"(%arg1, %[[DEQUANTIZE]], %arg0,
 }