t.Run(fmt.Sprintf("LitWidth %d", litWidth), func(t *testing.T) {
					var data []byte
					if litWidth == 6 {
						data = []byte{1, 2, 3}
					} else {
						data = []byte(`lorem ipsum dolor sit amet`)
					}
					var buf bytes.Buffer
					w := NewWriter(&buf, order, litWidth)
					if _, err := w.Write(data); err != nil {
						t.Errorf("write: %v: %v", string(data), err)
					}

      }

      if (!is_weight_constant) {
        if (!function_name.contains("matmul") &&
            !function_name.contains("einsum")) {
          return absl::InternalError(
              "Non-constant weights are not supported at the moment,"
              " except matmul and einsum.");
        } else if (!quant_options_.enable_two_input_tensors() &&
                   !is_unitwise_quantization_enabled) {

          function_name.contains("and_bias")) {
        spec->biases_params[2] = {{0, 1},
                                  quant::GetUniformQuantizedTypeForBias};
      }
    } else if (function_name.contains("einsum")) {
      spec->coeff_op_quant_dim[1] = -1;
      if (function_name.contains("with_bias")) {
        spec->biases_params[2] = {{0, 1},
                                  quant::GetUniformQuantizedTypeForBias};
      }

     */
    public void setEntryCompression(ZipEntryCompression entryCompression) {
        this.entryCompression = entryCompression;
    }

    /**
     * Enables building zips with more than 65535 files or bigger than 4GB.
     *
     * @see #isZip64()
     */
    public void setZip64(boolean allowZip64) {
        this.allowZip64 = allowZip64;
    }

    /**

# Delete downloaded .zip files.
go clean -modcache

# Check for updates.
go list -m -u rsc.io/breaker
stdout '^rsc.io/breaker v1.0.0 \[v2.0.0\+incompatible\]$'

# We should not have downloaded zips.
! exists $GOPATH/pkg/mod/cache/download/rsc.io/breaker/@v/v1.0.0.zip
! exists $GOPATH/pkg/mod/cache/download/rsc.io/breaker/@v/v2.0.0+incompatible.zip

-- go.mod --
module m

go 1.16

#include "tensorflow/compiler/mlir/quantization/tensorflow/quantization_options.pb.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"
#include "tensorflow/compiler/mlir/tensorflow/transforms/einsum.h"

namespace mlir {
namespace quant {
namespace {

using ::tensorflow::quantization::OpSet;

class PrepareLiftingPass
    : public PassWrapper<PrepareLiftingPass, OperationPass<func::FuncOp>> {
 public:

    func.return %5 : tensor<*xi32>
  }

   // Einsum with int32 accumulation.
  func.func private @internal_einsum_fn(
                         %input : tensor<*xi8>, %weight : tensor<*xi8>,
                         %input_scale : tensor<*xf32>, %input_zp : tensor<*xi32>,
                         %weight_scale : tensor<*xf32>, %weight_zp : tensor<*xi32>) -> tensor<*xi32> {

    # via
    #   -r requirements.in
    #   h5py
    #   jax
    #   keras-nightly
    #   ml-dtypes
    #   opt-einsum
    #   scipy
    #   tb-nightly
opt-einsum==3.3.0 \
    --hash=sha256:2455e59e3947d3c275477df7f5205b30635e266fe6dc300e3d9f9646bfcea147 \
    --hash=sha256:59f6475f77bbc37dcf7cd748519c0ec60722e91e63ca114e68821c0c54a46549
    # via

    )
    if use_kernel:
      model.einsum = model.einsum_with_kernel
      model_inputs = {'x': x}
    else:
      model.einsum = model.einsum_without_kernel
      model_inputs = {'x': x, 'y': y}

    saved_model_save.save(
        model, self._input_saved_model_path, signatures=model.einsum
    )

    signature_key = signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY

    # via
    #   -r requirements.in
    #   h5py
    #   jax
    #   keras-nightly
    #   ml-dtypes
    #   opt-einsum
    #   scipy
    #   tb-nightly
opt-einsum==3.3.0 \
    --hash=sha256:2455e59e3947d3c275477df7f5205b30635e266fe6dc300e3d9f9646bfcea147 \
    --hash=sha256:59f6475f77bbc37dcf7cd748519c0ec60722e91e63ca114e68821c0c54a46549
    # via