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

package json

import (
	"unicode"
	"unicode/utf8"
)

// foldName returns a folded string such that foldName(x) == foldName(y)
// is identical to bytes.EqualFold(x, y).
func foldName(in []byte) []byte {
	// This is inlinable to take advantage of "function outlining".

    return success();
  }
};

using FoldBroadcastInDimBeforeMulOp =
    FoldBroadcastInDimBeforeBinaryElementwiseOp<mhlo::MulOp>;

// Constant folds mhlo.mul, this folder doesn't have an upper limit on how many
// elements can be folded.
LogicalResult ConstantFoldMul(mhlo::MulOp op, PatternRewriter &rewriter) {
  ShapedType type = mlir::dyn_cast<ShapedType>(op.getType());
  Type etype = type.getElementType();

  // CHECK: %[[RESULT:.*]] = "tf.Mul"(%arg0, %[[CONST]]) : (tensor<1x6x8x1xf32>, tensor<f32>) -> tensor<1x6x8x1xf32>
  // CHECK: return %[[RESULT]] : tensor<1x6x8x1xf32>
}

// Do not fold if the op doesn't follow the constant folding policy. It doesn't
// fold if the  total result size is large (>1 MB) and more than 2 times the
// size of operands.

// CHECK-LABEL: DontFoldTile
func.func @DontFoldTile() -> (tensor<64x10000xi32>) {

    return mlir::failure();           \
  }

bool CanBeFolded(Operation* inst) {
  // Instructions with side effects should not be constant folded to preserve
  // the original semantics. Ops that have no side effect and zero results but
  // could be folded should have a custom folder instead of relying on the
  // TensorFlow folding hook.
  if (inst == nullptr || inst->getNumResults() == 0 ||

// Test for partial folding: only fold i32 constants.
// RUN: tac-opt-all-backends -tfl-fold-constants-to-subgraph='fold-all-constants=false' %s -split-input-file -verify-diagnostics | FileCheck --check-prefix=PARTIAL %s

// Test for fold all constants.
// RUN: tac-opt-all-backends -tfl-fold-constants-to-subgraph='fold-all-constants=true' %s -split-input-file -verify-diagnostics | FileCheck --check-prefix=ALL %s

module {

// RUN: tf-opt -tf-broadcast-fold %s | FileCheck %s

// CHECK-LABEL: @broadcast_mul0
func.func @broadcast_mul0(%arg0: tensor<5x7xf32>, %arg1: tensor<7xf32>) -> tensor<5x7xf32> {
  %cst = arith.constant dense<[5, 7]> : tensor<2xi32>
  %0 = "tf.BroadcastTo"(%arg1, %cst) : (tensor<7xf32>, tensor<2xi32>) -> tensor<5x7xf32>
  %1 = "tf.Mul"(%arg0, %0) : (tensor<5x7xf32>, tensor<5x7xf32>) -> tensor<5x7xf32>
  func.return %1 : tensor<5x7xf32>

        PatternMatcher matcher = copyAction.matcher

        ['root/folder1/folder2', 'modules/project1'].each {
            assertMatches matcher, it
        }

        ['archive/folder/file', 'root/archives/file', 'root/folder/abc',
         'collections/folder/file', 'root/collections/file', 'archives/collections/file',
         'root/folder/cde'].each {
            assertMatches matcher.negate(), it
        }
    }

Jonathan Amsterdam <******@****.***> 1700059801 -0500

// -----

// Tests that int constants are not folded.

// CHECK-LABEL: transpose_int
func.func @transpose_int() -> tensor<3x2xi32> {
  %0 = stablehlo.constant dense<0> : tensor<2x3xi32>
  %1 = stablehlo.transpose %0, dims = [1, 0] : (tensor<2x3xi32>) -> tensor<3x2xi32>
  return %1 : tensor<3x2xi32>
}
// CHECK: transpose

// -----

// Tests that transposing an argument cannot be folded.

// CHECK-LABEL: transpose_arg

// are foldable. Returns the constants generated by constant-folding or the
// original operation's outputs if not folded.
SmallVector<Value> ConstantFoldOpIfPossible(Operation* op);

// This pattern tries to constant-fold the quantizable operands of supported
// TF operations.
struct ConstantFoldQuantizableOperands : public RewritePattern {
 public: