/*num_bits=*/8, is_signed_,
        /*narrow_range=*/is_weight, legacy_float_scale_);
  }
  if (const auto quant_type = mlir::dyn_cast_or_null<QuantizedType>(final_type);
      quant_type != nullptr) {
    return SetResultParams(op, /*result_index=*/0, quant_type);
  }
  return false;
}

bool QuantizationDriver::SetResultParams(Operation* op, const int result_index,

// BitcastOp
//===----------------------------------------------------------------------===//

int64_t GetTypeBitWidth(mlir::Type type) {
  if (auto quant_type = type.dyn_cast<mlir::quant::QuantizedType>()) {
    return quant_type.getStorageTypeIntegralWidth();
  }
  if (type.isIntOrFloat()) {
    return std::max(type.getIntOrFloatBitWidth(),
                    static_cast<unsigned>(CHAR_BIT));
  }

                    "loc": ["body", "grant_type"],
                    "msg": "Field required",
                    "input": None,
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {
            "detail": [
                {
                    "loc": ["body", "grant_type"],
                    "msg": "field required",

#include <memory>
#include <string>

#include <gmock/gmock.h>
#include <gtest/gtest.h>
#include "llvm/Support/Casting.h"
#include "mlir/Dialect/Quant/QuantOps.h"  // from @llvm-project
#include "mlir/Dialect/Quant/QuantTypes.h"  // from @llvm-project
#include "mlir/Dialect/SparseTensor/IR/SparseTensor.h"  // from @llvm-project
#include "mlir/IR/BuiltinTypes.h"  // from @llvm-project
#include "mlir/IR/MLIRContext.h"  // from @llvm-project

                    "loc": ["body", "grant_type"],
                    "msg": "Field required",
                    "input": None,
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {
            "detail": [
                {
                    "loc": ["body", "grant_type"],
                    "msg": "field required",

                    "loc": ["body", "grant_type"],
                    "msg": "Field required",
                    "input": None,
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {
            "detail": [
                {
                    "loc": ["body", "grant_type"],
                    "msg": "field required",

#include "tensorflow/core/framework/types.pb.h"

namespace mlir::quant::tensorflow {

bool IsTFQintType(const Type type) {
  return mlir::isa<TF::Qint8Type, TF::Qint16Type, TF::Qint32Type,
                   TF::Quint8Type, TF::Quint16Type>(type);
}

Type GetIntTypeFromTFQint(const Type type) {
  return TypeSwitch<Type, Type>(type)
      .Case<TF::Qint8Type>(
          [&type](Type) { return IntegerType::get(type.getContext(), 8); })

                sending the `client_id` and `client_secret` (if any) using HTTP Basic
                auth.
                """
            ),
        ] = None,
    ):
        self.grant_type = grant_type
        self.username = username
        self.password = password
        self.scopes = scope.split()
        self.client_id = client_id
        self.client_secret = client_secret

#include "mlir/Dialect/Func/Extensions/AllExtensions.h"  // from @llvm-project
#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project
#include "mlir/Dialect/Quant/QuantOps.h"  // from @llvm-project
#include "mlir/Dialect/Quant/QuantTypes.h"  // from @llvm-project
#include "mlir/Dialect/SCF/IR/SCF.h"  // from @llvm-project
#include "mlir/Dialect/Shape/IR/Shape.h"  // from @llvm-project
#include "mlir/InitAllDialects.h"  // from @llvm-project

@app.route('/oauth2/callback')
def callback():
    error = request.args.get('error', '')
    if error:
        return "Error: " + error

    authorization_code = request.args.get('code')

    data = {'grant_type': 'authorization_code',
            'code': authorization_code, 'redirect_uri': callback_uri}
    id_token_response = requests.post(
        token_url, data=data, verify=False,