x,
            min=ops.convert_to_tensor(self._min[0]),
            max=ops.convert_to_tensor(self._max[0]),
            num_bits=8,
            narrow_range=False,
        )
        y = array_ops.fake_quant_with_min_max_vars(
            y,
            min=ops.convert_to_tensor(self._min[1]),
            max=ops.convert_to_tensor(self._max[1]),
            num_bits=8,

<code>package math</code>, which exports function <code>Sin</code>, and
installed the compiled package in the file identified by
<code>"lib/math"</code>.
This table illustrates how <code>Sin</code> is accessed in files
that import the package after the
various types of import declaration.
</p>

<pre class="grammar">
Import declaration          Local name of Sin

import   "lib/math"         math.Sin

  // particularly seems to be the case for the control edges between _SOURCE
  // and _SINK that the Graph constructor inserts. Copy the input edges and
  // sort the edges, but only the control edges, not data edges!
  // TODO(jmolloy): We should probably just ignore _SOURCE and _SINK nodes.
  // They'll break roundtripping anyway unless we strip them when converting
  // back to graphdef.

^bb0(%arg0: tensor<? x f32>):
  // CHECK: "tfl.sin"(%arg0)
  %0 = "tfl.sin"(%arg0): (tensor<? x f32>) -> tensor<? x f32>
  func.return %0 : tensor<? x f32>
}

// -----

// test invalid Sin input
func.func @testSinWithWrongInputType(tensor<?xi32>) -> tensor<?xi32> {
^bb0(%arg0: tensor<?xi32>):
  // expected-error @+1 {{tfl.sin' op operand #0 must be tensor of 32-bit float values}}

    OpBuilder<(ins "Value":$cond, "Value":$x, "Value":$y),
    [{
    BuildSelectV2Op(&$_builder, $_state, cond, x, y);
  }]>];

  let hasOptions = 1;
}

def TFL_SinOp: TFL_Op<"sin", [
    Pure,
    TF_SameOperandsAndResultTypeResolveRef]> {
  let summary = "Sine operator";

  let description = [{
    Computes element-wise Sine of input
  }];