def IsNull : Constraint<CPred<"!$0">>;

// This pattern optimizes:
//   conv/dot_general + a + b -> conv/dot_general + (a + b)
//   conv/dot_general - a - b -> conv/dot_general - (a + b)
//   conv/dot_general + a - b -> conv/dot_general + (a - b)
//   conv/dot_general - a + b -> conv/dot_general - (a - b)
foreach OpsTuple = [
    [CHLO_BroadcastAddOp, CHLO_BroadcastAddOp, CHLO_BroadcastAddOp],

Michael Levesque-Dion <******@****.***> 1706075999 -0800

// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.

// Issue 16317: cmd/compile: internal compiler error:
//              unhandled OCONV INT -> TUNSAFEPTR

set unit=%value:~-1%
rem assume the unit is specified
set conv=%value:~0,-1%

if "%unit%" == "k" goto kilo
if "%unit%" == "K" goto kilo
if "%unit%" == "m" goto mega
if "%unit%" == "M" goto mega
if "%unit%" == "g" goto giga
if "%unit%" == "G" goto giga

rem no unit found, must be bytes; consider the whole value
set conv=%value%
rem convert to KB
set /a conv=%conv% / 1024
:kilo
rem convert to MB

  // CHECK: %[[QUANT_ARG_0:.*]] = stablehlo.uniform_quantize %[[ARG_0]]
  // CHECK: %[[CONV:.*]] = stablehlo.convolution(%[[QUANT_ARG_0]], %[[QUANT_CST]])
  // CHECK-NOT: stablehlo.uniform_quantize
  // CHECK: %[[DEQUANT:.*]] = stablehlo.uniform_dequantize %[[CONV]]
  // CHECK: return %[[DEQUANT]]
  %cst = stablehlo.constant dense<0.4> : tensor<2x3x3x2xf32>

// CHECK: %[[cast:.*]] = "tf.Cast"(%[[cst]]) <{Truncate = false}> : (tensor<2x3x3x2xbf16>) -> tensor<2x3x3x2xf32>
// CHECK: %[[conv:.*]] = "tf.Conv2D"(%arg0, %[[cast]])
// CHECK: %[[identity:.*]] = "tf.IdentityN"(%[[conv]]) {device = ""} : (tensor<1x3x2x2xf32>) -> tensor<1x3x2x2xf32>
// CHECK: return %[[identity]] : tensor<1x3x2x2xf32>

// Copyright 2021 The Go Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.

package a

func Conv(v interface{}) string {
	return conv[string](v)
}

func conv[T any](v interface{}) T {
	return v.(T)
}

func Conv2(v interface{}) (string, bool) {
	return conv2[string](v)
}

func conv2[T any](v interface{}) (T, bool) {
	x, ok := v.(T)

// CHECK: %[[CONV:.+]] = stablehlo.convolution(%[[TRANSPOSE_0]], %[[TRANSPOSE_1]]) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {pad = {{\[\[}}1, 1], [1, 1]]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x4x4x8xf32>, tensor<3x3x8x8xf32>) -> tensor<1x4x4x8xf32>
// CHECK: %[[TRANSPOSE_2:.+]] = stablehlo.transpose %[[CONV]], dims = [0, 3, 1, 2] : (tensor<1x4x4x8xf32>) -> tensor<1x8x4x4xf32>

  [(HasRankOf<1> $add_rhs_value),
   (HasEqualElementSize<[-1], [0]> $conv_out, $add_rhs)], [], (addBenefit -1)>;

// Convert conv+sub+mul pattern to conv+mul+add.
// (conv - sub) * mul -> conv * mul + (-sub) * mul
//
// This is needed to support Conv+BatchNorm pattern from Jax models converted
// using jax2tf w/o native serialization. Note that Jax2tf patterns always

                "non-broadcastable operands";
      });
    }
    filter_value = filter.getValue();
    mul_value = multiplier.getValue();
    // In MHLO, Conv filter is in HWIO format, Depthwise conv filter is in HW1O
    // format and backprop input conv filter is in HWOI format.
    // Only fuses multiplier if all dimensions other than the out channel
    // dimension are equal to 1.
    if (!TFL::IsDimensionsDegenerateExceptLastOne(