rng.uniform(low=0.0, high=1.0, size=static_input_shape).astype(
            np.float32
        )
    )

    def data_gen() -> repr_dataset.RepresentativeDataset:
      for _ in range(100):
        yield {
            'input_tensor': rng.uniform(
                low=0.0, high=1.0, size=static_input_shape
            ).astype(np.float32)
        }

    dataset_path = self.create_tempfile('tfrecord').full_path

// isPaddedField reports whether the i'th field of struct type t is followed
// by padding.
func isPaddedField(t Type, i int) bool {
	field := t.Field(i)
	if i+1 < t.NumField() {
		return field.Offset+field.Type.Size() != t.Field(i+1).Offset
	}
	return field.Offset+field.Type.Size() != t.Size()
}

// StructOf returns the struct type containing fields.
// The Offset and Index fields are ignored and computed as they would be

// profile that event by storing a pointer to the lock in its "to be profiled
// upon unlock" field. If that field is already set, it uses the relative
// magnitudes to weight a random choice between itself and the other lock, with
// the loser's time being added to the "additional contention" field. Otherwise
// if the M's call stack buffer is occupied, it does the comparison against that
// sample's magnitude.
//

  auto saved_pos = op_builder.saveInsertionPoint();
  op_builder.setInsertionPointToEnd(&region.front());
  mlir::Operation* cloned_op = op_builder.clone(*op);
  // Add the yield operation.
  op_builder.create<mlir::TFL::YieldOp>(op_loc, cloned_op->getResults());
  // Now emit into the function body again.
  op_builder.restoreInsertionPoint(saved_pos);

    %7 = "tf.FakeQuantWithMinMaxVarsPerChannel"(%arg1, %arg2, %arg3) {device = "", narrow_range = false, num_bits = 8 : i64} : (tensor<*xf32>, tensor<*xf32>, tensor<*xf32>) -> tensor<*xf32>
    "tfl.yield"(%7) : (tensor<*xf32>) -> ()
  }) {device = "", narrow_range = false, num_bits = 8 : i64} : (tensor<3x4xf32>, tensor<4xf32>, tensor<4xf32>) -> tensor<3x4xf32>

					if key == nil {
						check.errorf(kv, InvalidLitField, "invalid field name %s in struct literal", kv.Key)
						continue
					}
					i := fieldIndex(utyp.fields, check.pkg, key.Name, false)
					if i < 0 {
						var alt Object
						if j := fieldIndex(fields, check.pkg, key.Name, true); j >= 0 {
							alt = fields[j]
						}
						msg := check.lookupError(base, key.Name, alt, true)

	// filters fail, we don't run the second pass.
	// We consider only equal or higher priority pods in the first pass, because
	// those are the current "pod" must yield to them and not take a space opened
	// for running them. It is ok if the current "pod" take resources freed for
	// lower priority pods.
	// Requiring that the new pod is schedulable in both circumstances ensures that

	// a 33-bit seconds field, and a 30-bit wall time nanoseconds field.
	// The nanoseconds field is in the range [0, 999999999].
	// If the hasMonotonic bit is 0, then the 33-bit field must be zero
	// and the full signed 64-bit wall seconds since Jan 1 year 1 is stored in ext.
	// If the hasMonotonic bit is 1, then the 33-bit field holds a 33-bit

					if key == nil {
						check.errorf(kv, InvalidLitField, "invalid field name %s in struct literal", kv.Key)
						continue
					}
					i := fieldIndex(fields, check.pkg, key.Value, false)
					if i < 0 {
						var alt Object
						if j := fieldIndex(fields, check.pkg, key.Value, true); j >= 0 {
							alt = fields[j]
						}
						msg := check.lookupError(base, key.Value, alt, true)

		var churn func(i int)
		churn = func(i int) {
			SetGoroutineLabels(WithLabels(ctx, Labels(t.Name()+"-churn-i", fmt.Sprint(i))))
			if i == 0 {
				ready.Done()
			} else if i%16 == 0 {
				// Yield on occasion so this sequence of goroutine launches
				// doesn't monopolize a P. See issue #52934.
				runtime.Gosched()
			}
			if ctx.Err() == nil {
				go churn(i + 1)
			}
		}
		go func() {