// CHECK-SAME: %[[INPUT:[^:[:space:]]+]]
func.func @fuseMulAndConv2D(%input: tensor<1x256x256x3xf32>) -> (tensor<1x256x256x2xf32>) {
  // CHECK-DAG: %[[FILTER:.+]] = mhlo.constant dense<{{\[\[\[\[}}1.000000e+00, 2.000000e+00], [3.000000e+00, 4.000000e+00], [5.000000e+00, 6.000000e+00]]]]> : tensor<1x1x3x2xf32>
  // CHECK-DAG: %[[CST:.+]] = mhlo.constant dense<[1.000000e-01, 2.000000e-01]> : tensor<2xf32>

  // CHECK: value = dense<[1.000000e+00, 2.000000e+00, 3.000000e+00, 4.000000e+00]> : tensor<4xf16>
  %0 = "tfl.pseudo_const"() { value = dense<[1.0, 2.0, 3.0, 4.0]> : tensor<4xf16> } : () -> tensor<4xf16>
  func.return %0 : tensor<4xf16>
}

func.func @f32() -> tensor<4xf32> {
  // CHECK-LABEL: @f32
  // CHECK: value = dense<[1.000000e+00, 2.000000e+00, 3.000000e+00, 4.000000e+00]> : tensor<4xf32>

  // CHECK: value = dense<[1.000000e+00, 2.000000e+00, 3.000000e+00, 4.000000e+00]> : tensor<4xf16>
  %0 = "tfl.pseudo_const"() { value = dense<[1.0, 2.0, 3.0, 4.0]> : tensor<4xf16> } : () -> tensor<4xf16>
  func.return %0 : tensor<4xf16>
}

func.func @f32() -> tensor<4xf32> {
  // CHECK-LABEL: @f32
  // CHECK: value = dense<[1.000000e+00, 2.000000e+00, 3.000000e+00, 4.000000e+00]> : tensor<4xf32>

  %1 = stablehlo.transpose %0, dims = [1, 0] : (tensor<2x3xf32>) -> tensor<3x2xf32>
  return %1 : tensor<3x2xf32>
}
// CHECK-DAG: %[[CONST_0:.+]] = stablehlo.constant dense<{{\[\[}}0.000000e+00, 3.000000e+00], [1.000000e+00, 4.000000e+00], [2.000000e+00, 5.000000e+00]]> : tensor<3x2xf32>
// CHECK-NOT: transpose
// CHECK: return %[[CONST_0]] : tensor<3x2xf32>

// -----

// CHECK-LABEL: transpose_simple_4d

# or to provide custom queries or build logic.
name: "CodeQL"

on:
  push:
    branches:
    - master
    - "*.x"
  pull_request:
    branches:
    - master
    - "*.x"
  schedule:
    - cron: '0 0 * * 4'

jobs:
  analyze:
    name: Analyze
    runs-on: ubuntu-latest

    strategy:
      fail-fast: false
      matrix:
        # Override automatic language detection by changing the below list

        int start = dstIndex;

        dataOffset = (dstIndex - headerStart) + 26; // 26 = off from here to pad

pad = ( dataOffset - headerStart ) % 4;
pad = pad == 0 ? 0 : 4 - pad;
dataOffset += pad;

        writeInt2( fid, dst, dstIndex );
        dstIndex += 2;
        writeInt4( offset, dst, dstIndex );
        dstIndex += 4;
        for( int i = 0; i < 4; i++ ) {

  // CHECK-DAG: %[[LOOKUP1:.*]] = arith.constant dense<{{\[\[\[}}1.000000e+00, 2.000000e+00], [3.000000e+00, 4.000000e+00]], {{\[\[}}5.000000e+00, 6.000000e+00], [7.000000e+00, 8.000000e+00]], {{\[\[}}1.000000e+00, 2.000000e+00], [3.000000e+00, 4.000000e+00]]]> : tensor<3x2x2xf32>

	(2.6628203086086130543813948e+00 + 1.4531345674282185229796902e+00i),
	(2.7823278427251986247149295e+00 - 4.9756907317005224529115567e-02i),
	(1.5397025302089642757361015e+00 - 1.6271336573016637535695727e+00i),
	(1.7103411581506875260277898e+00 + 2.8170677122737589676157029e+00i),
	(3.1390392472953103383607947e+00 + 4.6612625849858653248980849e-01i),
	(2.1117080764822417640789287e+00 + 1.2381170223514273234967850e+00i),

      value: "tf.Div:z:0"
    }
  }
}
versions {
  producer: 115
  min_consumer: 12
}

# CHECK:      func @main
# CHECK-DAG: constant dense<[1.000000e+00, 2.000000e+00, 3.000000e+00, 4.000000e+00]>
# CHECK-DAG: constant dense<[5.000000e+00, 6.000000e+00, 7.000000e+00, 8.000000e+00]>
# CHECK:      "tf.If"{{.+}}else_branch = @cond_false_10{{.+}}is_stateless = true{{.+}}then_branch = @cond_true_10

        int start = dstIndex;

        this.dataOffset = ( dstIndex - this.headerStart ) + 26; // 26 = off from here to pad

        this.pad = ( this.dataOffset - this.headerStart ) % 4;
        this.pad = this.pad == 0 ? 0 : 4 - this.pad;
        this.dataOffset += this.pad;

        SMBUtil.writeInt2(this.fid, dst, dstIndex);
        dstIndex += 2;
        SMBUtil.writeInt4(this.offset, dst, dstIndex);
        dstIndex += 4;