namex==0.0.8 \
    --hash=sha256:32a50f6c565c0bb10aa76298c959507abdc0e850efe085dc38f3440fcb3aa90b \
    --hash=sha256:7ddb6c2bb0e753a311b7590f84f6da659dd0c05e65cb89d519d54c0a250c0487
    # via keras-nightly
numpy==1.23.5 ; python_version <= "3.11" \
    --hash=sha256:01dd17cbb340bf0fc23981e52e1d18a9d4050792e8fb8363cecbf066a84b827d \
    --hash=sha256:06005a2ef6014e9956c09ba07654f9837d9e26696a0470e42beedadb78c11b07 \

namex==0.0.8 \
    --hash=sha256:32a50f6c565c0bb10aa76298c959507abdc0e850efe085dc38f3440fcb3aa90b \
    --hash=sha256:7ddb6c2bb0e753a311b7590f84f6da659dd0c05e65cb89d519d54c0a250c0487
    # via keras-nightly
numpy==1.23.5 ; python_version <= "3.11" \
    --hash=sha256:01dd17cbb340bf0fc23981e52e1d18a9d4050792e8fb8363cecbf066a84b827d \
    --hash=sha256:06005a2ef6014e9956c09ba07654f9837d9e26696a0470e42beedadb78c11b07 \

  (TF_RoundOp:$res TF_IntTensor:$input),
  (TF_IdentityOp $input)>;

// Implements TF Round on floats using basic operations. TF Round is specified
// as RoundHalfToEven to be compatible with Numpy.
def LowerRoundOpOnFloatTensor : Pat<
  (TF_RoundOp:$res TF_FloatTensor:$input),
  (TF_SelectV2Op
    (TF_EqualOp
      (TF_ConstOp:$zero (GetScalarOfFloatType<"0.0"> $input)),
      (TF_SelectV2Op:$rounded

// explicitly by running a TPUReplicatedOutput operation on the parallel device.
//
// TODO(allenl): There are some use-cases that are only supported by copying to
// host at the moment (e.g. debug print on a tensor, .numpy(), etc.). We either
// need to return something here or address these use-cases one by one.
TFE_TensorHandle* CopyTensorFromParallelDevice(TFE_Context* context,

from typing import List, Mapping, Optional, Sequence, Tuple

from absl.testing import parameterized
from mlir import ir
from mlir.dialects import stablehlo as stablehlo_dialect
import numpy as np
import tensorflow  # pylint: disable=unused-import

from tensorflow.compiler.mlir.stablehlo import stablehlo
from tensorflow.python.eager import def_function
from tensorflow.python.framework import dtypes

TF_CAPI_EXPORT extern void TFE_ContextEndStep(TFE_Context* ctx);

#ifdef __cplusplus
} /* end extern "C" */
#endif

#ifdef __cplusplus
// A workaround to ease conversion to and from numpy objects and
// TFE_TensorHandle's.
//
// TODO(ashankar): Figure out an alternative scheme that precludes the need for
// these API-boundary breaking methods.
namespace tensorflow {
class Tensor;

    [`tf.experimental.numpy`](https://www.tensorflow.org/api_docs/python/tf/experimental/numpy),
    which is a NumPy-compatible API for writing TF programs. This module
    provides class `ndarray`, which mimics the `ndarray` class in NumPy, and
    wraps an immutable `tf.Tensor` under the hood. A subset of NumPy functions
    (e.g. `numpy.add`) are provided. Their inter-operation with TF facilities is

# ==============================================================================
import os
import re
from typing import Mapping, Optional, Sequence

from absl.testing import parameterized
import numpy as np

from google.protobuf import text_format
from tensorflow.compiler.mlir.quantization.common.python import testing
from tensorflow.compiler.mlir.quantization.stablehlo import quantization_config_pb2 as qc

"""Base test class for quantize_model Tests."""
import os
import re
from typing import Collection, Iterable, Mapping, Sequence, Tuple, Optional, Union, List

from absl.testing import parameterized
import numpy as np
import tensorflow  # pylint: disable=unused-import

from tensorflow.compiler.mlir.quantization.tensorflow.python import representative_dataset as repr_dataset
from tensorflow.core.framework import function_pb2

"""Tests for quantize_model."""
# TODO(b/264234648): Refactor and cleanup this file.
import itertools
import os
from typing import Mapping, Optional, Sequence, Tuple, Union

from absl.testing import parameterized
import numpy as np
import tensorflow  # pylint: disable=unused-import

from tensorflow.compiler.mlir.quantization.common.python import testing