ConstBoolAttrFalse,
      ConstBoolAttrTrue),
    [(IsNhwcLayoutOp $attrs)]>;

// pattern to lower a stablehlo.composite of `jax` and `pytorch` image resize fuctions
// in `nearest`mode and with NCHW inputs to a tflite.resize_nearest_neighbor op.
// TODO(b/343278954): Move the creation of transposes to a separate prepare pass
// to avoid creating multiple pattern-rewrite rules for the same composite op.

  // OK
  %0 = "tf.AvgPool"(%arg0) {T = "tfdtype$DT_FLOAT", data_format = "NCHW", ksize = [1, 1, 3, 6], padding = "VALID", strides = [1, 1, 3, 1]} : (tensor<1x16x6x6xf32>) -> tensor<1x16x1x1xf32>
  // Unsupported ksize
  %1 = "tf.AvgPool"(%arg0) {T = "tfdtype$DT_FLOAT", data_format = "NCHW", ksize = [3, 1, 3, 6], padding = "VALID", strides = [1, 1, 3, 1]} : (tensor<1x16x6x6xf32>) -> tensor<1x16x1x1xf32>

//===----------------------------------------------------------------------===//
def IsDataFormatNHWC : ConstantAttr<TF_ConvnetDataFormatAttr, "\"NHWC\"">;
def IsDataFormatNCHW : ConstantAttr<TF_ConvnetDataFormatAttr, "\"NCHW\"">;

class I32VectorElementsAttr<int len> : ElementsAttrBase<
  CPred<"$_self.isa<DenseIntElementsAttr>() &&"
      "$_self.cast<DenseIntElementsAttr>().getType()."
      "getElementType().isSignlessInteger(32)">,

```
With `src_format` of `NHWC`, `dst_format` of `NCHW`, and input:
```
[1, 2]
```
, the output will be:
```
[1, 2]
```
  }];

  let arguments = (ins
    Arg<TF_I32OrI64Tensor, [{Tensor of rank 1 or 2 in source data format.}]>:$x,

    DefaultValuedOptionalAttr<StrAttr, "\"NHWC\"">:$src_format,
    DefaultValuedOptionalAttr<StrAttr, "\"NCHW\"">:$dst_format
  );

// is handled, which can optionally require a general broadcast of the
// 'bias' term in a way that is not compatible with the standard left-padded
// broadcast semantics (i.e. NCHW will broadcast into dimension 1).
// The correct 'bias' broadcast will be synthesized manually.
class ConvertBiasAddOp : public OpRewritePattern<TF::BiasAddOp> {
 public:
  using OpRewritePattern::OpRewritePattern;

*   Add Mel-Frequency Cepstral Coefficient support to `tf.contrib.signal` (with
    GPU and gradient support).
*   Add a self-check on `import tensorflow` for Windows DLL issues.
*   Add NCHW support to `tf.depth_to_space` on GPU.
*   TensorFlow Debugger (tfdbg):
    *   Add `eval` command to allow evaluation of arbitrary Python/numpy
        expressions in tfdbg command-line interface. See